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2018MNRAS.476.5417S__McCray_&_Kafatos_1987_Instance_1

According to our interpretation, the observed high velocity dispersion region in zone ‘F’ associated with the zone totally empty of gas between the two opposite velocity clouds (that the 3Dbarolo model would instead predict to be filled) resembles an expanding superbubble. Superbubbles are known to be associated with very massive stars (OB-associations): strong stellar winds and subsequent SN explosions from those stars inject energy and mass into the ambient ISM, creating shock fronts that sweep-up the ISM (e.g. Castor, McCray & Weaver 1975). As the SN explosions start occurring within the cavity formed by the stellar wind bubbles, super-bubbles are created (e.g. McCray & Kafatos 1987), which may eventually reach kiloparsec sizes. These explosions never form a visible SNR, but instead expend their energy in the hot interior as sound waves. Both stellar winds and stellar explosions thus power the expansion of the superbubble in the ISM. The interstellar gas swept up by superbubbles generally cools, forming a dense shell around the cavity (observed in Hi and Hα). The bubble interior contains hot (>106 K), rarefied material, usually associated with extended diffuse X-ray emission (thus appearing as an empty cavity in cold and molecular gas). In this interpretation, the two blobs of gas above and below the observed empty cavity in region ‘F’ (at +1.5 arcsec offset, with velocities of +70 and −70 km s−1, corresponding to the two peaks in Fig. 6), can be easily explained as gas surrounding the ‘superbubble’ being thrown away in different directions by the expanding spherical shell (see Kamphuis, Sancisi & van der Hulst 1991; Boomsma et al. 2008, for detected velocities up to 100 km s−1 associated with ‘holes’ in Hi). In Fig. 13, we show different CO(2–1) velocity channels, where the ‘superbubble’, surrounded by material moving in opposite directions (e.g. peaks at −70 and 70 km s−1, not present at the systemic velocities), shows up as an empty area (encircled in the plot), with a clear shock front at its left-hand side, peaking around the systemic velocities (≃0 km s−1).

2018AandA...609A..13K__Mucciarelli_et_al._(2017)_Instance_2

Gaia 1 is a star cluster that was recently discovered by Koposov et al. (2017) in the first Gaia data release (Gaia Collaboration 2016), alongside with another system of lower mass. Its observation and previous detections were seriously hampered by the nearby bright star Sirius, which emphasized the impressive discovery power of the Gaia mission. This object was first characterized as an intermediate-age (6.3 Gyr) and moderately metal-rich (−0.7 dex) system, based on isochrone fits to a comprehensive combination of Gaia, 2MASS (Cutri et al. 2003), WISE (Wright et al. 2010), and Pan-STARRS1 (Chambers et al. 2016) photometry. Hence, this object was characterized by Koposov et al. (2017) as a star cluster, most likely of the globular confession. Further investigation of Gaia 1 found a metallicity higher by more than 0.5 dex, which challenged the previous age measurement and rather characterized it as a young (3 Gyr), metal-rich (−0.1 dex) object, possibly of extragalactic origin given its orbit that leads it up to ~1.7 kpc above the disk (Simpson et al. 2017). Subsequently, Mucciarelli et al. (2017) measured chemical abundances of six stars in Gaia 1, suggesting an equally high metallicity, but based on their abundance study, the suggestion of an extragalactic origin was revoked. While a more metal-rich nature found by the latter authors conformed with the results by Simpson et al. (2017), the evolutionary diagrams of both studies are very dissimilar and could not be explained by one simple isochrone fit. In particular, it was noted that “the Simpson et al. (2017) stars do not define a red giant branch in the theoretical plane, suggesting that their parameters are not correct” (Fig. 1 of Mucciarelli et al. 2017). Such an inconsistency clearly emphasizes that a clear-cut chemical abundance scale is inevitable for fully characterising Gaia 1, and to further allow for tailored age determinations, even more so in the light of the seemingly well-determined orbital characteristics, Thus, this work focuses on a detailed chemical abundance analysis of four red giant members of Gaia 1, based on high-resolution spectroscopy, which we complement with an investigation of the orbital properties of this transition object. Combined with the red clump sample of Mucciarelli et al. (2017) and reaching down to the subgiant level (Simpson et al. 2017), stars in different evolutionary states in Gaia 1 are progressively being sampled.

2021MNRAS.503.2108P__Andresen_et_al._2017_Instance_1

CCSNe are also of interest for GW astronomy as targets in their own right. As the sensitivity of GW detectors increases, they will begin to detect not only binary mergers but also other lower amplitude sources of GWs such as CCSNe. Accurate knowledge of the GW emission from CCSNe will be essential for detection and parameter estimation. The GW signal from rotational core bounce has already been well covered in the literature (e.g. Dimmelmeier et al. 2008; Abdikamalov et al. 2014; Fuller et al. 2015; Richers et al. 2017). In the non-rotating case, the GW emission from the post-bounce phase has been studied using self-consistent 3D simulations by many groups (Kuroda, Kotake & Takiwaki 2016; Andresen et al. 2017, 2019; Kuroda et al. 2017, 2018; Powell & Müller 2019, 2020; Radice et al. 2019; Andresen, Glas & Janka 2020; Mezzacappa et al. 2020; Pan et al. 2020). The structure of the GW emission has shown common features in different simulations from recent years. The dominant emission feature in the GW emission is due to the quadrupolar surface f/g mode 1 of the proto-neutron star (PNS), which produces GW frequencies rising in time from a few hundred Hz up to a few kHz (Müller, Janka & Wongwathanarat 2012; Sotani et al. 2017; Kuroda et al. 2018; Morozova et al. 2018; Torres-Forné et al. 2018, 2019). In addition, some models (Kuroda et al. 2016, 2017; Andresen et al. 2017; Mezzacappa et al. 2020; Powell & Müller 2020) exhibit low-frequency GW emission due to the standing accretion shock instability (SASI; Blondin, Mezzacappa & DeMarino 2003; Blondin & Mezzacappa 2006; Foglizzo et al. 2007). In rapidly rotating models, very strong GW emission can also occur during the post-bounce phase due to a corotation instability (Takiwaki & Kotake 2018). The emerging understanding of the GW emission features has led to the formulation of universal relations for the GW emission (Torres-Forné et al. 2019) and paved the way for phenomenological modelling for CCSN signals (Astone et al. 2018). Further work is still needed, however, to extend these models to fully explore CCSN GW signals from across the progenitor parameter space. The majority of 3D simulations that include GW emission are for progenitor stars below $30\, \mathrm{M}_{\odot }$. In this paper, we perform simulations of high-mass Population III (Pop-III) stars in the pulsational pair instability regime to expand the parameter space coverage of 3D simulations and to provide further insights into the massive and very massive star remnant BH population.

2017MNRAS.469.3270V__Chakrabarti,_Jin_&_Arnett_1987_Instance_1

Observations show that the core temperatures of powerful AGN jets are estimated to be quite high (Moellenbrock et al. 1996). So the jets are hot to start with in this paper too. The advective disc model, as in most disc models, comes with a variety of inner disc temperatures. Simulations of advective discs for high viscosity parameter produced T ≳ 1012K in the PSD (Lee et al. 2016). Moreover, in the presence of viscous dissipation in curved space–time, the Bernoulli parameter (−hut) may increase by more than 20 per cent of its value at large distance and produce very high temperatures in the PSD (Chattopadhyay & Kumar 2016). For highly rotating BHs too, the temperatures of the inner disc easily approach 1012 K. It must also be remembered that inner regions of the accretion disc can be heated by the Ohmic dissipation, reconnection, turbulence heating or MHD wave dissipation may heat up the inner disc or the base of the jet (Pudritz 2003). High temperatures in the accretion disc can induce exothermic nucleosynthesis too (Chakrabarti, Jin & Arnett 1987; Hu & Peng 2008). All these processes taken together in an advective disc will produce very hot jet base. We do not specify the exact processes that will produce very hot jet base, but would like to emphasize that it is quite possible to achieve so. One may also wonder that if the jets are indeed launched from the disc, and how justified is it to consider non-rotating jets. Phenomenologically speaking, if jets have a lot of rotation then it would not flow around the axis of symmetry and, therefore, either it has to be launched with less angular momentum or it has to lose most of the angular momentum with which it is launched. It has been shown that viscous transport removes significant angular momentum of the collimated outflow close to the axis (Lee et al. 2016). Since the jet is launched with low angular momentum and it is further removed by viscosity or by the presence of magnetic field; therefore, the assumption of non-rotating hot jet is quite feasible. Incidentally, similar to this study, there are many theoretical studies of jets that have been undertaken under similar assumptions of non-rotating, hot jets at the base (Fukue 1987b; Falcke 1996; Memola et al. 2002).

2022MNRAS.509..314F__Dikpati_et_al._2020_Instance_1

Magneto-Rossby waves arise due to the inhomogeneity of the Coriolis force depending on latitude on a sphere in rotating astrophysical plasma by analogy with a neutral fluid (Petviashvili & Pokhotelov 1992; Onishchenko et al. 2004; Vallis 2006; Onishchenko, Pokhotelov & Astafieva 2008; Zeitlin 2018). It should be noted that owing to the presence of Lorentz force full vorticity is no longer conserved and in the case of a strong magnetic field magneto-Rossby waves tend to Alfvén wave solutions almost on all wavenumber range (Zaqarashvili et al. 2021). Magneto-Rossby waves are basic mechanism in variability of various objects in plasma astrophysics. Magneto-Rossby waves determine the large-scale dynamics of the Sun and stars (Hughes et al. 2007; Zaqarashvili et al. 2007, 2011; Dikpati et al. 2020; Mandal & Hanasoge 2020; Raphaldini et al. 2020), dynamics of magnetoactive atmospheres of exoplanets captured by tides from the host star (Cho 2008), flows in accretion discs of neutron stars (Inogamov & Sunyaev 2010). Despite the difficulty of observing Rossby waves in astrophysical plasma, they have recently been detected on the Sun (McIntosh et al. 2017; Zaqarashvili & Gurgenashvili 2018; Loeptien et al. 2018; Liang et al. 2019). We also note a number of important studies on the effect of Magneto-Rossby waves on solar seasons (Lou 2000; Dikpati et al. 2017, 2018) and space weather (Dikpati & McIntosh 2020; Dikpati, McIntosh & Wing 2021). In addition, magneto-Rossby waves play a key role in the occurrence of zonal flows in two-dimensional magnetohydrodynamic turbulence (Tobias, Diamond & Hughes 2007; Zinyakov & Petrosyan 2018, 2020). The weakly non-linear theory of magneto-Rossby waves in the quasi-two-dimensional MHD single-layer model has been developed in Klimachkov & Petrosyan (2017a) and in the presence of large-scale compressibility in Klimachkov & Petrosyan (2018). In Fedotova et al. (2020), MHD shallow water approximation has been extended to the case of external vertical magnetic field and stratified flows. Linear and weakly non-linear theory of magneto-Rossby waves in a rotating stratified plasma in the quasi-two-dimensional MHD approximation in two-layer model has been developed. In Klimachkov & Petrosyan (2017a, 2018) and Fedotova et al. (2020), the phase matching conditions have been investigated and non-linear interactions of three magneto-Rossby waves have been found. In Raphaldini & Raupp (2015), Raphaldini et al. (2019, 2020) influence of non-linear dynamics of magneto-Rossby waves on cyclic nature of solar magnetic activity is studied. Non-linear interactions of magneto-Rossby waves are associated with the duration of the solar cycle. In Raphaldini et al. (2020) is shown that irregular transitions in wave amplitudes resemble the observed time series of solar activity. In Klimachkov & Petrosyan (2017a, 2018), Fedotova et al. (2020) magneto-Rossby waves have been investigated in the β-plane approximation for the Coriolis force. The β-plane approximation describes rotating spherical plasma flows in a local Cartesian coordinate system. In this case, the Coriolis parameter changes little with small changes in latitude and expands in a series up to the first order in latitude.

2021AandA...648A...5M__Windhorst_et_al._(1990)_Instance_1

Another important consistency check regards the angular size distribution of the sources. Figure 6 shows the cumulative size distributions of the final catalogs combined together, in four flux density bins (yellow solid lines). Such distributions can be considered reliable only down to a flux-dependent minimum intrinsic size (see vertical gray lines), below which most of the sources cannot be reliably deconvolved and they are conventionally assigned Θ = 0. The observed distributions are compared with various realizations of the cumulative distribution function described by Eq. (6), obtained by varying either the function exponent q (left and right columns respectively) or the assumed median size – flux relations (see various black lines).The original function proposed by Windhorst et al. (1990) (Eq. (6) with q = 0.62, see left column) does provide a good approximation of the observed distributions, when assuming the original Θmed − S relation described by Eq. (7), only at flux densities S150 MHz≳10 mJy (see long-dashed lines). This is perhaps not surprising considering that this relation was calibrated at 1.4 GHz down to a few mJy fluxes. At the lowest flux densities (S150 MHz≲1 mJy) we need to assume a steepening of the parameter m (see Eq. (8)), to get a good match with observations (dotted line in the top left panel). This is consistent with what proposed for higher frequency deep surveys (as discussed earlier in this section). At intermediate fluxes (S150 MHz ~ 1−10) mJy, on the other hand, none of the discussed median size – flux relations can reproduce the observed size distribution (see second-row panel on the left). It is interesting to note, however, that if we assume a steeper exponent for the distribution function described by Eq. (7) (i.e., q = 0.80), we get a very good match with observations at all fluxes, when assuming a flux-dependent scaling factor (k = k(S); see Eq. (9)) for the Windhorst et al. (1990) median size – flux relation (black solid lines on the right). The median sizes derived from the T-RECS simulated catalogs (Bonaldi et al. 2019) also provide good results for q = 0.80 (dot-dashed lines on the right), except again at intermediate fluxes (S150 MHz ~ 1−10), where they show strong discrepancies with observations also in Fig. 5. This seems to indicate that the number density of extended radio galaxies in this flux density range is over-estimated in the T-RECS simulated catalogs.

2021MNRAS.507.1229P__Lyman_et_al._2016_Instance_1

In this work, we present well-calibrated optical photometric (−0.2 to +413 d), polarimetric (−2 to +31 d) and optical (−5 to +391 d), NIR (−5 to +22 d) spectroscopic studies of SN 2012au, based on data obtained using many observational facilities around the globe. Analysis based on our photometric observations suggests that SN 2012au appears to be one of the most luminous SNe Ib (MB, peak = −18.06 ± 0.12 mag), though fainter than the threshold limit of SLSNe I (M$_\mathrm{ g}\, \lt -$19.8 mag; Quimby et al. 2018). The MR, peak (∼ –18.67 ± 0.11 mag) of SN 2012au is brighter than the average values of SNe Ib and Ic, but closer to those reported for SNe Ic-BL (Drout et al. 2011). Similarly, the peak bolometric luminosity of SN 2012au (∼ [6.56 ± 0.70] × 1042 erg s−1) is higher than the mean peak luminosities of SNe Ib and Ic, but still lower than those of SNe Ic-BL (Lyman et al. 2016). Using the early bolometric light curve of SN 2012au, the estimated values of Mej, Ek, MNi, and T0 are ∼5.1 ± 0.7 M⊙, ∼ (4.8 ± 0.6) × 1051 erg, ∼0.27−0.30 M⊙, and ∼66.0 ± 9.4 d, respectively. These physical parameters of SN 2012au are close to those inferred for SN 2009jf (a bright SN Ib: Sahu et al. 2011) and – on average – larger than for classical SNe Ib/c but smaller than for some SNe Ic-BL. SN 2012au manifests larger Mej and MNi in comparison with most of the SNe IIb, Ib, and Ic, which may be the prime reason behind the luminous peak of SN 2012au, as seen in the case of SLSNe I (Nicholl et al. 2015). On the other hand, light-curve decline rates of SN 2012au (at phases ≥+40 d) in all the optical bands are shallower than typically observed in the case of SNe Ib and slow-decaying SLSNe I, and theoretically predicated for 56Co $\rightarrow \, ^{56}$fe decay. As SN 2012au exhibits comparatively larger Mej, a larger optical depth resulting in a larger diffusion time-scale (for the trapped energy to cross the outer envelope) could broaden the light curve. Therefore, high trapping of gamma-rays at late phases or higher opacity of massive ejecta are among the plausible interpretations for the modest luminosity decline rate of SN 2012au in comparison with other SNe Ib (Clocchiatti & Wheeler 1997). However, smoothly distributed circumstellar media up to a larger radius could be another possibility behind the late-time shallower decay rate for SN 2012au, but an absence of the CSMI in the late-time spectra ruled out this scenario (Milisavljevic et al. 2018). The late-time bolometric light curve of SN 2012au is better constrained by $L~\varpropto\, t^{-2}$, a conventional magnetic dipole equation. Hence for SN 2012au the shallower decay of the late-time light curve might be a potential indicator of a central engine powering source that is accelerating the inner ejecta.

2022AandA...665A.118F__Carlsson_et_al._2016_Instance_1

Despite significant advances, the solar wind remains challenging to model (and importantly forecast) due to the large range of scales that need to be incorporated. It is well known that energy is injected into the corona at all scales, from magnetohydrodynamic (MHD) waves (Nutto et al. 2012; Van Doorsselaere et al. 2020) to flares and coronal mass ejections with global extent (Aschwanden et al. 2017; Green et al. 2018; Wyper et al. 2018). In addition to the range of spatial scales, heating events take place on a variety of timescales (Hollweg 1973; Viall & Klimchuk 2017). Putting aside large-scale eruptions so as to focus on the quasi-steady input of energy into the corona, it is possible to distinguish three broad magnetic configurations of the solar atmosphere for modelling purposes. These are the quiet Sun (Danilovic et al. 2010; Rempel 2014), active or enhanced regions (Carlsson et al. 2016; Chen et al. 2021), and coronal holes (Wójcik et al. 2019). In each of these configurations, energy is channelled from the convection into the low corona. Coronal holes are the dominant source of the solar wind in the heliosphere (Cranmer et al. 2017; Stansby et al. 2021), typically producing the fast solar wind (McComas et al. 2008; Ebert et al. 2009; Macneil et al. 2020a; Wang 2020). The magnetic field configuration of a coronal hole is relatively simple, compared with the quiet Sun and active regions, given that the field is principally open to the solar wind (Lowder et al. 2017; Hofmeister et al. 2019). However, there are still a range of dynamic processes taking place, such as the braiding of magnetic field lines (Wedemeyer-Böhm et al. 2012; Wedemeyer et al. 2013; Huang et al. 2018) and the emergence of new magnetic flux (Murray et al. 2009). These can trigger the formation of jets (Shen et al. 2017; Yang et al. 2017) and other phenomena, which are then observed as spicules (Martínez-Sykora et al. 2017; Bose et al. 2021) or fibrils (Hansteen et al. 2006; Leenaarts et al. 2015).

2020ApJ...903L..22T__Vuitton_et_al._2007_Instance_3

While the Loison et al. (2015) CH3C3N model corroborates the upper atmospheric abundance of C4H3N inferred by Vuitton et al. (2007) from the T5 INMS measurements (a factor of 2 higher than those derived from T40 in Vuitton et al. 2019), a large disparity between the photochemical models (and within the ensemble of models produced by Loison et al. 2015) arises in the lower atmosphere due to the poorly constrained C4H3N branching ratios and reaction rate coefficients at temperatures appropriate for Titan. Aside from electron dissociative recombination of C4H3NH+ (Vuitton et al. 2007), neutral production of CH3C3N can occur in a few ways, as found through crossed beam experiments and theoretical and photochemical modeling studies (Huang et al. 1999; Balucani et al. 2000; Zhu et al. 2003; Wang et al. 2006; Loison et al. 2015). First, through the reactions of larger hydrocarbons with CN radicals, 1 2 Similarly, with CCN radicals following their formation through H + HCCN (Takayanagi et al. 1998; Osamura & Petrie 2004) and subsequent reactions with ethylene, 3 or through the chain beginning with acetylene, 4 While both reactions (3) and (4) are found to be equally likely by Loison et al. (2015), the production of CCN via H + HCCN is not well constrained, and the synthesis of CH3C3N through CN radicals (Equations (1) and (2)) are not included in their photochemical model. Additionally, cyanoallene may be produced through reactions (1)–(4) instead of (or in addition to) methylcyanoacetylene. CH3C3N itself may form the protonated species, C4H3NH+, through reactions with the HCNH+ and C2H5+ ions producing HCN and C2H4, respectively (Vuitton et al. 2007). The other mechanism for forming C4H3NH+ is through the combination of HCN and l-C3H3+, though the reaction rate coefficient for this reaction and the abundance of l-C3H3+ are unknown (Vuitton et al. 2007). As such, the production and loss pathways for both C4H3NH+ and CH3C3N require further investigation.

2020AandA...636A.103H__Xu_&_Borovsky_2015_Instance_1

Solar wind categorization schemes rely on different solar wind properties to identify the solar wind type and adopt mainly one of the following two approaches: (1) Composition-based schemes exploit the oxygen and carbon charge-state composition of the solar wind (Zhao & Fisk 2010; von Steiger et al. 2000). Based on the assumption that the charge states observed in the solar wind are determined in the solar corona and are not significantly changed thereafter, lower (higher) charge states are associated with source regions of the respective solar wind stream with comparatively low (high) electron temperatures. Because the charge state is not expected to change during the travel time of the solar wind, composition-based criteria are well suited to identify different solar source regions. Transport effects due to, for instance, compression regions in stream interaction regions and wave-particle interaction are not directly reflected in the charge-state composition. Stream interaction regions tend to be characterized by a (gradual or abrupt) transition in the oxygen charge-state compositions. From the charge-state information alone, stream interaction regions cannot be uniquely identified, and their solar source regions cannot be unambiguously determined without additional or context information. (2) Proton plasma properties provide an alternative to determine the solar wind type (Xu & Borovsky 2015; Camporeale et al. 2017). A clear advantage of this approach is that the required observables are available from more spacecraft. Unlike the charge-state composition, the proton speed, proton density, proton temperature, and magnetic field strength (and derived quantities such as the specific entropy and the Alfvén speed) are all susceptible to transport effects. In particular, these quantities show radial gradients throughout the heliosphere (Marsch et al. 1982; Bale et al. 2019; Kasper et al. 2019). Thus, a solar wind categorization based on threshold values for these quantities can be expected to depend on position. In particular, the solar wind proton temperature is not a tracer of the coronal (electron) temperature. The solar wind proton temperatures show the opposite effect (von Steiger et al. 2000): high solar wind proton temperatures are observed for coronal hole wind (which originates from comparatively cool coronal regions), while low solar wind proton temperatures appear in the slow solar wind (which likely originates in hot coronal regions). The solar wind proton temperature is probably strongly influenced by transport effects, in particular, by wave-particle interactions. In addition, proton temperature, proton density, and magnetic field strength all show characteristic variations in stream interaction regions. Solar wind categorization schemes based on proton plasma properties are therefore well suited to assess the effect of solar wind evolution during its travel time. However, these transport effects can blur the tracers of the solar origin of the solar wind. For approaches based on charge-state composition and on proton plasma, the respective threshold values are usually determined heuristically and vary in the literature. Mainly as a result of their availability, solar wind electron data (e.g., Lin et al. 1995; Wilson et al. 2018) are typically not considered for solar wind classifications, although their properties, for example, the electron temperature and the electron-proton collisional age, can be expected to be informative in this context. Future improvements on solar wind classification would most likely benefit considerably from including electron data. The collisional age (or Coulomb number) has been proposed as an ordering parameter for the solar wind in Kasper et al. (2008), Tracy et al. (2016), and Maruca et al. (2013). The collisional age can be interpreted as counting the number of 90°-equivalent collisions during the travel time from the Sun to the observing spacecraft. This notion of the collisional age relies on the simplifying assumption that the solar wind parameters are constant during the solar wind travel time. Maruca et al. (2013) introduced an improvement in the computation of the collisional age that takes into account that the underlying quantities are not constant during the travel time of the solar wind.

2016ApJ...822....7K__Kumar_et_al._2012_Instance_1

To investigate the particle precipitation or transport sites during the flare, we used HXR 25–50 keV and NoRH 17/34 GHz images. We chose the Pixon algorithm (Metcalf et al. 1996) for the RHESSI image reconstruction. The Pixon method is considered to be the most accurate algorithm (Hurford et al. 2002). The integration time for each image was 20 s. We utilized NoRH 5 s cadence intensity images (R+L) at 17 and 34 GHz. Figure 4 displays the HXR 25–50 keV (blue) and NoRH 17 GHz (red) contours overlaid on the AIA 1600 Å images at ∼23:51 UT. These images are used at the peak time of each of the bursts observed in the HXR 25–50 keV and microwave channels. Figure 4(a) shows a small filament rising at the flare site. We can easily identify the two legs of the filament (marked by N and S in the figure). Generally, the filaments are observed in the chromospheric images (e.g., Hα and AIA 304 Å). However, if the kink-unstable filament is heated during magnetic reconnection, it is often observed in the AIA 1600 Å channels (e.g., Kumar et al. 2012 and Kumar & Cho 2014). The locations of both the 25–50 keV sources and the 17 GHz source are almost at the quasi-circular ribbon. However, their centroids constructed at the 90% level of the peak intensity are not cospatial. We note that the 25–50 keV sources (centroid) are located close to the legs of the filament, whereas the 17 GHz source is located at the northern leg of the filament. It seems that these sources are at the footpoints of an underlying flare loop. To identify the location of the flare loop, we selected the AIA 94 Å hot channel image at 23:53 UT. In this image (panel b), we show the NoRH 34 GHz contours (yellow) overlaid on AIA 94 Å images at ∼23:53 UT. This is done to show the coronal loops associated with the eruption of the small filament. The overlying 34 GHz source is cospatial with the small loop located above the quasi-circular ribbon. This 34 GHz emission may be the evidence of trapped nonthermal electrons in the loop. The rising filament is heated during reconnection with the ambient fields and then decays into an untwisting jet, as seen in Figures 4(b)–(e). Furthermore, during ∼23:53–23:59 UT, we see the footpoint HXR sources. The NoRH 17 GHz sources cover the quasi-circular ribbon (Figures 4(c)–(d)) and could be the emission from the trapped electrons in the loop. This suggests that the bursts are most likely caused by the same population of nonthermal electrons with different energies.

2015MNRAS.446.1293C__Hauser_&_Dwek_2001_Instance_1

The contribution to the submm background from LBGs is still poorly constrained; however, our data can finally address this question, since we now have a robust detection of the average 850 μm flux density of LBGs at three epochs, at least those with ultraviolet luminosities of L1700 ≈ 1029 erg s−1 Hz−1, characteristic of galaxies in our sample (Table 2). Using our average stacked 850 μm flux densities, we estimate surface brightness densities of 1700, 600, and 100 mJy deg−2 of LBGs at z ∼ 3, 4, and 5, respectively. By comparison, the total background at 850 μm inferred from COBE-FIRAS is 3.1–4.4 × 104 mJy deg−2 (Puget et al. 1996; Fixsen et al. 1998; Hauser & Dwek 2001; Lagache, Puget & Dole 2005). Summing these separate surface brightness densities together, we find that the LBGs with L1700 > 1029 erg s−1 Hz−1 in our z ∼ 3, 4, and 5 samples comprise around 6–8 per cent of the submm background at 850 μm (where the range of values simply reflects the uncertainty in the COBE-FIRAS result). However, the true contribution from LBG-like galaxies to the submm background will come from a wider range in redshift, not just from the rather narrow redshift slices we have sampled (see Fig. 1), and from sources falling out of our samples due to incompleteness. To determine the total (corrected) contribution from LBGs over 3 z 5, we assume that LBGs have a constant comoving number density (which is a reasonable assumption since the bright end of the luminosity function for LBGs shows little evolution over 3 z 5; Bouwens et al. 2007; McLure et al. 2009; Reddy & Steidel 2009). Starting with the z ∼ 3 sample (which is our most complete subsample of LBGs), we can integrate over the comoving volume element for this redshift range, scaling the LBG submm background contribution accordingly. We find that the total contribution to the submm background from LBGs over the redshift range 3 z 5 is likely to be closer to 14–20 per cent. This result is consistent with Webb et al. (2003), who estimated an upper limit to the contribution to the submm background from 1 z 5 of less than 20 per cent.

2022MNRAS.517.2383B__Strat,_Morgenstern_et_al._2009_Instance_1

The UK Chemistry and Aerosol (UKCA) model (Morgenstern et al. 2009; O’Connor et al. 2014; Archibald et al. 2020) is a framework that we use to describe the global atmospheric chemical composition of our simulated exoplanet. UKCA includes aerosol and gas-phase chemistry and is coupled to the UM dynamics. It uses the UM components for large-scale advection, convective transport, and boundary layer mixing of its aerosol and chemical tracers (O’Connor et al. 2014; Archibald et al. 2020). UKCA contains a large number of gas-phase and heterogeneous chemical reactions, some of which we have included in our chemical network. Furthermore, the chemistry schemes in UKCA describe wet and dry deposition (Giannakopoulos et al. 1999). In this study, we use the Stratospheric (Strat, Morgenstern et al. 2009) and Stratospheric-Tropospheric (StratTrop, Archibald et al. 2020) chemistry schemes. Originally, StratTrop includes 75 chemical species that are connected by 283 reactions (Archibald et al. 2020). We used a reduced version of the UKCA chemistry schemes (Table 2) to quantify the impact of the different chemical mechanisms on the atmospheric chemistry of a tidally-locked exoplanet. First, we use a simple network that describes the Chapman mechanism of ozone formation (Chapman 1930), following Yates et al. (2020). Second, we add the reactive hydrogen (HOx) catalytic cycle, where HOx denotes the ensemble of atomic hydrogen (H), the hydroxyl radical (OH) and the hydroperoxy radical (HO2). We include this cycle to account for ozone chemistry following the oxidation and photolysis of water vapour. Lastly, we add the nitrogen oxide (NOx) catalytic cycle, including NO and nitrogen dioxide (NO2) to the network. We also include other oxidized nitrogen species, such as nitrate (NO3), nitrous oxide (N2O), and the reservoirs nitric acid (HNO3), and dinitrogen pentoxide (N2O5). Collectively, these nitrogen species belong to the NOy family and can also influence ozone chemistry. In our simulations, lightning is the main source of NO that initiates further NOy chemistry, as described in Section 2.4. In the upper atmosphere, the slow termolecular reaction between N2 and O(1D) provides another source of NOy, but this does not impact the lightning-induced chemistry that occurs at altitudes below 20 km.

2019AandA...623A...1I__Rudick_et_al._(2009)_Instance_1

From the observational side, the deep FDS data further confirm that the bulk of the gravitational interactions between galaxies happened on the W-NW sub-clump of the cluster. In fact, this is the only region of the cluster, inside the virial radius, where the intra-cluster baryons (diffuse light and GCs) are found, that is, the bridge between NGC 1399 and FCC 184 (Iodice et al. 2016), the intra-cluster light and GCs between FCC 184, FCC 170, and FCC 161 (Iodice et al. 2017b), and the new faint filaments between FCC 143 and FCC 147 (see Sect. 5.1 and Fig. 13). The gravitational interactions could have also modified the structure of the galaxy outskirts and produced the intra-cluster baryons. Compared with simulations by Rudick et al. (2009), the diffuse form observed for the ICL is consistent with the scenario where this component formed by stripped material from the outskirts of a galaxy in a close passage with the cD (Iodice et al. 2017b). In this area of the cluster, the stellar envelope of some ETGs is asymmetric, appearing more elongated and twisted in one direction, while the outskirts of galaxies at larger distances from the cluster centre have a more regular shape. Mastropietro et al. (2005) show how harassment can induce twists in the outer isophotes of dwarf galaxies. More massive and luminous galaxies, like the elliptical galaxies in this region of the Fornax cluster, have a deeper potential well, therefore the stripping of stars by harassment implies even stronger tidal forces. A disturbed morphology in galaxy outskirts could also result from the ongoing accretion of smaller satellites. Simulations on the mass accretion and stellar halo formation for different stellar masses (1010 − 1013 M⊙) show that the outskirts of galaxies (for μr ∼ 27 − 31 mag arcsec−2) appear with a quite disturbed morphology and with an overall elongated shape (Michel-Dansac et al. 2010; Cooper et al. 2015; Monachesi et al. 2018). The structure of the stellar envelope, as well as the shape of the SB profile, depends on the mass and number of the accreted progenitors. The ETGs showing asymmetric and diffuse envelopes (FCC 161, FCC 167, FCC 184, see Sect. 5.1 and Fig. 13) are in range of stellar mass (∼3 − 10 × 1010 M⊙) comparable with simulations and they could still build up their envelope. As noticed by Iodice et al. (2017b), a fraction of the ICL population in this region of the cluster could also come from lower mass dwarf galaxies that are tidally disrupted in the potential well of the massive galaxies, which are therefore contributing to the mass assembly in their halo. This is further supported by a recent study from Venhola et al. (2017), based on FDS data, that found a drop in the number density of LSB galaxies at cluster-centric distances smaller than ∼180 kpc.

2022MNRAS.516.1539O__Yang_et_al._2022_Instance_1

At intermediate energies, Fig. 1 shows that non-thermal bremsstrahlung processes become more important. We find this dominates the keV X-ray emission during the first ∼2 Myr. While OY22 demonstrated this non-thermal emission would likely not be detectable in external galaxies, X-ray observations towards the Galactic Fermi bubbles reveal substantially higher emission than that computed with our model at a similar bubble age (see the comparison in OY22; also Snowden et al. 1997; Kataoka et al. 2013; Predehl et al. 2020). Although this may suggest better X-ray detection prospects for external galaxy bubbles than our results would imply, we note that these Galactic observations may include a very significant thermal bremsstrahlung contribution from all the gas in the Milky Way halo, which likely extends to a radius of ∼250 kpc (i.e. far larger than the size of our simulation box, see e.g. Blitz & Robishaw 2000; Grcevich & Putman 2009), the Galactic bulge, and gas heated by the shocks associated with the bubble (Yang et al. 2022; see also Zhang & Guo 2021), none of which is included in our model (and could evolve as the bubble ages). Moreover, features external to the Galactic bubbles (e.g. the North Polar Spur; Kataoka et al. 2013) are not included in our model, but may make a contribution to the observed X-ray emission. We thus consider a direct comparison between the X-ray emission from our model and that observed from the Galactic Fermi bubbles/halo to be complicated by substantial thermal emission and emission from structures not associated with the bubbles. Addressing these additional contributions is non-trivial, and is not necessarily informative to predict the observational prospects of bubbles around external galaxies where thermal emission contributions could differ greatly. After the first few Myr, non-thermal bremsstrahlung X-rays are surpassed by inverse Compton emission, which dominates the X-ray emission from the bubble by 7 Myr. At these later times, a significant non-thermal bremsstrahlung component can also be seen to emerge in TeV γ-rays. This is attributed to the concentration of gas and CR energy density near the top of the bubble (cf. Section 3.3), although we note that the physical strength of this emission may not be properly resolved.20 This will be explored in more detail in future work (see also Section 4.3).

2020ApJ...901...45Z__Gopalswamy_et_al._2004_Instance_1

In this paper, we are focusing on the association of the acceleration and release of SEPs with different types of CME–CME interaction. In fact, the particle acceleration process is a complex one involving many factors, e.g., (1) the CME (or shock) speeds (Richardson et al. 2015; Papaioannou et al. 2016; Kouloumvakos et al. 2019), (2) the shock parameters, e.g., Mach numbers, compression ratios, and shock geometry (Lee 1983; Kozarev et al. 2015; Kouloumvakos et al. 2019), (3) the magnetic connectivity between the spacecraft and the source (Richardson et al. 2014; Xie et al. 2019), (4) the level of seed particles, and (5) the level of turbulence (e.g., Wanner & Wibberenz 1993; Laitinen et al. 2018; Strauss & le Roux 2019). Figure 2 shows a relationship between the CME 3D speed and the SEP Ip in NP3D group, which is consistent with the results in Kouloumvakos et al. (2019). The penultimate point has been widely discussed (e.g., Gopalswamy et al. 2004; Kahler & Vourlidas 2014; Ding et al. 2015), involving the role of the flare material and the interacting CMEs on seed particles. In Ding et al. (2015), the authors used a Fe/O ratio of 2.0 as the threshold for the presence of flare material and found that all events except one with Fe/O > 2.0 are in the “twin-CME” scenario, indicating the presence of flare seed material that are possibly from pre-flares. In Kahler & Vourlidas (2014), they proposed that higher SEP Ip could be explained by increases in both CME rates and seed particles during times of high solar activity instead of being due to CME–CME interaction. In Figure 7, the higher Ip in the cases of (nearly) interacting CMEs gives a hint that more seed particles will be accelerated if the priCME eruption is close to the preCME eruption, but it is still necessary to figure out which factor, i.e., the solar activity, the flare, or the preCME, mainly controls the level of the seed populations. The launch of the Parker Solar Probe (PSP) can contribute to this investigation in the future, because the spacecraft will reach as close as 8.86 Rs from the solar surface by 2024. During its first two perihelion passages, a series of SEP events have been studied, focusing on the acceleration mechanisms and seed population preconditioning (see McComas et al. 2019; Schwadron et al. 2020).

2016MNRAS.460.3554A__Reville_&_Bell_2014_Instance_1

We consider that the amplified hotspot magnetic field B is turbulent, and that the large-scale background field downstream of the reverse shock is Bjd, nearly perpendicular to the shock normal because the perpendicular component is compressed and enhanced by a factor of 4 to 7 (i.e. Bjd ∼ rBj). In such a case, to accelerate particles up to an energy Ec via a diffusive mechanism, the mean-free path λc ∼ rg(γc, B)2/s in the shock downstream region, where B is a small-scale field, has to be smaller than Larmor radius in Bjd (Lemoine & Pelletier 2010; Reville & Bell 2014).4 The condition λc ≲ rg(γc, Bjd) is satisfied when the magnetic-turbulence scalelength is (23) \begin{equation} s \ge \frac{E_{\rm c}}{eB}\left(\frac{B_{\rm jd}}{B}\right) = r_{\rm g}(\gamma _{\rm s},B), \end{equation} where rg(γs, B) is the Larmor radius of protons with energy (24) \begin{eqnarray} E_{\rm s} &=& E_{\rm c}\left(\frac{B_{\rm jd}}{B}\right) = 0.07 E_{\rm c}\left(\frac{r}{7}\right) \left(\frac{B_{\rm j}}{\rm \mu G}\right) \left(\frac{B}{100 \,\rm \mu G}\right)^{-1}\nonumber\\ &&\sim 10 \left(\frac{r}{7}\right) \left(\frac{\nu _{\rm c}}{10^{14}\,{\rm Hz}}\right)^{\frac{1}{2}} \left(\frac{B_{\rm jd}}{\rm \mu G}\right) \left(\frac{B}{\rm 100\,\mu G}\right)^{{-}\frac{5}{2}}\,\,{\rm GeV}, \end{eqnarray} where we take B ∼ 100 μG and Bj ∼ μG as characteristic values. Note that (25) \begin{equation} \frac{s}{\rm cm} > 5\times 10^{11}\left(\frac{r}{7}\right) \left(\frac{\nu _{\rm c}}{10^{14}\,{\rm Hz}}\right)^{\frac{1}{2}} \left(\frac{B_{\rm jd}}{\rm \mu G}\right) \left(\frac{B}{\rm 100\,\mu G}\right)^{{-}\frac{5}{2}} \end{equation} is greater than c/ωpi in equation (14), as required. Note however that this limit, s ≳ 500 c/ωpi for typical values considered in this paper, cannot be fulfilled by Weibel-generated turbulence with scale ∼c/ωpi. Therefore, the maximum energy achieved by electrons in the jet reverse shock, Ec, cannot be constrained by Weibel instabilities.

2015MNRAS.446.3631A__Brown,_Bildsten_&_Rutledge_1998_Instance_1

Note that the evolution scenario in Fig. 2 is qualitatively different from previous expectations that assumed standard viscous damping and a large saturation amplitude, see e.g. Levin (1999). There it was proposed that sources slowly spin-up at low temperatures outside of the instability region (where cooling becomes slow) followed by quick r-mode heating once the source enters the instability region and similarly fast spin-down and cooling segments which complete a cycle. There would then be no gravitational wave emission from known radio pulsars since sources would leave the instability region very quickly (Levin 1999). However, this scenario is not compatible with the well-established hypothesis that LMXBs are the progenitors of millisecond pulsars, because their observed large temperatures and frequencies (Haskell et al. 2012) place them firmly inside the instability region, as shown e.g. in fig. 1 of Alford & Schwenzer (2013). These astrophysical observations are furthermore theoretically explained by deep crustal heating due to pycnonuclear reactions (Brown, Bildsten & Rutledge 1998). For large r-mode saturation amplitudes LMXBs either could not spin-up to the high frequencies of observed radio pulsars or would be spun down very quickly, which should rule out this scenario. A modified scenario that might account for the observed spin limit of pulsars would be the presence of enhanced damping that does not increase with temperature, for instance due to a viscous boundary layer (Andersson et al. 2000) or mutual friction in a superfluid and superconducting core (Haskell, Andersson & Passamonti 2009; Haskell et al. 2012). In this case r-modes could be completely damped up to the frequencies of observed radio pulsars and it would be very unlikely that any of the known pulsars currently emits gravitational waves (Andersson et al. 2000). However, estimates on mutual friction are still rather uncertain (Haskell et al. 2009, 2012), and we have recently shown that even in the benevolent scenario of a thin viscous boundary layer the damping is very likely not sufficient to explain the fastest spinning sources (Alford & Schwenzer 2013). In Fig. 2 we show the case that crustal heating dominates r-mode heating whereby a source spins up along a vertical trajectory. If r-mode heating dominates, a source would spin-up along roughly the same trajectory along which it subsequently spins down. Another option is that the spin-up stalls since a steady state is reached where the accretion spin-up is balanced by r-mode spin-down (Wagoner 2002). However these different scenarios during the LMXB phase lead to the same qualitative evolution once the accretion ends.

2020MNRAS.492.2528L__Prieto_et_al._2017_Instance_1

Massive black holes (MBHs) are ubiquitous in the Universe, and inhabit all massive galaxies (e.g. Ferrarese & Merritt 2000). MBHs are typically observed via their accretion-powered radiation as active galactic nuclei (AGNs), whose impact on to the host galaxy is invoked to explain massive galaxy quenching (e.g. Silk & Rees 1998; Di Matteo, Springel & Hernquist 2005) and the emergence of the MBH–galaxy correlations (Gültekin et al. 2009; Kormendy & Ho 2013). However, the demographics of MBHs are not yet well constrained (see e.g. Reines & Comastri 2016; Greene, Strader & Ho 2019, for reviews) and the role of AGN feedback in dwarf galaxies is just starting to be explored (Penny et al. 2018; Mackay Dickey et al. 2019; Manzano-King, Canalizo & Sales 2019). In particular, theoretical studies have shown that the MBH–halo occupation fraction can be low in dwarf galaxies (e.g. Greene 2012; Miller et al. 2015; Habouzit, Volonteri & Dubois 2017), and even in systems hosting MBHs, their growth is strongly suppressed because of the typically low gas densities in the host (compared to more massive disc galaxies) and the strong impact of supernova explosions, both at low and high redshift (Dubois et al. 2014; Anglés-Alcázar et al. 2017; Prieto et al. 2017; Trebitsch et al. 2018). Observationally, this could be partially reflected in MBHs in dwarfs being inactive for most of their life, hence in the small number of low-luminosity AGNs found (Reines, Greene & Geha 2013; Baldassare et al. 2016, 2018, 2019; Mezcua et al. 2016, 2018; Reines et al. 2019), although there are also strong observational biases that could make these AGNs difficult to find. On the other hand, if MBHs were present in many dwarfs, and efficiently grew, their feedback could significantly affect their host (see e.g. Penny et al. 2018; Mackay Dickey et al. 2019; Manzano-King et al. 2019), could play a role in the reionization of the Universe (Volonteri & Gnedin 2009), could help removing gas from massive disc progenitors (e.g. Peirani et al. 2012), and also mitigate the ‘too-big-to-fail’ problem (Garrison-Kimmel et al. 2013). Recently, Kaviraj, Martin & Silk (2019; K19 hereafter) tried to better assess the role of AGN feedback in dwarfs by jointly analysing the Hyper-Supreme Cam Subaru Strategic Program (Aihara et al. 2018b) and the WISE (Wright et al. 2010) surveys, finding that AGNs in dwarfs could exhibit very large bolometric luminosities, hence they could play a significant role in their host evolution. However, a clear consensus on the identification of AGNs in dwarfs is still missing (see e.g. Satyapal et al. 2014; Sartori et al. 2015; Marleau et al. 2017), in particular because of the low resolution of WISE (∼6  arcsec) relative to current optical surveys, resulting in a strong source overlap, and the possible contamination of infrared emission by star formation activity that could mimic AGN activity (Hainline et al. 2016; Satyapal, Abel & Secrest 2018), especially in dwarf galaxies (Hainline et al. 2016). In this paper, we build-up on the K19 work by re-analysing their dwarf sample in more detail in the aim at better disentangling plausible AGNs in dwarf from star-forming galaxies by taking into account possible source overlapping in the sample, and also assess the MBH properties.

2022MNRAS.511.1439F__Gaensler_et_al._2002_Instance_1

As discussed before, a fraction of PSRs is bound to emerge from the progenitor SNR before our fiducial final time tend = 105yr, due to the high average kick velocity that characterizes the pulsar population. The typical escape time can be estimated by matching the PSR displacement due to its kick velocity (Vpsr) with the size of the SNR in the Sedov–Taylor phase: (14)$$\begin{eqnarray} t_{\rm esc} \simeq 725\,\, \mbox{kyr} \left[\left(\frac{E_{\rm sn}}{10^{51} \, \mbox{erg}}\right)\! \left(\frac{\rho _0}{1\, \mbox{part/cm^{3}}}\right)^{-1}\! \left(\frac{V_{\rm psr}}{100\, \mbox{km/s}}\right)^{-5} \right]^{\, 1/3}\!\!\! . \\ \end{eqnarray}$$Considering the mean (median) value of the PSR velocity distribution of 380 (330) km s−1 and of the ISM number density of 0.7 (0.25) particles cm−3, we obtain a mean (median) escape time of tesc ≃ 88 (160) kyr. Even taking into account that transition of SNRs to the radiative phase is expected at 35 (60) kyr, the escape time only slightly reduces to tesc ≃ 77 (120) kyr. Since tend = 100 kyr, only a fraction of the sources will then escape the SNR by the end of the simulation. For those systems with tesc tend, the runaway PSR will give rise to the formation of a bow shock nebula. These nebulae, whose first examples were detected in Hα (Chevalier, Kirshner & Raymond 1980; Kulkarni & Hester 1988; Cordes, Romani & Lundgren 1993; Bell et al. 1995; van Kerkwijk & Kulkarni 2001; Jones, Stappers & Gaensler 2002; Brownsberger & Romani 2014; Dolch et al. 2016; Romani, Slane & Green 2017), more recently have been discovered and observed in X-rays and sometimes in radio (Gaensler et al. 2002, 2004; Arzoumanian et al. 2004; Chatterjee et al. 2005; Yusef-Zadeh & Gaensler 2005; Hui & Becker 2007; Hui & Becker 2008; Kargaltsev & Pavlov 2008; Misanovic, Pavlov & Garmire 2008; de Rosa et al. 2009; Ng et al. 2010; De Luca et al. 2011; Ng et al. 2012; Marelli et al. 2013; Jakobsen et al. 2014; Auchettl et al. 2015; Klingler et al. 2016; Kargaltsev et al. 2017; Posselt et al. 2017; Kim et al. 2020). They are characterized by a cometary shape, with a tiny head typically of the order of 1016 cm, whose size is set by ram pressure balance between the PSR wind and the incoming (in the PSR frame) ISM, followed by a long tail opposite to the PSR motion, which can extend for very long distances up to a few pc. Given their limited spatial extension and low residual luminosity (Kargaltsev et al. 2017), bow shock nebulae will not probably be statistically relevant in γ-rays and so far have not been detected (Abdalla et al. 2018c). Runaway PSRs, however, have recently been associated to extended TeV haloes (Abeysekara 2017; Sudoh et al. 2019), most likely due to escaping pairs (Bykov et al. 2017; Evoli, Linden & Morlino 2018; Olmi & Bucciantini 2019c; Di Mauro, Manconi & Donato 2020; Evoli et al. 2021). However, the formation and properties of γ-ray haloes are still poorly understood, and different interpretations lead to very different expectations in terms of the possible detection of these sources in the next future (Sudoh et al. 2019; Giacinti et al. 2020). The modelling of these complex sources is outside the scopes of the present work, so we simply keep trace of the position of escaped PSRs for possible future implementations. The fraction of PWNe escaped from their parent SNR at the end of the simulation is represented in the right-hand panel of Fig. 1, where evolved PWNe are shown on top of the initial distribution of PWNe + SNRs.

2017MNRAS.464.1065G__Opher_et_al._2015_Instance_1

Finally in this paper, we restricted ourselves to a very limiting case when the ISM is at rest with respect to the star. This two-jet solution can, in principle, be generalized by adding the interstellar flow. Let us consider an arbitrary plane perpendicular to z-axis. This plane cuts a circle from the astropause. In the case of subsonic ISM flow, we can consider planar potential solutions around circles for each plane. According to the d'Alembert paradox, the force acting on each circle is zero. Therefore, the tube of the astropause should not be deflected into the tail, although the circle could be deformed to the ellipsoidal shape in the self-consistent solution. This scenario works, if we consider the interstellar flow to be ideal and incompressible. However, numerical results (e.g. Opher et al. 2015) show some bending of the jets towards the tail. This bending in numerical models (for slow incompressible ISM flows) is connected with the numerical dissipation inherent in the numerical schemes. Numerical viscosity may cause the boundary layer breakage on the surface of the astropause, which consequently causes the pressure asymmetry that deflects the astropause. This may be the explanation for the fact that the tube of the astropause is always deflected to the tail in the numerical models. The above-described numerical effects have nothing to do with physical dissipation phenomena responsible for the bending of real astrospheres. The physical dissipation mechanisms (e.g. magnetic reconnection, finite resistivity, Hall effects) should be explored as a possible cause of the astropause bending in the models with slow subsonic ISM flow. For the fast supersonic ISM flow, the BS is formed around the astropause. The post-shock ISM flow is vortical, and the d'Alembert paradox does not work in this case. Therefore, the bending of the astrospheric jets into the tail direction is easier to justify for the supersonic relative ISM/SW motion.

2017AandA...604A..80M__Propris_et_al._(2013)_Instance_3

Using the whole sample (\hbox{$\bar{z}=0.40$}z̅ = 0.40), we find a decreasing faint end for both datasets with consistent values between HST (α = − 0.76 ± 0.07) and Subaru (α = − 0.78 ± 0.06). Separating between low-redshift (\hbox{$\bar{z}=0.29$}z̅ = 0.29) and high-redshift (\hbox{$\bar{z}=0.51$}z̅ = 0.51) samples, we find an evolution of the faint end slope of 1.7σ with HST and 2.6σ with Subaru. There is thus a mild decrease of the faint end slope (less negative α) with increasing redshift over the range (0.187 z 0.686). This evolution is in good agreement with recent papers in the literature: in particular Zenteno et al. (2016) found a decrease of the RS faint end at 2.1σ for a wider range of redshifts (0.1 z 1.13), but with ~ 80% of their clusters being in the same redshift range as ours. De Propris et al. (2013) claim that the evolution in the faint end slope has a significant contribution from surface brightness selection effects. They used HST data of differing depths on a single cluster (MS 1358.4+6254) to show that surface brightness selection effects become important above the formal magnitude limit of their data and that they affect the RS GLF at magnitudes z ≥ 24.5 for 2.7 ks HST exposures (see their Fig. 18). The faint RS for their cluster has F814W − z = 0.25, implying that the SB selection effects in their sample become important at F814W> 24.75. On the other hand, our CLASH data are significantly deeper than theirs (4.1 ks) and we limit our GLFs at F814W 24.5. Therefore, the real SB selection effects noticed in De Propris et al. (2013) should not be playing a role in our space-based results. In addition, De Propris et al. (2013) claim that previous estimates of the evolution in the RS GLF (e.g., De Lucia et al. 2007; Rudnick et al. 2009) were also due to SB effects. Both of those works were based on the same ground-based data with a formal magnitude limit of I = 24 or 24.5 (for the low- and high-redshift clusters, respectively) and the evolution in the GLF was seen over the faintest 2 mag. We cannot directly address the role of SB effects in the EDisCS results without detailed simulations on those data (see below for such simulations for our clusters) but the similarity between our HST and Subaru GLFs imply that the EDisCS evolution in the GLF is not dominated by SB effects.

2020ApJ...904..185O__Price_et_al._2018_Instance_1

Recently, rotationally supported disks have been found not only in Class I sources but also in some Class 0 sources (e.g., Murillo et al. 2013; Yen et al. 2013, 2017; Ohashi et al. 2014; Tobin et al. 2015, 2016b, 2016a; Seifried et al. 2016; Aso et al. 2017; Lee et al. 2017; Okoda et al. 2018). In spite of these extensive studies, there is still controversy regarding when and how a disk structure is formed around a newly born protostar. Moreover, the disk formation process has been revealed to be much more complicated for binary and multiple cases, both in observations (Dutrey et al. 2014; Tokuda et al. 2014; Takakuwa et al. 2014, 2017; Tobin et al. 2016b, 2016a; Boehler et al. 2017; Artur de la Villarmois et al. 2018; Alves et al. 2019) and in numerical simulations (e.g., Bate & Bonnell 1997; Kratter et al. 2008; Fateeva et al. 2011; Shi et al. 2012; Ragusa et al. 2017; Satsuka et al. 2017; Price et al. 2018; Matsumoto et al. 2019). For instance, circumbinary/circummultiple disk structures with a spiral structure as well as a circumstellar disk for each component are reported (e.g., Tobin et al. 2016a; Takakuwa et al. 2017; Artur de la Villarmois et al. 2018; Matsumoto et al. 2019; Alves et al. 2019). In addition, it is not clear how molecules are processed during the disk formation process and what kinds of molecules are finally inherited by protoplanetary disks and potentially by planets. Understanding these processes is crucial, as they will provide important constraints on the initial physical and chemical conditions for the planetary system formation study. In this context, physical and chemical structures and their mutual relation for disk-forming regions of low-mass protostellar sources have been investigated with the Atacama Large Millimeter/submillimeter Array (ALMA; e.g., Sakai et al. 2014b, 2014a; Oya et al. 2016, 2017, 2018, 2019; Imai et al. 2016, 2019; Jacobsen et al. 2019). These studies reveal that infalling envelopes and rotationally supported disks are not smoothly connected to each other either in physical structure or in chemical composition, unlike previous expectations.

2017ApJ...838..132O___2015_Instance_1

As one of the previous studies on the atomic gas in the Perseus region, Stanimirović et al. (2014) calculated the optical depth toward 26 extra-Galactic radio continuum sources (such as quasars). They calculated as a function of velocity toward each radio source by using the method described in Heiles & Troland (2003). The calculated spectra were fitted with a sum of Gaussian functions, and the peak values and the Gaussian FWHMs (full width at half maximum) of each velocity component were derived. However, they found the optically thick gas only toward of lines of sight. We test the results in Stanimirović et al. (2014) and Fukui et al. (2014, 2015), which differ by several factors. To do this, we compare derived in Stanimirović et al. (2014) and that obtained in Section 3.5. Since our corresponds to the average value within given velocity width ( ; see Section 3.4), we compare the following two values toward each radio source located in the region we analyzed: (1) the sum of the areas of each Gaussian component of the profiles calculated in Stanimirović et al. (2014), and (2) the products of our and . The results are listed in columns 8 and 9 of Table 2. Note that 4C +30.04, 3C 092, and 3C 093.1 are located at the masked area; therefore cannot be calculated by our method toward them. Although there is a rough positive correlation between them, they differ times as a concrete numerical value. The correlation between them is plotted in Figure 16. The solid line indicates the one-to-one relationship ( ), and the dashed line is the best-fit regression line through the origin ( ). The results in Stanimirović et al. (2014) are systematically smaller than our results, and it is obvious that there is a discrepancy between these two results. This discrepancy can, however, be explained by characteristics of the data used to derive in the present study and Stanimirović et al. (2014).

2020MNRAS.491.1498C__Zhang_&_Wang_2019_Instance_1

We use the largest sample of FRB 121102, which is observed by GBT at 4–8 GHz (Zhang et al. 2018). This sample contains 21 pulses reported in Gajjar et al. (2018) and 72 pulses identified by machine learning. These pulses were observed within a 6 h observation. They share the same observation conditions and were observed by the same telescope. Therefore, we can put them together to analysis and ignore complex selection effects. Power-law distributions of energy αE = 1.63 ± 0.06 and distributions αT = 1.57 ± 0.13 for these 93 FRB 121102 bursts are shown in Fig. 5. Gourdji et al. (2019) discovered a low-energy sample with 41 bursts for FRB 121102 and found αE ∼ 1.7 if all bursts are included (see their fig. 5). However, if the low-energy bursts are discarded, a steeper αE ∼ 2.8 is found. Wang & Zhang (2019) also found that six samples of FRB 121102 bursts observed by different telescopes at different frequencies show a universal energy distribution with αE around 1.7. Meanwhile, a similar power-law index of energy distribution for non-repeating FRBs is also found (Lu & Piro 2019; Zhang & Wang 2019). The waiting time distribution of FRB 121102 can also be described by a non-stationary Poisson process with mean burst rates $\lambda _{0}=1.23^{+0.80}_{-0.38} \times 10^{-5} \,\rm ms^{-1}$. Zhang et al. (2018) found that the rate of detection is not stationary, and the distribution of waiting time cannot be well fitted using Poissonian distribution for the same sample. For a small sample of waiting times of FRB 121102, Oppermann, Yu & Pen (2018) modelled the distribution of waiting times as Weibull distribution, which can describe non-Poissonian distributions with clustering. It must be noted that the non-stationary Poissonian distribution used in this paper is similar to the Weibull distribution. Because the rate of bursts in a non-stationary Poisson process also varies with time (Wheatland et al. 1998), the mean burst rate is 1.23$^{+0.80}_{-0.38}\times 10^{-2}$ s−1. Using the same data, Zhang et al. (2018) found that the rate is 0.05 s−1 for Poissonian distribution. Using a sparse waiting time sample, Oppermann et al. (2018) derived a mean repetition rate of $5.7^{+3.0}_{-2.0}$ d−1. The large discrepancy between the two rates is that the waiting times used in this paper are derived from 93 bursts in 5 h observation, comparing to 17 bursts in about 74 h observation in Oppermann et al. (2018).

2016ApJ...832..183K__Kuiper_1941_Instance_1

The results presented here are based on the assumptions that the CBPs do not interact with the material ejected from their binary star. However, numerical studies have indicated that this material is neither lost isotropically from the binary during the CE phase, nor does it all become unbound. Instead, 1–10% of the ejecta may fall back into a CB disk according to Kashi & Soker (2011), and Passy et al. (2012) suggest that ∼80% of the ejected material may remain gravitationally bound to the binary (also see Kuiper 1941; Shu et al. 1979; and Pejcha et al. 2016 for mass loss outflows through the L2 Lagrange point24 24 Mass loss through L2 results in several possible outcomes, e.g., isotropic or equatorial wind, CB disk; for details, see Table 1 and Figures 12 and 13 of Pejcha et al. (2016). ). Either of these scenarios would significantly complicate the dynamical evolution of the system as the CBP could accrete material and gain mass and also experience migration similar to that during planetary formation.25 25 There are, however, two potential benefits of the former in terms of detection: a more luminous planet would be more amenable to direct imaging efforts, and a more massive planet would cause stronger ETVs. Such accretion of material of a different specific angular momentum will change the orbital evolution of the planet, as will gravitational interaction with the bulk gas in an accretion-favorable environment such as a CB disk. Additionally, interactions between CBPs and the CE ejecta of close binary stars (including ejection or destruction of the planets) may also play an important role in the elusive mechanisms responsible for the shaping, morphology, and chemistry of planetary nebulae (see Bear & Soker 2016 for triple star origin of asymmetric planetary nebulae; for recent reviews see Zijlstra 2014 and Jones 2015, and references therein). We note that the CE-triggered dynamical disturbances discussed here occur on timescales of ∼1 year and are thus “instantaneous” compared to any subsequent planet migration, which occurs on much longer timescales.

2020MNRAS.493.4950S__Haines_et_al._2015_Instance_2

In the framework of the hierarchical formation of structures, clusters of galaxies are continuously accreting galaxies. It has been suggested that in this process of falling, galaxies could undergo different physical processes that could affect the star formation even before they reach the cluster. Consequently, to fully understand what the cluster environment produces in galaxies, it is of key importance to have a throughout characterisation of the population of galaxies in the outskirts of clusters. Several observations have shown that properties of galaxies such as star formation, gas content, and colour are affected by the cluster environment at large clustercentric distances (e.g. Lewis et al. 2002; Solanes et al. 2002; Gómez et al. 2003; Braglia et al. 2009; Hansen et al. 2009; Park & Hwang 2009; von der Linden et al. 2010; Haines et al. 2015; Rhee et al. 2017). In particular, spiral galaxies with low star formation rates were found in the outskirts of clusters in early studies such as Couch et al. (1998) or Dressler et al. (1999). In recent years, a deficit of star-forming galaxies in the infalling region of clusters has been reported (e.g. Wetzel et al. 2013; Haines et al. 2015; Bianconi et al. 2018). This has been reproduced in simulations by Bahé et al. (2013). These results can be explained by the presence of environmental effects accelerating the consumption of the gas reservoir before galaxies enter in a cluster, a process known as pre-processing (e.g. Fujita 2004; Mihos 2004). An important fraction of the cluster galaxies has spent time in groups or filaments before they fall into the cluster (e.g. McGee et al. 2009; De Lucia et al. 2012; Wetzel et al. 2013; Hou, Parker & Harris 2014). The population of galaxies in the outskirts of clusters includes not only galaxies that have not yet entered the cluster but also backsplash galaxies, i.e. galaxies that have passed close to the centre of the cluster since their infall and are now beyond the virial radius (e.g. Mamon et al. 2004; Gill, Knebe & Gibson 2005; Mahajan, Mamon & Raychaudhury 2011). For an adequate characterisation of the properties of galaxies that are falling into clusters, it is important to take into account the contamination by backsplash galaxies, which, having orbited through the inner regions of a cluster, could have been affected by the physical processes present in that extreme environment. The backsplash scenario in the evolution of galaxies has also been explored in Rines & Diaferio (2005), Pimbblet et al. (2006), Aguerri & Sánchez-Janssen (2010), and Muriel & Coenda (2014).

2015ApJ...799..138S__Zaritsky_et_al._1994_Instance_1

We present these results with one very important caveat. Accurately determining metallicities at different redshifts is of key importance to studying the evolution of the MZR. In the local universe, relationships between strong emission line ratios and metallicity can be calibrated to “direct” electron temperature-determined metallicities from measuring auroral lines such as [O iii] λ4363 (Pettini & Pagel 2004; Pilyugin & Thuan 2005) or photoionization models of star-forming regions (Zaritsky et al. 1994; Kewley & Dopita 2002; Kobulnicky & Kewley 2004; Tremonti et al. 2004). At redshifts above z ∼ 1, it is nearly impossible to detect weak auroral lines for directly determining metallicity (but see Yuan & Kewley 2009; Rigby et al. 2011; Brammer et al. 2012a; Christensen et al. 2012; Maseda et al. 2014). Creating photoionization models that suitably represent high-redshift star-forming regions requires knowledge of physical parameters which have been poorly constrained up to this point. Thus, it is unknown if local metallicity calibrations hold at high redshifts. Figure 6 shows a comparison between metallicities determined using the O3N2 indicator and the N2 indicator for both local SDSS galaxies (grey points) and MOSDEF z ∼ 2.3 galaxies (black points). The black dashed line indicates a one-to-one relationship. If local calibrations do indeed hold at high redshifts, then the relationship between metallicities determined from different indicators should not evolve with redshift. It is clear that the z ∼ 2.3 galaxies are offset below the local galaxies. The dotted line is the best-fit line of slope unity to the individual z ∼ 2.3 galaxies, yielding an offset of −0.1 dex from a one-to-one correspondence, over twice that displayed by the SDSS sample. Steidel et al. (2014) found an offset slightly larger than this at z ∼ 2.3. This offset demonstrates that the two metallicity indicators are not evolving in the same way with redshift, and shows the need of metallicity calibrations appropriate for high-redshift galaxies.

2022AandA...658A..77N__Dudzevičiūtė_et_al._(2020)_Instance_1

Finally, we attempted to estimate the total obscured star formation within the Mpc scale environments of ELAN, which can be achieved by assuming that the excess number of submillimeter sources are all associated with the respective ELAN. To compute the SFR densities we first seek a proper conversion from S850 to SFRs. We utilized a sample of ALMA-identified SMGs in the UKIDSS-UDS field, which has been studied in detail with proper SED fittings (Dudzevičiūtė et al. 2020). Similarly to our observations, the sample of Dudzevičiūtė et al. (2020) was drawn from a flux-limited sample produced by the SCUBA-2 Cosmology Legacy Survey (Geach et al. 2017). Their results should therefore be representative, on average, of SCUBA-2 sources uncovered in other fields. These authors found a linear correlation of log10[SFR(M⊙ yr−1)] = (0.42 ± 0.06) × log10[S870(mJy)] + (2.19 ± 0.03) for their SMGs, which span a flux range of ∼1 − 10 mJy, appropriate for the SCUBA-2 sources discovered in our target ELAN fields. We then computed the total SFR densities by integrating over a given S850 range in which the SFR contribution at a given S850 is the product of the excess number density of the submillimeter sources and their corresponding SFR based on the conversion. For each field, by considering a flux range of S850 = 1 − 20 mJy and assuming a sphere with an equivalent circular radius of the corresponding effective area, we obtain SFR densities of 1100 ± 500, 1100 ± 500, 2300 ± 1100, and 1400 ± 1100 M⊙ yr−1 Mpc−3 for Fabulous, Slug, Jackpot, and MAMMOTH-1 ELAN, and a weighted average SFR density of ΣSFR = 1200 ± 300 M⊙ yr−1 Mpc−3. We plot the results in Fig. 5, showing that they are consistent with those found in the Mpc-scale environments of other quasar samples or proto-clusters at z ∼ 2 − 3 (Clements et al. 2014; Dannerbauer et al. 2014; Kato et al. 2016). This result suggests that the star formation activities around ELANe are at a similar level of other dense systems in this redshift range, or, in other words, at a factor of about 300 greater than the cosmic mean.

2015ApJ...810...96S___2010_Instance_1

Most of our knowledge about reconnection comes from effectively 2D reconnection experiments, and only recently have efforts to understand 3D magnetic reconnection been pursued (Priest 2011; Pontin 2011; Shepherd & Cassak 2012; Janvier et al. 2014), revealing a much wider range of dynamics. Very little is known about the actual properties of the solar plasma during the reconnection process on the Sun. Many authors have studied the global and local reconnection rates and timescales of solar reconnection during solar flares based on analysis of the ribbon motions in the chromosphere (Fletcher & Hudson 2001; Qiu et al. 2002, 2010; Isobe et al. 2005; Jing et al. 2005; Saba et al. 2006; Miklenic et al. 2007; Xie et al. 2009). Generally, they use measurements of the magnetic flux at the photosphere, the velocity of the ribbons parallel to the PIL, and the 2D approximation of the standard flare model to determine the reconnected flux and the electric field and Poynting flux at the reconnection site. In a future paper, we plan to test the validity of this approximation. However, these studies are purely based on the ribbon dynamics and are not able to capture the dynamics of the 3D coronal magnetic field that is actually involved in the reconnection process. For example, to calculate the energy release rate from reconnection, one needs to combine observations with knowledge of the location and size (i.e., length—the width is generally below the resolution) of the reconnection current sheet, which can only be provided by data-constrained magnetic field models and extrapolations or by data-driven MHD simulations with the appropriate NLFFF initial conditions (and is still only an approximation). Aulanier et al. (2000, 2012) and Schrijver et al. (2011) utilize idealized MHD simulations to interpret the appearance of the flare ribbons. Although such studies show a qualitative similarity of the QSLs and flare ribbons and are valuable for determining the basic topology of the region, no actual estimates of the reconnection parameters can be obtained, which could be improved by the use of data-constrained and data-driven magnetic field modeling.

2018AandA...618A..62P__Cantalupo_et_al._2010_Instance_1

The recovery of the sky signal from these huge, noisy time streams, a process called map-making, represents one of the most important steps in CMB data analysis and, if the detector noise properties and scanning strategy are known, map-making becomes a linear inverse problem. The generalized least-squares (GLS) equation provides an unbiased solution to map-making for an arbitrary choice of weights given by a symmetric and positive definite matrix (Tegmark 1997a). Moreover, if we consider the inverse covariance of the time domain noise as the weights, the GLS estimate is also a minimum variance and a maximum likelihood solution to the problem. However, computation of the solution in such a case may require either an explicit factorisation of a huge, dense matrix (Tegmark 1997a; Borrill 1999; Stompor et al. 2002) or an application of some iterative procedure (Wright 1996; Oh et al. 1999; Doré et al. 2001; de Gasperis et al. 2005; Cantalupo et al. 2010). These latte typically involve several matrix-vector multiplications at each iteration step. What makes the map-making problem particularly challenging are the sizes of the current and forthcoming CMB data sets which are directly related to the number of floating point operations (flops) needed to achieve the solution and to the memory requirements due to the sizes of the arrays required for it. Both these factors set the requirements on computational resources and indeed many current CMB data analysis pipelines opt for massively parallel computing platforms. However, even in such circumstances, efficient algorithms are necessary to ensure that the analysis can indeed be performed. The computational complexity of the algorithms involving an explicit matrix inversion is O ( N p 3 ) $ \textstyle\mathcal O(\mathbf N_\mathrm p^3) $ flops, where Np is the number of pixels in the map, and therefore they are only suitable for cases where the estimated sky maps do not involve many sky pixels. Nonetheless, whenever feasible, the direct approaches can yield high-precision, unbiased estimates of the sky signal (e.g. Poletti et al. 2017, for a recent example). The next generations of the ground experiments, CMB-Stage III (Arnold et al. 2014; Henderson et al. 2016; Benson et al. 2014) and IV (Abazajian et al. 2016), however, are expected to observe significant fractions of the entire sky with high resolution, thus resulting in maps with Np ≃ 𝒪(106), rendering the direct approaches prohibitive even for the largest forthcoming supercomputers.

2016MNRAS.461..839K__Galazutdinov,_LoCurto_&_Krelowski_2008b_Instance_1

Diffuse interstellar bands (DIBs) are absorption features seen in the spectra of many astronomical objects in the visible and infrared wavelength regions. The total number of these features exceeds 400. These bands are observed in absorption in star light crossing translucent clouds and the carriers of only three such features have been proposed; none of them certain. The origin of the DIBs is as puzzling as since their first detection, more than 90 years ago. The central wavelengths of DIBs are not readily identified with any known atomic or molecular spectral lines. The profiles of DIBs are not just Gaussians as shown for the first time by Westerlund & Krełowski (1988) which may suggest their molecular carriers. Moreover, precisely determined DIB profiles (Galazutdinov, LoCurto & Krelowski 2008b), showing a specific substructure pattern each, should facilitate their carrier's identification. The better-substantiated hypothesis is that DIBs arise from absorption produced by polycyclic aromatic hydrocarbons (PAHs), although Cox (2011) and Salama & Ehrenfreund (2014) doubt this statement and no specific PAH has been identified until recently (Salama et al. 2011). The other possibility is that carbon chain molecules, similar to those observed in star-forming regions, may carry DIBs. but this idea also has no clear proof (Motylewski et al. 2000). Two DIBs, observed in the near-infrared, were tentatively ascribed to the bucky ball (C$_{60}^{+}$) molecule (e.g. Foing & Ehrenfreund 1994; Campbell et al. 2015). Nevertheless there is an indication that this identification was proposed but not finally proven. Recently it has been demonstrated that DIB profiles (at least some of them) change in unison with the rotational temperature of simple homonuclear molecules C2 and C3 (Kaźmierczak et al. 2009). The relation between temperatures of simple carbon chains and those of DIB carriers may suggest that there is a common chemical history and that the DIB carrier may be polyatomic centrosymmetric (non-polar) molecules as well. This is likely why the earlier attempts to match the electronic spectra of known polar molecules (identified in microwave region of wavelengths) and DIBs failed (Motylewski et al. 2000). In a certain sense, this phenomenon still remains an enigma for astrophysicists. For recent reviews see Cami & Cox (2014).

2022ApJ...940...72R__Camilo_et_al._2006_Instance_1

Several studies have discussed the radio luminosity of GLEAM-X J1627 during its radio outburst in comparison with the limits of its rotational energy (Erkut 2022; Hurley-Walker et al. 2022). In particular, assuming isotropic emission, the radio luminosity of the brightest single peaks (L radio ∼ 1030–1031 erg s−1; Hurley-Walker et al. 2022) exceeds the limits on the rotational power of the source by a few orders of magnitude. Figure 6 shows those peak radio luminosities and the rotational power of GLEAM-X J1627 in comparison with other pulsars, rotating radio transients (RRATs) and radio-loud magnetars. For the radio-loud magnetars, given their large variability, we have chosen the brightest radio pulses reported in the literature (data collected from Camilo et al. 2006, 2007; Weltevrede et al. 2011; Deller et al. 2012; Lynch et al. 2015; Majid et al. 2017; Pearlman et al. 2018; Lower et al. 2020, and Esposito et al. 2021). It is well known that assuming isotropic radio emission is not realistic, and a beaming factor necessarily has to be present (see, e.g., Erkut 2022). However, the relation between the duty cycle and the spin period of canonical pulsars has a large spread (Manchester et al. 2005). Moreover, it is observed that this relationship does not apply to radio-loud magnetars, which in general show larger duty cycles than what one would expect from the extrapolation of this tentative relation for radio pulsars to magnetars (see, e.g., Camilo et al. 2006, 2007). To avoid the uncertainty of beaming models, which for magnetars are mostly unknown even theoretically, we plotted the isotropic radio luminosity for all the different pulsar classes in Figure 6. From this plot, at variance with canonical radio pulsars, we see how the brightest single peaks for radio-loud magnetars might exceed their rotational powers, in line with what is possibly observed for GLEAM-X J1627. While not resolving uncertainties related to the exact mechanism of radio emission or the beaming factor, Figure 6 shows that, under the assumption of isotropic emission, even for magnetars the brightest single peaks exceed their rotational energy budget. Considering all the uncertainties in the assumptions used to derive the radio luminosities plotted in Figure 6, GLEAM-X J1627’s radio luminosity excess over its rotational power cannot be used as an argument for or against its neutron star nature.

2021AandA...654A.132B__Esquej_et_al._(2014)_Instance_1

A third approach to assessing the central star formation is based on the presence of poly-aromatic hydrocarbons (PAHs), which are known to trace young stars, but over a wider range of ages (∼100 Myr) than the ionised line emission. However, there is a debate about whether the PAHs are excited by stars or by the AGN itself, or whether small PAHs are destroyed by the hard radiation from an AGN (Siebenmorgen et al. 2004; Smith et al. 2007; Sales et al. 2010). This may depend on which PAH feature one considers: Diamond-Stanic & Rieke (2010) found that in AGNs on kpc scales the 6.2, 7.7, and 8.6 μm features were suppressed, while the 11.3 μm feature was not. Partly for this reason, recent studies of PAHs close to AGNs have focussed on the feature at 11.3 μm. Esquej et al. (2014) detected PAHs on subarcsec scales in about half of their sample of 29 nearby Seyfert galaxies. They argued that the high column densities in the torus around the AGN would provide shielding that enables PAHs to survive, and the implied central star formation rate density was much higher than in the circum-nuclear region. A similar conclusion about PAH survival was reached by Esparza-Arredondo et al. (2018) for their sample of 19 AGNs, based on the lack of relation between the X-ray luminosity and a central PAH deficit – while PAHs were detected in most AGNs, the equivalent width was lower in the centre. They attributed this to low star formation rates in that region. On the other hand, while Jensen et al. (2017) also detected PAHs in a sample of 13 AGNs, they argued that the similarity and slope of the radial profiles from tens to hundreds of parsecs point towards an origin in a single compact source of excitation. In order to shed more light on the excitation of PAHs in this context, Alonso-Herrero et al. (2020) compared PAH line ratios in 22 AGNs to models of PAH excitation and analysed this in the context of the measured molecular gas content. They concluded that PAHs can be shielded from the hard AGN radiation.

2021MNRAS.506.1045M__Kotani_et_al._1994_Instance_1

Discovered in 1977 from its bright H α emission (Stephenson & Sanduleak 1977), SS433’s defining characteristics are undoubtedly the helical motion of highly collimated jets of plasma launched from its innermost regions, and mass-loaded, non-polar outflows (Fabian & Rees 1979; Margon et al. 1979) which together inflate the surrounding W50 supernova remnant. Knots in SS433’s jet can be resolved at radio frequencies using very long baseline interferometry (VLBI) and indicate the presence of highly relativistic electrons (Vermeulen et al. 1987), while the baryon content is revealed by emission lines ranging from H and He lines in the optical through to highly ionized Fe lines in the X-rays (Kotani et al. 1994; Marshall et al. 2013). The Doppler shifts of the lines indicate precession of the accreting system with a period of ≈ 162 d, also seen in optical (He ii) emission lines originating from the non-polar wind (Fabrika 1997). Both the jets and winds carry a large kinetic luminosity (>1038 erg s−1, e.g. Marshall et al. 2002), which requires extraction of energy via accretion on to a compact object. While the nature of the compact object in SS433 remains somewhat unknown (although dynamical arguments suggest the presence of a black hole – Blundell, Bowler & Schmidtobreick 2008), the rate of mass transfer from the companion star, as inferred from the IR excess (Shkovskii 1981; Fuchs et al. 2006), is thought to be ∼1 × 10−4 M⊙ yr−1, orders of magnitude in excess of the Eddington limit for any plausible stellar remnant (>300 times the Eddington mass accretion rate for a typical stellar mass black hole of around 10 M⊙). Classical theory and radiation magnetohydrodynamic (RMHD) simulations agree that such ‘super-critical’ rates of accretion will lead to a radiatively supported, large scale height (H/R ≈ 1, where H is the height of the disc at distance R from the compact object) accretion disc with powerful winds launched from the surface at mildly relativistic speeds (Shakura & Sunyaev 1973; Poutanen et al. 2007; Ohsuga & Mineshige. 2011; Takeuchi et al. 2013; Jiang et al. 2014; Sadowski et al. 2014).

2020MNRAS.494.5110B__Troja_et_al._2018_Instance_1

Following the short gamma-ray burst (sGRB) associated with this event, GRB 170817A (Abbott et al. 2017a,b; Goldstein et al. 2017), radio emission was anticipated as the associated merger outflow interacted with the circum-merger medium. Monitoring the radio emission could therefore provide crucial information on the energetics and geometry of the outflow, as well as the ambient environment. At radio frequencies, telescopes were observing the Advanced LIGO–Virgo probability region for GW170817 within 29 min post-merger (Callister et al. 2017a), and subsequent monitoring of AT 2017gfo resulted in an initial radio detection 16 d after the event (Abbott et al. 2017a; Hallinan et al. 2017). Further monitoring, predominantly at frequencies between 0.6 and 15 GHz, has since taken place (e.g. Alexander et al. 2017, 2018; Corsi et al. 2018; Dobie et al. 2018; Margutti et al. 2018; Mooley et al. 2018a,b,c;Resmi et al. 2018; Troja et al. 2018, 2019). At these frequencies, a general picture emerged in which the radio light curve was first observed to steadily rise, before it turned over and began a more rapid decay. Using a compilation of 0.6–10 GHz radio data from 17 to 298 d post-merger, Mooley et al. (2018c) derived both a fitted time for the radio peak of 174$^{+9}_{-6}$ d and a fitted 3-GHz peak flux density of 98$^{+8}_{-9}\, \mu$Jy (also see similar analyses in Dobie et al. 2018 and Alexander et al. 2018). The fitted radio spectral index α1 from this study is −0.53 ± 0.04, consistent with broad-band spectral indices determined using radio, optical, and X-ray data at various epochs, where the typical value is approximately −0.58 (e.g. Alexander et al. 2018; Margutti et al. 2018; Troja et al. 2018, 2019; Hajela et al. 2019). Mooley et al. (2018c) also found power-law dependencies for the rise and decay phases of approximately t0.8 and t−2.4, respectively, where t is the time since the merger. Within the associated uncertainties, these results are consistent with the broad-band evolution of AT 2017gfo (e.g. Alexander et al. 2018; Hajela et al. 2019; Lamb et al. 2019; Troja et al. 2019).

2020MNRAS.499.1788W__Malhotra_et_al._2001_Instance_1

Owing to their brightness at rest-frame FIR wavelengths, the ionized and neutral species of Carbon, Nitrogen, and Oxygen are powerful diagnostic lines for tracing the ISM of nearby and distant galaxies. When combined with photodissociation region (PDR) models (Tielens & Hollenbach 1985), measurement of the emission from different lines provide a means to constrain quantities such as the ionization rate and metallicity of the ISM of galaxies. Multilevel FIR transition lines have now been widely surveyed in local galaxies, originally by ISO (e.g. Luhman et al. 1998; Malhotra et al. 2001) and more recently using the PACS spectrometer (Poglitsch et al. 2010) on the ESA Herschel Space Observatory (Pilbratt et al. 2010). The [C ii]158 μm line is typically the brightest in star-forming galaxies, arising from ionized, and even neutral gas where it is the main coolant (Wolfire et al. 2003). Another commonly observed FIR line tracer of the ionized ISM is [N ii]122 μm. It has the advantage that it can be found associated with lower excitation gas, close to that observed in our own Galaxy (e.g. Goldsmith et al. 2015; Herrera-Camus et al. 2016). Another major coolant of the ISM is [O i]63 μm (Wolfire et al. 2003). Owing to its high excitation temperature and critical density, it can dominate the cooling in regions of starburst activity (Kaufman et al. 1999; Kaufman, Wolfire & Hollenbach 2006; Brauher, Dale & Helou 2008; Croxall et al. 2012; Narayanan & Krumholz 2017). When combined with measurements of the [C ii]158 μm line intensity and FIR luminosity, the [O i]63 μm line intensity can constrain the FUV field, G, and the gas density using PDR models. The luminosity in these FIR lines generally exhibits a deficit in the most FIR luminous galaxies compared to the trend expected from lower luminosity galaxies (e.g. Malhotra et al. 2001; Graciá-Carpio et al. 2011; Díaz-Santos et al. 2017). This has made the emission from lines like [O i]63 μm more challenging to detect at high-redshifts.

2020MNRAS.493.4960T__Young,_Ross_&_Fabian_1998_Instance_1

The albedo profile is then computed by cloudy after having specified the values of temperature T(r) and density ρ(r) for each radial patch (with r the radial distance). Results for the energy-dependent albedo profile A(Eloc) obtained for different radial patches in the cases of a = 0 (left), 0.9 (centre), and 0.998 (right) are shown in Fig. 8. As it can be clearly seen, in all the cases explored the simplifying assumption of 100 per cent albedo turns out to be a good approximation only at very high energies, i.e. Eloc ≈ 10–100 keV. Elsewhere, the albedo significantly deviates from unity (except for some values of r at lower energies), especially in the 0.1–10 keV band, which is indeed the working energy range of the forthcoming X-ray polarimeters like IXPE. Here different line features appear, more or less visible depending on the BH spin and radial distance, such as the clear iron absorption edge that occurs at around ∼6–7 keV (see e.g. Young, Ross & Fabian 1998). Plots in Fig. 9 give a more exhaustive view on how the albedo profile depends on the density of the slab in which calculations are performed. In this case the outputs are obtained for a = 0.998, three different values of the temperature, i.e. those corresponding to r = 2 (left), 5 (middle), and $10\, r_{\rm g}$ (right) according to the Novikov & Thorne (1973) temperature profile, and different values of the total hydrogen density n(H) between 1015 and 1023 cm−3. The plots show that the dependence of A(Eloc) on the density is stronger at low energies, where it exhibits an increasing behaviour by decreasing n(H). In particular, it attains values close to 0 at around 0.1 keV for particle densities in excess of 1022–1023 cm−3, especially for lower temperatures (i.e. for larger radial distances, see the right-hand panel). On the other hand, at higher energies ($\gtrsim 10$–20 keV), the albedo tends to reach the same value (≈1) in the entire range of densities explored.

2015MNRAS.454.1468K__Winckel_2003_Instance_1

Owing to their dusty circumstellar environments, a large mid-infrared (mid-IR) excess is a characteristic feature of post-AGB stars and a detection of cold circumstellar material using mid-IR photometry can be used to identify these objects. The first extensive search for these objects was initiated in the mid-80's using results from the Infrared Astronomical Satellite (Neugebauer et al. 1984) which enabled the identification of post-AGB stars in our Galaxy (Kwok 1993). The Toru$\acute{\rm n}$ catalogue (Szczerba et al. 2007) for Galactic post-AGB stars lists around 391 very likely post-AGB objects. The Galactic sample of post-AGB stars have been found to be a very diverse group of objects (Van Winckel 2003). Studies showed that the majority of the optically visible Galactic post-AGB stars could be classified based on their spectral energy distributions (SEDs) into two groups: shell-sources and disc-sources (Van Winckel 2003). The shell-sources show a double-peaked SED with the hot central star peaking at shorter wavelengths while the cold, detached, expanding dust shell peaks at longer wavelengths. This type of SED is considered to be characteristic of objects that follow the single-star evolution scenario mentioned above. The disc-sources do not show two distinct flux peaks in the mid-IR but they do display a clear near-infrared (near-IR) excess indicating that circumstellar dust must be close to the central star, near sublimation temperature. It is now well established that this feature in the SED indicates the presence of a stable compact circumbinary disc, and therefore these sources are referred to as disc-sources (de Ruyter et al. 2006; Deroo et al. 2007; Gielen et al. 2011a; Hillen et al. 2013). The rotation of the disc was resolved with the ALMA array (Bujarrabal et al. 2013a) in one object and using single dish observations Bujarrabal et al. (2013b) confirmed that disc rotation is indeed widespread. Moreover, these disc-sources are confirmed to be binaries and show orbital periods between 100 and 2000 d (Van Winckel et al. 2009; Gorlova et al. 2014). In contrast, for the Galactic shell-sources long-term radial velocity monitoring efforts have not yet resulted in any clear detected binary orbit (Hrivnak et al. 2011), which either confirms the single-star nature of these objects or introduces a possibility that these systems can have companions on very wide orbits.

2020MNRAS.499.3792B__Pimbblet_2011_Instance_2

For consistency, we adopt the translation of this to the absolute velocities of cluster galaxies normalized by their respective galaxy cluster velocity dispersions into the range $0.3 \lt |\Delta \mathrm{V}|/\sigma _{r_{200}} \lt 0.5$ as deduced by Pimbblet (2011). Thus, if the mode of the standardised velocities for a sub-population has its foci at around $0.3 \lt |\Delta \mathrm{V}|/\sigma _{r_{200}} \lt 0.5$ for values around the virial radius, which we assume to be Rvirial ∼ r200, said sub-population would be classified as infalling. In contrast, a sub-population of backsplash cluster galaxies would be expected to peak significantly at $|\Delta \mathrm{V}|/\sigma _{r_{200}}\sim 0$ for values at or beyond our definition of the virial radius, with their fraction reaching zero at some upper limit (e.g. Mamon et al. 2004; Pimbblet 2011; Bahé et al. 2013; Haggar et al. 2020). Therefore, with respect to Fig. 5, we see that the column of our non-merging sub-populations across both bins of radius do not show any significant difference in the distributions of velocities with the exception of those that lie ≤r200, which show the non-AGN sub-population to occupy a mode within the range that nominally represents infallers, most likely for cluster galaxies 0.5 ≤ r200 1.0 (Gill et al. 2005). Additionally, the AGN sub-population slightly deviates from the non-AGN velocity distribution with a mode centred at $|\Delta \mathrm{\it V}|/\sigma _{r_{200}}\sim 0.8$, which could indicate stronger infalling. In contrast, the column of our merging AGN sub-populations shows the strongest deviations from the distribution of non-AGN, especially with the >r200 bin showing a significant centrally dominated AGN sub-population, where such a central dominance in relative velocity corresponds to a sub-population that were predominantly backsplash cluster galaxies. However, the dependence of this being the true nature of the sub-population relies upon more precise definitions of the radii since there is a natural upper limit a bound cluster galaxy can extend outward to with respect to its galaxy cluster’s potential, known as the splashback radius (More et al. 2015, 2016). In addition, Haggar et al. (2020) show that the fraction of backsplash galaxies diminishes by 2r200 and 2.5r200 for massive (∼×1015M⊙) merging and non-merging cluster systems, respectively, thus demonstrating that merging cluster environments experience a greater decrease in the fraction of harbouring backsplash galaxies as one continues to extend beyond r200. Indeed, the sub-populations of the merging cluster galaxies present in the ≤r200 bin show more variations in their general distributions with the modes of both the AGN and non-AGN sub-populations lying around $0.3 \lt |\Delta \mathrm{V}|/\sigma _{r_{200}} \lt 0.5$, which eludes to mostly infalling sub-populations rather than those associated with backsplash. Finally, if one considers the equivalent peak of the AGN density histogram at $\Delta \mathrm{V}|/\sigma _{r_{200}}\sim 1.7$ it could be possible there is a mix of recently accreted cluster galaxies and those that are relaxing on to a common potential. Although it should be noted that not much information can be confidently derived from the AGN sub-populations within the bins that possess small samples size (N ≲ 100), especially with the merging AGN-hosting cluster galaxies at ≤r200 that only has N = 15.

2022ApJ...935..137K__Whittet_et_al._2001_Instance_1

In Figure 2, the reduced AKARI IRC spectra of all protostars are presented; the absorption features of the H2O, CO2, and CO ices are clearly detected. All of our targets show deep and broad absorption features of H2O ice in the wavelength range 2.7–3.4 μm. In the case of AFGL 7009S, strong extinction toward the source saturates the absorption features throughout the wavelengths from 2.7 to 3.6 μm, including H2O ice. Other ice features, such as CH4 (Lacy et al. 1991; Boogert et al. 2004) and CH3OH (Grim et al. 1991; Brooke et al. 1996), were observed at 3.3−3.5 μm, but it is difficult to extract their absorption profiles from the blended features due to the low spectral resolution of AKARI IRC. An absorption feature of the CO2 ice around 4.27 μm was clearly detected toward all targets. At the wavelength around 4.6 μm for Perseus 1 and 3, RNO 91, and AFGL 7009S, there is a hint for another ice component overlapping with the CO absorption feature at 4.67 μm. Many near-infrared observations have revealed the same feature on the blue wing part of the CO absorption feature (Tegler et al. 1995; Chiar et al. 1998; Whittet et al. 2001; van Broekhuizen et al. 2005; Aikawa et al. 2012), which was suggested as an absorption feature of XCN ice. Lacy et al. (1984) and Pendleton et al. (1999) reported that the 4.62 μm absorption feature of XCN ice consists of a nitrile group and an unknown component “X”. Many laboratory studies have suggested that UV photolysis or cosmic ray irradiation of ice mantle could make the solid state OCN− on grain surfaces (Lacy et al. 1984; Grim & Greenberg 1987; Bernstein et al. 2000; Palumbo et al. 2000; Hudson et al. 2001; van Broekhuizen et al. 2004). In addition to these ice components, there are some absorption features around 4.8 and 4.9 μm. For Perseus 3 and the background star, the absorption features with a peak position around 4.78 μm are likely associated with 13CO ice (Boogert et al. 2002; Pontoppidan et al. 2003). We also detected another absorption feature at 4.83 μm toward the low-luminosity targets. However, we could not find any corresponding ice features from previous studies. The 4.9 μm absorption feature detected toward all targets was identified as solid carbonyl sulfide (OCS) ice. OCS ice can be produced when the interstellar ices containing CO and CO2 are exposed to UV photons or cosmic rays (Palumbo et al. 1997).

2015AandA...582A..26G__model,_Young_(2014)_Instance_1

In addition, if 26Al in the solar system was inherited from a molecular cloud, one would expect the solar system to have a (60Fe/26Al)0 ratio identical to that of the ISM. If the collapse timescales – depending on the amount of turbulence, the intensity of magnetic fields, and other complex parameters (McKee & Ostriker 2007) – exceed a few 26Al half lives, the solar system’s initial (60Fe/26Al)0 ratio is even expected to be higher than that of ISM because 26Al decays much faster than 60Fe. Both radionuclides have now been identified in the ISM via γ-ray astronomy (Diehl 2014). The measured ISM flux ratio 60Fe/26Al ratio is 0.15 (Wang et al. 2007), which translates into a mass ratio of 0.35. The ISM 60Fe/26Al mass ratio is therefore two orders of magnitude higher than the solar value of 3.9 × 10-3 (see Sect. 1), ruling out that both radionuclides were inherited from the ISM. Despite the observational evidence, and to keep alive the inherited model, Young (2014) proposed to decrease the theoretical 60Fe abundance in molecular clouds by assuming that stars more massive than 30 M⊙ do not explode as SNe. These stars would not contribute to the 60Fe inventory, bringing the theoretical ISM 60Fe/26Al ratio closer to that of the solar system. Because stars more massive than 30 M⊙ contribute to less than 50% of the 60Fe production2, this proposition cannot resolve the two orders of magnitude discrepancy between the model and observations. Furthermore, the recent discovery of a supernova whose progenitor mass was far above the threshold of 30 M⊙ is at odds with that solution (Gal-Yam et al. 2014). Finally, if 26Al was inherited from the natal molecular cloud, it would be homogeneously distributed in the SPD, which is contrary to observations (Krot et al. 2012). As discussed by Gounelle & Meynet (2012), some heterogeneity in the 26Al distribution is expected in the dense shell model because the shell collapse timescale (a few 105 yr) is comparable to the 26Al half life.

2018ApJ...867...90N__Hobbs_et_al._2006_Instance_1

We constructed the gamma-ray folded light curve of 3FGL J2039.6–5618 using the orbital period from J. Strader et al. (2018, in preparation) and the two best periods in our searches using the full data and the data before MJD 57,040. The phase zero is defined to be the epoch of the optical maximum (T0 = 57,603.95787 in MJD). In order to maximize the signal-to-noise ratio, we use the method of photon weighting (Kerr 2011) instead of an aperture selection to produce the folded light curve. The probability that the photon is emitted by 3FGL J2039.6–5618 is assigned to each of the photons using gtsrcprob in the Science Tools. The orbital phase is calculated using the TEMPO2 package (Hobbs et al. 2006) with the Fermi pulg-in (Ray et al. 2011). In the timing model, we adopted the main-sequence/pulsar binary model (MSS; Wex 1998). Using the photon probabilities as the weights, the resulting weighted light curves are shown in Figure 4. From top to bottom, the orbital periods used in folding the light curves are PStrader = 0.22798177 days, Pfull = 0.2279757 days, and Pbefore = 0.2279808 days, respectively. Two orbital periods are shown for clarity. The light curve indicates that the modulation is a single peak. The FWHM of the peak spans from about ϕ = 0.25 to ϕ = 0.7, which occupies almost half of the orbital period. Although the best period found from the Rayleigh test has different values with different time spans, the folded light curves in Figure 4 generally show similar signal structures. As we speculate that the gamma-ray modulation disappears after MJD 57,040, it is not reliable to use the best period Pfull obtained from the full data set, which includes the no-signal duration. On the other hand, the best period Pbefore is obtained from the data only containing the portion before MJD 57,040; therefore, it may be biased to be applied to the study of the full data set. Therefore, with a negligible difference in the light curves and modulation significances ( vs. for data before MJD 57,040), we adhere to the orbital period PB = PStrader = 0.2279817(7) days, which is reported from the independent optical observation by J. Strader et al. (2018, in preparation), for the rest of this study. Figure 5 shows the energy-dependent orbital light curves of 3FGL J2039.6–5618 in the energy ranges of 0.1–500 GeV (top), 0.1–3 GeV (middle), and 3–500 GeV (bottom). It is clear that the orbital modulation is mostly contributed by the lower part of the energy.

2018AandA...611A..74R__Grady_et_al._2013_Instance_2

In this context, MWC 758 (HD 36112) offers a unique environment to probe the existence of planetary companions and to explore the connection between disk structures and planet formation. MWC 758 is a young stellar object (3.5 ± 2 Myr, Meeus et al. 2012) at a distance of 151 $^{+9}_{-8}$ 151 −9 +8 4 pc (Gaia Collaboration 2016) close to the edge of the Taurus star forming region (stellar properties are given in Table 1). Measurements of resolved CO emission around the star determined the stellar mass to be 2.0 ± 0.2 M⊙ and the disk to have an inclination of 21° ± 2° and a position angle of the semi-major axis of 65° ± 7° (Isella et al. 2010). The mass and age estimates were based on the previously adopted hipparcos distances of 200 pc (van den Ancker et al. 1998) and 279 pc (van Leeuwen 2007). Given the revised Gaia distance, the star could be older and lighter than previously thought. In this paper, we assume a stellar mass of 1.5 ±0.2 M⊙, reflecting the scaling of the dynamical mass estimate to the new Gaia distance. Based on its SED, MWC 758 has been classified as a pre-transition disk (Grady et al. 2013). Although a cavity of 55 astronomical units (au) in radius has been inferred from dust millimeter emission (Andrews et al. 2011), infrared polarized intensity observations have found no clear evidence for a cavity in scattered light (Grady et al. 2013; Benisty et al. 2015). Using Ks-band (2.15 μm) direct imaging andH-band (1.65 μm) polarimetric imaging with the High-Contrast Instrument with Adaptive Optics (HiCIAO) at the Subaru Telescope, Grady et al. (2013) detected two spiral arms and polarized light down to 0.′′ 1 (15 au) from the star. Recent VLT Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) observations in the Y band (1.04 μm) have confirmed the presence of scattered light at least down to 14 au (Benisty et al. 2015). The asymmetries observed by Isella et al. (2010) in the mm-dust distribution and in CO emission suggest that the disk may be gravitationally perturbed by a low-mass companion orbiting within a radius of 23 au (assuming a distance of 151 pc). The asymmetric cm-dust distribution was shown to follow the location of the mm-dust (Marino et al. 2015a), hinting towards the hypothesis of a dust trap, which could also be created by a companion in the gap through the Rossby wave instability (e.g., Pinilla et al. 2012b). Hydrodynamical simulations of the disk indicate that the observed spirals could instead be launched by a massive planet or brown dwarf at larger separations (~ 100 au based on the revised Gaia distance, Dong et al. 2015b). The presence of stellar companions down to a mass limit of 12 MJup at 0.′′ 25 and of planets outside 0.′′5 (5 MJup at 0.′′ 5, and 3 MJup at 1′′ , according to the BT-SETTL models; Allard et al. 2012) has been ruled out based on a combination of sparse aperture masking observations at L′ band and angular differential imaging at K′ and Ks bands (Grady et al. 2013).

2021AandA...653A..36M__Goulding_&_Alexander_(2009)_Instance_5

The SFG sample was constructed using the Great Observatories All-Sky LIRG Survey (GOALS sample, Armus et al. 2009), from which we extracted 158 galaxies, with data from Inami et al. (2013), who report the fine-structure lines at high resolution in the 10 − 36 μm interval, and Stierwalt et al. (2014), who include the detections of the H2 molecular lines and the PAH features at low spectral resolution. For those galaxies in the GOALS sample that have a single IRAS counterpart, but more than one source detected in the emission lines, we have added together the line or feature fluxes of all components, to consistently associate the correct line or feature emission to the total IR luminosity computed from the IRAS fluxes. To also cover lower luminosity galaxies, as the GOALS sample only includes luminous IR galaxies (LIRGs) and ultra-luminous IR galaxies (ULIRGs), we included 38 galaxies from Bernard-Salas et al. (2009) and Goulding & Alexander (2009), to reach the total sample of 196 galaxies with IR line fluxes in the 5.5 − 35 μm interval in which an AGN component is not detected. For the Bernard-Salas et al. (2009), Goulding & Alexander (2009), and the GOALS samples, we excluded all the composite starburst-AGN objects identified as those with a detection of [NeV] either at 14.3 or 24.3 μm. It is worth noting that the original samples from Goulding & Alexander (2009) and Bernard-Salas et al. (2009) have spectra solely covering the central region of the galaxies. To estimate the global SFR, we corrected the published line fluxes of the Spitzer spectra by multiplying them by the ratio of the continuum reported in the IRAS point source catalogue to the continuum measured on the Spitzer spectra extracted from the CASSIS database (Lebouteiller et al. 2015). We assumed here that the line emission scales (at first order) with the IR brightness distribution. In particular, we considered the continuum at 12 μm for the [NeII]12.8 μm and [NeIII]15.6 μm lines, and the continuum at 25 μm for the [OIV]25.9 μm, [FeII]26 μm, [SIII]33.5 μm, and [SiII]34.8 μm lines. This correction was not needed for the AGN sample and the GOALS sample because of the greater average redshift of the galaxies in the 12MGS and GOALS samples. In particular, the 12MGS active galaxy sample has a mean redshift of 0.028 (Rush et al. 1993), while the GOALS sample has a mean redshift of 0.026. The galaxies presented by Bernard-Salas et al. (2009) have instead an average redshift of 0.0074, while the sample by Goulding & Alexander (2009) has an average redshift of 0.0044. For the other lines in the 10 − 36 μm interval, Goulding & Alexander (2009) did not report a detection, and we used the data presented in Bernard-Salas et al. (2009) for a total of 15 objects. Both Bernard-Salas et al. (2009) and Goulding & Alexander (2009) reported data from the high-resolution Spitzer-IRS spectra. Data in the 50 − 205 μm interval were taken from Díaz-Santos et al. (2017). For the GOALS sample, 20 starburst galaxies were taken from Fernández-Ontiveros et al. (2016), and 23 objects were taken from the ISO-LWS observations of Negishi et al. (2001). As a result, we obtained a total sample of 193 objects. Lastly, the PAH features’ fluxes were measured from the low-resolution Spitzer-IRS spectra by Brandl et al. (2006), including 12 objects from the sample of Bernard-Salas et al. (2009) and 179 objects from Stierwalt et al. (2014).

2022ApJ...924...56S__Madau_&_Fragos_2017_Instance_1

The formation and evolution of black holes (BHs) in the universe is one of the major issues to be addressed by the modern research in astrophysics and cosmology. In the mass range m • ∼ 5–150 M ⊙, BHs are originated from the final, often dramatic stages in the evolution of massive stars (possibly hosted in binary systems). These compact remnants can produce luminous X-ray binaries (e.g., Mapelli et al. 2010; Farr et al. 2011; Inoue et al. 2016), can constitute powerful sources of gravitational waves for ground-based detectors like the current LIGO/Virgo facility (e.g., Belczynski et al. 2010; Dominik et al. 2015; Spera & Mapelli 2017; Boco et al. 2019; Spera et al. 2019; Abbott et al. 2021a, 2021b), can possibly energize short gamma-ray bursts and associated kilonovas (e.g., Abbott et al. 2020, 2021c; Ackley et al. 2020; Gompertz et al. 2020), can inject strong energy inputs in the primeval universe (e.g., Mirabel et al. 2011; Justham & Schawinski 2012; Artale et al. 2015; Madau & Fragos 2017; Lehmer et al. 2021), and can provide light seeds for the subsequent growth of more massive BHs (e.g., Madau et al. 2014; Volonteri et al. 2015; Lupi et al. 2016; Pacucci et al. 2017; Boco et al. 2020; Das et al. 2021). At the other end, in the range M • ∼ 106–1010 M ⊙, supermassive BHs grow mainly by gaseous accretion that energizes the spectacular broadband emission of active galactic nuclei (AGNs). Such an activity can have a profound impact on galaxy evolution (e.g., Alexander & Hickox 2012; Lapi et al. 2014, 2018), as testified by the strict relationships between the relic BH masses and the physical properties of the hosts (e.g., Kormendy & Ho 2013; Shankar et al. 2016, 2020; Zhu et al. 2021). The intermediate-mass range m • ∼ 103–106 M ⊙ is the most uncertain. So far, only tentative evidence of these systems has been identified (see Paynter et al. 2021). However, the chase is open in view of their astrophysical relevance. Most noticeably, they can provide heavy seeds for quick (super)massive BHs growth (e.g., Mayer & Bonoli 2019; Boco et al. 2020), as it seems required by the puzzling observations of an increasing numbers of giant monsters M • ≳ 109 M ⊙ when the age of the universe was shorter than ≲0.8 Gyr (e.g., Mortlock et al. 2011; Venemans et al. 2017; Banados et al. 2018). Moreover, such intermediate-mass BHs will constitute important targets for space-based gravitational wave detectors like LISA and DECIGO (see eLisa Consortium 2013; Kawamura et al. 2021; also Barausse & Lapi 2021; Boco et al. 2021b).

2018AandA...619A..13V__Saviane_et_al._2012_Instance_2

The EWs were measured with the methods described in Vásquez et al. (2015). As in Paper I, we used the sum of the EWs of the two strongest CaT lines (λ8542, λ8662) as a metallicity estimator, following the Ca II triplet method of Armandroff & Da Costa (1991). Different functions have been tested in the literature to measure the EWs of the CaT lines, depending on the metallicity regime. For metal-poor stars ([Fe/H] ≲ −0.7 dex) a Gaussian function was used with excellent results (Armandroff & Da Costa 1991), while a more general function (such as a Moffat function or the sum of a Gaussian and Lorentzian, G + L) is needed to fit the strong wings of the CaT lines observed in metal-rich stars (Rutledge et al. 1997; Cole et al. 2004). Following our previous work (Gullieuszik et al. 2009; Saviane et al. 2012) we have adopted here a G+L profile fit. To measure the EWs, each spectrum was normalised with a low-order polynomial using the IRAF continuum task, and set to the rest frame by correcting for the observed radial velocity. The two strongest CaT lines were fitted by a G+L profile using a non-linear least squares fitting routine part of the R programming language. Five clusters from the sample of Saviane et al. (2012) covering a wide metallicity range were re-reduced and analysed with our code to ensure that our EWs measurements are on the same scale as the template clusters used to define the metallicity calibration. Figure 5 shows the comparison between our EWs measurements and the line strengths measured by Saviane et al. (2012) (in both cases the sum of the two strongest lines) for the five calibration clusters. The observed scatter is consistent with the internal errors of the EW measurements, computed as in Vásquez et al. (2015). The measurements show a small deviation from the unity relation, which is more evident at low metallicity. A linear fit to this trend gives the relation: ΣEW(S12) = 0.97 ΣEW(this work) + 0.21, with an rms about the fit of 0.13 Å. This fit is shown in Fig. 5 as a dashed black line. For internal consistency, all EWs in this work have been adjusted to the measurement scale of Saviane et al. (2012) by using this relation. In Table 3 we provide the coordinates, radial velocities, and the sum of the equivalent widths for the cluster member stars, both measured (“m”) and corrected (“c”) to the system of Saviane et al. 2012.

2015ApJ...815....7V__Davila_1987_Instance_1

There are also simplified problems, less complex than fully developed turbulence, in which one finds the formation of small scales in the direction perpendicular to an applied magnetic field It is well known that this effect appears in the context of MHD when imposed parallel-propagating waves interact with an inhomogeneous background consisting either of pressure-balanced structures or velocity shears (Ghosh et al. 1998). Phase mixing of torsional Alfvén waves in axisymmetric-equilibrium magnetic configurations have been studied in Ruderman et al. (1999), where possible applications to the solar corona and solar wind have been proposed. In two-dimensional (2D) equilibria, where the Alfvén velocity varies in directions perpendicular to the magnetic field, two mechanisms have been investigated in detail: (1) phase mixing (Heyvaerts & Priest 1983), in which differences in group velocity at different locations progressively bend wave fronts, and (2) resonant absorption, which concentrates the wave energy in a narrow layer where the wave frequency locally matches a characteristic frequency (Alfvén or cusp). These processes have been studied both by investigating normal modes of the inhomogeneous structure (Kappraff & Tataronis 1977; Mok & Einaudi 1985; Steinolfson 1985; Davila 1987; Hollweg 1987; Califano et al. 1990, 1992) and by considering the evolution of an initial disturbance (Lee & Roberts 1986; Malara et al. 1992, 1996). Effects of density stratification and magnetic line divergence (Ruderman et al. 1998), nonlinear coupling with compressive modes (Nakariakov et al. 1997, 1998), and evolution of localized pulses (Tsiklauri & Nakariakov 2002; Tsiklauri et al. 2003) have been considered. The propagation of MHD waves in inhomogeneous magnetic fields containing null points has also been studied in detail (Landi et al. 2005; see also McLaughlin et al. 2010 for a review). Phase mixing in 3D inhomogeneous equilibria has also been considered in the small-wavelength limit (Similon & Sudan 1989) using a WKB approximation (Petkaki et al. 1998; Malara et al. 2000), also within the problem of coronal heating (Malara et al. 2003, 2005, 2007). Particle acceleration in phase mixing of Alfvén waves in a dispersive regime has been studied by Tsiklauri et al. (2005) using particle-in-cell simulations, both in 2D (Tsiklauri 2011) and in 3D (Tsiklauri 2012) configurations. Finally, instabilities generating KAWs in a plasma with transverse density modulations have been considered by Wu & Chen (2013). Similar ideas involving dissipative mechanisms related to the interaction of Alfvén waves or KAWs and phase mixing have been examined in the context of the magnetospheric plasma sheet (Lysak & Song 2011) and in coronal loops (Ofman & Aschwanden 2002).

2018MNRAS.480.1174H__Jehin_et_al._2009_Instance_1

The origin of nitrogen in the Solar system is still an open question. More specifically, the main repository of nitrogen in the protosolar nebula (PSN) is still unclear, although there is some consensus that it may be atomic, N, or molecular, ${\rm N_2}$ (Schwarz & Bergin 2014). Furthermore, the large variations of the isotopic ratio of nitrogen (${\rm ^{14}N}/{\rm ^{15}N}$), as measured in various carriers within different types of Solar system objects, remain unexplained (Aléon 2010; Hily-Blant et al. 2013a, 2017; Füri & Marty 2015). One striking problem is the ${\rm ^{14}N}/{\rm ^{15}N}$ isotopic ratio of nitrogen in comets. Its average value, 144 ± 3 (Jehin et al. 2009; Bockelée-Morvan et al. 2015; Shinnaka et al. 2016; Hily-Blant et al. 2017), is three times lower than the bulk ratio of 441 ± 6 in the protosun as inferred from solar wind measurements (Marty et al. 2011). The reasons for these different ratios remain elusive, casting doubts on our understanding of the origin of the composition of comets and more generally of the origin of nitrogen in the Solar system. Several possibilities (not mutually exclusive) could explain the discrepancy: (i) the tracers of nitrogen observed so far in comets – HCN, CN, and ${\rm NH_2}$ – are minor reservoirs of cometary nitrogen and thus naturally do not reflect the bulk ratio in the PSN, (ii) efficient fractionation processes in the PSN at the time of comet formation, (iii) efficient fractionation processes in the parent interstellar cloud, and (iv) exchange processes within cometary ices since their formation. Recently, it was shown that protoplanetary discs – or equivalently PSN analogues – carry at least two isotopic reservoirs of nitrogen, traced, respectively, by CN and HCN, with HCN probing a secondary, fractionated, reservoir (Hily-Blant et al. 2017). Furthermore, the isotopic reservoirs traced by HCN and CN are found to be in a 1:3 ratio, respectively, reminiscent of the factor of 3 between the cometary and bulk isotopic ratios (144:441) in the PSN. It follows that exchange processes in parent bodies [possibily (iv) above] are not necessary. The PSN hypothesis is supported by models of selective photodissociation of ${\rm N_2}$ in protoplanetary discs (Heays et al. 2014) that predict a strong enrichment of HCN in ${\rm ^{15}N}$, but also of CN, in contrast with observations (Hily-Blant et al. 2017). At present, clear-cut observational evidences supporting the PSN or interstellar hypothesis are still lacking.

2019AandA...630A..37S__Behar_et_al._2017_Instance_3

Solar wind velocity distribution moments are described in Behar et al. (2017). The ion density nsw is the moment of order 0, and the ion bulk velocity usw (a vector) appears in the moment of order 1, the flux density $n_{\mathrm{sw}} \ \underline{\mathbf{u}_{\mathrm{sw}}}$ n sw   u sw _ . The bulk speed can be defined as the norm of the bulk velocity, that is, $u_{\mathrm{sw}} = |\underline{\vec{u}_{\mathrm{sw}}}$ u sw =| u sw _ |. However, this bulk speed is representative of single-particle speeds as long as the velocity distribution function is compact (e.g., a Maxwellian distribution). Complex velocity distribution functions were observed by RPC-ICA within the atmosphere of 67P. For instance, partial ring distributions were frequently observed for solar wind protons at intermediate heliocentric distances, when the spacecraft approached the SWIC (Behar et al. 2017). To illustrate the effect of such distorted distributions, a perfect ring (or shell) distribution centered on the origin of the plasma reference frame can be imagined, in which all particles have the same speed of 400 km s−1. The norm of the bulk velocity in this case would be 0 km s−1, whereas the mean speed of the particles is 400 km s−1, which is the relevant speed for SWCX processes. This mean speed, noted Usw, of the particles is calculated by first summing the differential number flux over all angles, and then taking the statistical average (Behar 2018). Over the entire mission, the deceleration of the solar wind using the mean speed of the particles is much more limited than the deceleration shown by the norm of the bulk velocity (Behar et al. 2017): there is more kinetic energy in the solar wind than the bulk velocity vector would let us think. This is the main difference with the paradigm used at previously studied (and more active) comets (Behar et al. 2018b). These complex, nonthermal velocity distribution functions also prevent us from reducing the second-order moment (the stress tensor) to a single scalar value, which, for a Maxwellian distribution, could be identified with a plasma temperature. In the context of 67P and for an important part of the cometary orbit around the Sun, the temperature of the solar wind proton has no formal definition.

2015ApJ...814...84D__Ellison_et_al._2008_Instance_1

We first need to discuss that the environmental dependence of the metallicity of star-forming galaxies may depend on the scale at which the environment is defined. At small scales (a few tens of kpc), there is substantial evidence from observations and simulations for a decrement of metallicity and an enhancement of star-formation activity in galaxy close pairs, merging, and interacting systems compared to isolated, field galaxies, mostly attributed to the interaction-induced inflow of metal-poor gas from the periphery of interacting galaxies to the center, diluting their metal content, and increasing their gas fuel for star-formation (Mihos & Hernquist 1996; Kewley et al. 2006; Ellison et al. 2008, 2013; Michel-Dansac et al. 2008; Rupke et al. 2010; Sol Alonso et al. 2010; Perez et al. 2011; Scudder et al. 2012b; Ly et al. 2014). At intermediate group scales where galaxy interactions are more common compared to cluster and field environments (Perez et al. 2009; Tonnesen & Cen 2012)—owing to a combination of (1) a lower velocity dispersion of group galaxies relative to their cluster counterparts and (2) a higher number density of group galaxies compared to the field systems, which provide an ideal condition for interactions)—there is also evidence for a deficit of metals in group galaxies compared to control samples in the field (Lara-López et al. 2013b), possibly owing to a higher fraction of interacting galaxies. At larger filamentary and cluster scales, the slight metal enhancement of galaxies relative to the field might be due to (1) the inflow of already-enriched interafilamentary or interacluster gas into galaxies, as observations and simulations have shown a more metal-enriched intergalactic medium in cluster and filament environments compared to the field (Arnaud et al. 1994; Aracil et al. 2006; Stocke et al. 2006, 2007; Sato et al. 2007; Cen & Chisari 2011; Davé et al. 2011; Oppenheimer et al. 2012); (2) the environmental strangulation (Larson et al. 1980; Peng et al. 2015) of low-metallicity diluting gas falling from the surrounding LSS cosmic web into galaxies; (3) the environmental ram pressure stripping (Gunn & Gott 1972; Abadi et al. 1999) of the metal-poor diluting gas in the periphery of galaxies; and (4) trapping and recycling of metal-enriched outflows due to the hotter environment of filaments and clusters (Aracil et al. 2006; Cen & Ostriker 2006; Werner et al. 2008) compared to the field.

2021AandA...654A..88W__Cai_et_al._2017_Instance_1

This paper focuses on the population of high-redshift radio galaxies (HzRGs; L500 MHz > 1026 W Hz−1Miley & De Breuck 2008), which are some of the most massive galaxies known at any redshift (with a narrow range in stellar masses of (1 − 6)×1011 M⊙ for 1  z  5.2; De Breuck et al. 2010). Their energetic radio jets are unique markers of concomitant powerful AGN activity, which place them amongst the most active sources at and near cosmic noon. High-redshift radio galaxies have furthermore been shown to be powerful beacons of dense (proto-)cluster environments in the early Universe (e.g., Le Fevre et al. 1996; Stern et al. 2003; Venemans et al. 2002, 2003, 2004, 2005, 2007; Wylezalek et al. 2013). The quasar-level AGN activity (Miley & De Breuck 2008) at the center is blocked by the thick dusty torus acting as the “coronograph” (Vernet et al. 2001); this makes HzRGs true obscured type-2 quasars, allowing us to probe their host galaxies and CGM without strong AGN contamination (e.g., for unobscured quasars, see Arrigoni Battaia et al. 2019, and for radio-quite type-2 sources, see Cai et al. 2017). Comprehensive studies using near-infrared integral field unit (IFU) instruments show that the ionized gas in HzRGs is highly perturbed (FWHM ∼ 1000 km s−1) at kiloparsec scales and is aligned with the radio jets (Nesvadba et al. 2006, 2007, 2008, 2017a,b; Collet et al. 2015, 2016). This implies that the energy and momentum transfer between the central quasar and their ISM is likely due to the jets. Radio-mode feedback may therefore play a fundamental role during the evolution of HzRGs. Recently, Falkendal et al. (2019) combined infrared and millimeter data and deduced a more robust result of a relatively low star formation rate (SFR) for a sample of HzRGs, suggesting evidence of rapid quenching compared to previous studies (e.g., Drouart et al. 2014). Using a small sample of HzRGs, Nesvadba et al. (2011) shows that they are going through a transition phase from active to passive. These observations indicate that HzRGs are on a different track of evolution compared to radio-quiet objects, assembling most of their stellar mass early (z ∼ 3; Seymour et al. 2007; De Breuck et al. 2010), and that radio jets may actively affect their quenching. However, there is also circumstantial evidence showing that the jet can induce star formation. Humphrey et al. (2006) found that HzRGs (z > 2 in the sample) with smaller radio sources and more perturbed gas (emission line) kinematics show lower UV continuum polarization, which could be due to the presence of more luminous young stellar populations and can possibly be explained by the interaction between radio jets and the ISM that enhances star formation. Besides, there is also an anticorrelation between the rest frame submillimeter flux density and radio size in HzRGs (Humphrey et al. 2011), although it is not clear if the physics behind this is feedback-induced star formation, a simultaneous triggering of star formation and the radio-loud AGN activity, or simply environmental effects. Some well-studied HzRGs show evidence of having high SFRs (e.g., 4C41.47 and PKS 0529−549; Nesvadba et al. 2020; Falkendal et al. 2019). In these sources, we may interestingly be witnessing both the jets compressing the gas, leading to enhanced SFRs (e.g., Fragile et al. 2017), and the feedback from the AGN and star formation quenching it (Man et al. 2019).

2018ApJ...854..120M__Baxter_et_al._2016_Instance_1

The main purpose of this paper is to calibrate the mass–observable relation from a joint measurement of the abundance (number counts) and the stacked cluster weak lensing profiles. We develop and apply our method to the Sloan Digital Sky Survey (SDSS) red-sequence Matched-filter Probabilistic Percolation (redMaPPer) cluster catalog that is constructed by identifying overdensities of red sequence galaxies with similar colors to galaxy clusters from the SDSS ugriz photometries (Rozo & Rykoff 2014; Rykoff et al. 2014; Rozo et al. 2015a, 2015b; see most recently Rykoff et al. 2016, for the details of the method). Since the cluster finder gives an estimation of the optical richness, λ, for each cluster, we will constrain the scaling relation between the optical richness and mass for the clusters. In this paper we develop a forward modeling approach, where we constrain the probability distribution of richness for a given halo mass, . This is in contrast with previous studies (Baxter et al. 2016; Jimeno et al. 2017; Melchior et al. 2017; Simet et al. 2017), where the backward modeling approach is employed to constrain the probability of mass for a given richness, . The forward modeling approach has several advantages. First, we can use the abundance measurements more easily to constrain the mass–observable relation, as Saro et al. (2015) constrained from the abundance measurements of SZ-selected clusters after matching to redMaPPer clusters. Second, can be inferred from once the halo mass function is given, based on the Bayes theorem, while the opposite transformation, i.e., inferences of from , is not straightforward, because this requires knowledge of the richness function over the whole range of λ, which is not generally available, or is at least very noisy (and possibly affected by contamination), for richness below a threshold richness in cluster catalogs. Third, the forward modeling is convenient to generate mock catalogs of clusters by populating halos in N-body simulations with galaxies, e.g., to test systematics in a cluster-finding algorithm.

2022AandA...659A.180G__Kutsenko_et_al._2018_Instance_1

In the last few decades, the dynamic properties of the quiet Sun have been thoroughly investigated using a range of substantially different techniques, allowing us to elaborate a consistent picture of the photospheric dynamics by approaching the problem from different points of view. Particularly interesting and promising are the studies involving the tracking of small-scale magnetic fields in the quiet photosphere. Such investigations reveal features that still cannot be captured by theoretical models and/or simulations because of the complexity of the system and the simultaneous coupling of a wide range of spatial and temporal scales. These studies are based on the hypothesis that magnetic fields are passively transported by the plasma flow and provide a characterisation of advection and diffusion processes in the quiet photosphere from granular to supergranular scales (see, e.g. Wang 1988; Berger et al. 1998; Cadavid et al. 1998, 1999; Hagenaar et al. 1999; Lawrence et al. 2001; Sánchez Almeida et al. 2010; Abramenko et al. 2011; Manso Sainz et al. 2011; Lepreti et al. 2012; Giannattasio et al. 2013, 2014a,b; Giannattasio et al. 2019; Keys et al. 2014; Caroli et al. 2015; Del Moro et al. 2015; Yang et al. 2015a,b; Roudier et al. 2016; Abramenko 2017; Kutsenko et al. 2018; Agrawal et al. 2018; Giannattasio & Consolini 2021). These studies reveal an anomalous scaling of magnetic field transport with a superdiffusive character consistent with a Levy walk inside supergranules and a more Brownian-like motion in their boundary. This has provided constraints on the magnetic flux emergence and evolution that models have to consider in order to fully explain the dynamics governing these environments. At the same time, the scaling laws affecting magnetic fields in the quiet Sun are crucial to understanding how such fields vary with scale size, despite the small scales at which dissipation occurs still being inaccessible with the currently available observations (see, e.g. Lawrence et al. 1994; Stenflo 2012, and references therein). For example, in the milestone work by Stenflo (2012), the spectrum of magnetic flux density in the quiet Sun was found to be consistent with a Kolmogorov power-law scaling. The scale at which scale invariance is broken lies below the current resolution limit. This latter author argued that the collapse of magnetic fields in Kilogauss flux tubes injects energy that is expected to cascade down because of the flux decay occurring via interchange instability, and to fragment into weaker ‘hidden’ fields at smaller scales (down to ∼10 km). As far as we know, no other studies have focused on the scaling properties characterising the magnetic fields in a quiet Sun region within a range of spatial and temporal scales from (sub)granular to supergranular in the time domain. In this work, for the first time we apply the structure function analysis typical of complex systems (Frisch 1995) to fill this gap. This approach complements the studies based on feature tracking mentioned above. The main difference is that, while in those works statistical properties of the photospheric plasma flows are investigated via the transport of small-scale magnetic fields in a frozen-in condition, here we directly study the magnetic field variations emerging from magnetogram time-series. The paper is organised as follows. Section 2 describes the data set used and the analysis techniques applied. Section 3 describes the obtained results, while Sect. 4 is devoted to their discussion in the light of current literature. Finally, in Sect. 5, we present our conclusions and present future perspectives.

2022ApJ...926...21B__Viviani_et_al._2018_Instance_1

Some studies have used the 2.5D mean-field dynamo approach to do so, extending solar mean-field dynamo models to other stellar spectral types (Chabrier & Küker 2006; Jouve et al. 2010; Küker et al. 2011; Kitchatinov et al. 2018, and references therein). While these studies are very helpful, most of them lack the full nonlinearity and genuine parametric dependence of 3D magnetohydrodynamic (MHD) simulations. Recent developments by Pipin (2021) are starting to overcome these limits and have extended the work of Rempel (2006) on the Sun to solar-type stars with various rotation rates. Nevertheless, with the arrival of more powerful supercomputers, other authors have used instead global 3D MHD simulations to model DR and stellar magnetism in the convection zone of solar-like stars (Glatzmaier & Gilman 1982; Miesch et al. 2000, 2006; Brun et al. 2004, 2011; Brown et al. 2008, 2010; Ghizaru et al. 2010; Käpylä et al. 2011, 2014; Gastine et al. 2014; Augustson et al. 2015; Karak et al. 2015). These studies pointed out the large magnetic temporal variability and the critical effect of stellar rotation and mass on magnetic field generation through dynamo mechanism, leading in some parameter regimes to configurations with cyclic activity (Gilman & Miller 1981; Gilman 1983; Glatzmaier 1985a; Brown et al. 2011; Racine et al. 2011; Augustson et al. 2013, 2015; Käpylä et al. 2013; Nelson et al. 2013; Beaudoin et al. 2016; Guerrero et al. 2016, 2019; Strugarek et al. 2017, 2018; Viviani et al. 2018, 2019; Warnecke 2018; Matilsky & Toomre 2020). Several studies pointed out the positive effect of a stable region underneath the convection zone (Parker 1993) on the efficient storage of intense toroidal field and the lengthening of the stellar dynamo cycle period (Glatzmaier 1985b; Browning et al. 2006; Lawson et al. 2015; Beaudoin et al. 2016; Guerrero et al. 2016, 2019; Käpylä et al. 2019; Bice & Toomre 2020). Over the last decade, significant progress has been made in successfully simulating large-scale mean flows and stellar activity cycle using different numerical codes and methods (Jones et al. 2011). This is quite reassuring that a global consensus is growing on the nature of solar-like star dynamos. It is common knowledge that there are still key transitions in Rossby number (at low and high values of this parameter) that need to be understood further, as well as what is the exact type of convective dynamos realized in solar-like stars as their global parameters are varied. This study continues this effort by doing an even broader systematic parametric study of solar-like star dynamos coupled to a stably stratified layer below than what have been published so far. It extends the work published in Varela et al. (2016) and Brun et al. (2017) with the MHD anelastic spherical harmonic code (ASH) (Brun et al. 2004). In particular, we wish to better characterize energy transfers and how much of a star’s energy (luminosity) is converted into magnetic energy by nonlinear global convective dynamos over a wide range of Rossby numbers, generalizing to solar-like stars the work by Starr & Gilman (1966) and Rempel (2006).

2018ApJ...869..143P__Wills_&_Browne_1986_Instance_1

In order to understand this discrepancy, we consider the BL Lac object nature of NGC 1275 (Veron 1978). The BL Lac object properties of 3C 84 have been noted in connection with the synchrotron optical emission that hides the accretion generated continuum. The BL Lac object aspect can be very pronounced with optical polarization that changes dramatically in amplitude and position angle, with the largest optical polarization reaching 6% (Angel & Stockman 1980). Such extreme blazar-like properties suggest a small LOS to the jet axis (Lind & Blandford 1985). We qualify this statement by noting that the evidence does not support extreme BL Lac object behavior. The range of polarization is 1%–6% in Angel & Stockman (1980) and more extensive polarization data9 9 From http://www.bu.edu/blazars/VLBAproject.html. covering the time period 2011–2018 indicates an optical polarization that is usually below 2% and extremely rare (2) instances of polarization >3% were reported. This suggests a slightly off angle BL Lac object. The Hβ BEL is considered to be rotating gas in a flat “pancake-like” region in which the normal to the BEL disk is parallel to the jet axis (Wills & Browne 1986). Thus, the FWHM that appears in Equation (4) depends on the LOS. For polar lines of sight, Equation (4) will under estimate Mbh. In the virial mass estimation, 5 where G is the gravitational constant, RBLR is the orbital radius of the BLR (broad line region) and vBLR is the velocity of the BEL gas. In order to relate vBLR to an observed quantity, one defines the de-projection factor, f, 6 Equations (5) and (6) indicate that . The de-projection factor has been estimated for various classes of objects that are believed to be differentiated by an LOS (Antonucci 1993; DeCarli et al. 2011). The method of DeCarli et al. (2011) was to estimate Mbh from the bulge luminosity of the host galaxy. Using this estimate to set the value of Mbh in the virial formula, they were able to estimate f for various classes of objects, 7 Equation (4) is derived based on assuming an isotropic distribution of BEL gas velocity. Thus, we adopt a correction factor for the estimate in Equation (4) of for BL Lac object orientations such as the one that exists in 3C 84. Taking the nominal value of DeCarli et al. (2011) in Equation (7), we expect a correction factor of 64. The orientation corrected central black hole mass estimate based on the data in Table 1 yields . Alternatively, if we use the blazar correction of 42 associated with the nominal value of fblazars in Equation (7) instead, we get .

2021ApJ...908...95H__Harrington_et_al._2016_Instance_1

Strong gravitational lensing of high-z star-forming galaxies offers a unique way to examine highly magnified molecular gas. The method for selecting strongly lensed dusty galaxy candidates, at z > 1, is primarily based on unusually bright (sub)millimeter fluxes compared to the expected steep drop-off in (sub)millimeter number counts (e.g., Negrello et al. 2007, 2010). This method has since identified a large number across the extragalactic sky, i.e., more than 100 lensed candidates at z > 1 (Ivison et al. 2010; Vieira et al. 2010, 2013; Bussmann et al. 2013, 2015; Wardlow et al. 2013; Weiß et al 2013; Cañameras et al. 2015; Harrington et al. 2016; Strandet et al. 2016; Díaz-Sánchez et al. 2017; Negrello et al. 2017; Bakx et al. 2018). The lensed population of dusty star-forming galaxies selected by the South Pole Telescope (SPT), Herschel Space Observatory, and Planck has now been detected in more than two CO transitions (e.g., Spilker et al. 2016; Strandet et al. 2017; Yang et al. 2017; Bakx et al. 2020; this work). The Herschel-selected, strongly lensed galaxy sample (Bussmann et al. 2013) offered the first systematic approach to producing a statistically significant sample of CO/[C i] lines (Yang et al. 2017), followed by a compilation in 11 Planck- and Herschel-selected lensed galaxies (Cañameras et al. 2018b), including four galaxies with both [C i] lines detected (Nesvadba et al. 2019). The IR-to-CO luminosity relations of local starbursts and high-z star-forming galaxies explored by Greve et al. (2014) indicate that the ISM radiation field is an important component to consider when understanding CO line excitation, yet this investigation was limited to 23 unlensed and 21 lensed dusty star-forming systems—all with more than three frequency measurements of the dust continuum and usually a single CO line detection. Most previous studies used only single- and/or double-component gas-emitting regions to reproduce the observed CO emission, excluding the simultaneous modeling of the available [C i] emission, but also ignoring the role of the dust continuum emission as a heating source of the gas.

2019ApJ...880...92J__Yang_et_al._2013_Instance_1

Studies of molecules play a prominent role in explaining the physical, chemical, and kinematic properties of the interstellar medium (ISM) in galaxies (Omont 2007; Tielens 2013). One such molecule is H2O, the third most abundant molecule in the warm dense ISM after H2 and CO (Neufeld et al. 1995). As an asymmetric rotor with a large electric dipole moment, H2O has a rich and complex spectrum giving rise to emission and absorption lines mainly in the submillimeter and far-infrared (FIR) regimes of the electromagnetic spectrum. Observations from local galaxies (van der Werf et al. 2010; Weiß et al. 2010; Rangwala et al. 2011; Yang et al. 2013), high-redshift ultra-luminous infrared galaxies (ULIRGs; Omont et al. 2013; Yang et al. 2016), and active galactic nuclei (AGNs; van der Werf et al. 2011) have shown H2O emission to be ubiquitous with intensities as bright as CO lines. Modeling has shown that, in addition to infrared pumping where H2O is excited by FIR photons, collisions also contribute to the intensities of low-excitation transitions (e.g., González-Alfonso et al. 2010, 2012). This is best represented in Figure 3 from Liu et al. (2017), which shows prominent H2O lines in different ISM components. The low-excitation lines become weaker or completely disappear in the warm and hot regions (>40 K) where infrared pumping dominates over collisions. The higher excitation transitions that require strong far-infrared radiation density are mainly found in the hotter regions (100–200 K) of the galaxy. The cascading emission lines, (Eup = 100.8 K,νrest = 987.927 GHz), (Eup = 137 K, νrest = 752.033 GHz), and p-H2O (22,0 − 21,1) (Eup = 196 K, νrest = 1228.789 GHz) are pumped by 101 μm photons from the base 11,1 level and are primarily excited in the warm regions of the galaxy. The collisional excitation of the low-lying levels (11,1 and 20,2) in optically thin or high-density hot regions might also contribute to the emission of the line. Hence, H2O transitions probe the infrared radiation field density and physical properties of the ISM such as gas density and kinetic temperature (e.g., Weiß et al. 2010; González-Alfonso et al. 2014; Liu et al. 2017).

2016ApJ...821...74J__Tokovinin_et_al._2013_Instance_1

Recent theoretical work has suggested that the presence, or lack thereof, of long-period giant planets could affect the formation of such systems. Batygin & Laughlin (2015) argued that the migration of Jupiter within our own solar system might have disrupted a massive primordial inner protoplanetary disk that could have formed multiple short-period super-Earths; they predicted that systems like the Kepler short-period multiple systems should typically lack long-period giant planets. A related question is, how common are planetary systems broadly similar in architecture to our solar system, with small close-in planets and more distant giant planets? We can begin to answer these questions in the near future through the combination of searches for short-period super-Earths and data from the long-term RV programs that have been monitoring many bright FGK stars for well over a decade. Super-Earths can be found with either high-precision RV observations or space-based transit searches. Such high-precision RV surveys include those being undertaken currently with HARPS (e.g., Díaz et al. 2016), HARPS-N (M15), APF (Vogt et al. 2014), and CHIRON (Tokovinin et al. 2013), and in the near future with MINERVA (Swift et al. 2015), CARMENES (Quirrenbach et al. 2014), ESPRESSO (Mégevand et al. 2014), and SPIRou (Artigau et al. 2014). The major upcoming space-based transit survey is that of TESS (Ricker et al. 2015). Long-term RV programs include the McDonald Observatory Planet Search (e.g., Endl et al. 2016), the Anglo-Australian Planet Search (e.g., Jones et al. 2010), the Lick-Carnegie Exoplanet Survey (e.g., Rowan et al. 2016), the CORALIE planet search (Marmier et al. 2013), and the planet search at ESO (e.g., Zechmeister et al. 2013). Long-period giant planets will also be found by Gaia, which will produce a huge sample of astrometrically detected planets (Perryman et al. 2014). While most of the Kepler sample is too faint to have been observed previously by long-term RV surveys (e.g., Coughlin et al. 2015), Gaia will be able to astrometrically detect long-period planets around many of these stars. Our own McDonald Observatory Planet Search program now has a baseline of 12–15 years for ∼200 FGKM stars, and a handful of stars also have lower precision observations dating back more than 25 years. HD 219134 is one of these stars, and here we present an analysis of our RV observations of this star, as well as our data on the stellar activity.

2018AandA...612A..77M__Gromadzki_&_Mikołajewska_(2009)_Instance_1

“Wiggling” outflows are often observed among young stellar jets and protostellar molecular outflows (Eisloffel et al. 1996; Terquem et al. 1999). Terquem et al. (1999) investigated such binary systems where the accretion disk, from which the jet originates, is inclined to the binary orbital plane. They concluded that the observed jet “wiggling” is a consequence of the jet precession caused by tidal interactions in such non-coplanar binary systems. Nichols & Slavin (2009) as well as Hollis & Michalitsianos (1993) suggested that the precession of the accretion disk around the WD may be responsible for the bending of the wide-angle outflow found in the previous studies. In analogy to these observations of young stellar jets, we suggest that the “wiggling” that we also find here for the R Aqr jet may result from disk precession as well. We estimated the precession period using the theory from Terquem et al. (1999) and the binary parameters taken from Gromadzki & Mikołajewska (2009) – Mh = 0.8M⊙ (the mass of the hot WD companion), Mp∕Mh = 1.65 (where Mp is the mass of the primary companion), D = 15.5 AU (the mean semi-major axis of the system), and e = 0.25 (eccentricity). The value of Rd is unknown in our case and we used Rd = 5 AU giving D∕Rd ≈ 3 which corresponds to the average value of 2 ≤ D∕Rd ≤ 4 (the range taken from Terquem et al. 1999). For this calculation, we assumed that the angle δ between the disk plane and that of the binary orbit is small enough (10°) and we adopted cosδ = 1. Using Eq. (1) from Gromadzki & Mikołajewska (2009), we derived the precession time of T ≈ 530 yr. This value is quite large for the wiggling waves that we see. We estimated the projected spatial wavelength λproj of the “wiggling” wave according to λ = λproj∕sin i, where i is the angle between the jet symmetry axis and the line of sight, and T = λ∕υ, where υ is the jet velocity, from Gromadzki & Mikołajewska (2009). Using i = 72° and υ ~ 100 km/s, we derive λproj ≈ 10 500 AU which is more than 20 times larger than the projected length of the observed wiggling outflow (2′′ ≈ 440 AU). However, we should note that the precessing time strongly depends on the D∕Rd; the T decreases significantly with increasing R. It may also be the case that the “wiggling” model developed for YSO jets is not fitting for R Aqr which consists of evolved objects, and both the WD and the disk where the jet probably forms are much hotter than YSO systems. Furthermore, we cannot exclude that the steady wiggling might be a sequence of dynamical interactions of the two collimated flows tilted to each other.

2018MNRAS.479.3438G___2005_Instance_1

For instance, due to its dissipative nature, gas can be very efficient in absorbing and transporting outwards the angular momentum of the pair, likely leading to a rapid evolution and eventual coalescence. From observations, as well as numerical simulations, it has been established that in gas-rich galaxy mergers there is a large inflow of gaseous material to the central kiloparsec of the galactic remnant, often resulting in a massive circumnuclear disc (Barnes & Hernquist 1992; Sanders & Mirabel 1996; Mayer et al. 2007). Driven by dynamical friction and global torques from this disc, the pair of MBHs decays very efficiently down to separations of the order of ∼1–0.1 pc, where it forms a gravitationally bound binary (Escala et al. 2004, 2005; Mayer et al. 2007; Fiacconi et al. 2013; del Valle et al. 2015; Roškar et al. 2015). At these sub-parsec scales, most theoretical and numerical studies have focused on the evolution of binaries surrounded by a gaseous circumbinary disc, often either co-rotating (see e.g. Ivanov, Papaloizou & Polnarev 1999; Armitage & Natarajan 2005; Cuadra et al. 2009; Haiman, Kocsis & Menou 2009; Lodato et al. 2009; Nixon et al. 2011; Roedig et al. 2011, 2012; Kocsis, Haiman & Loeb 2012; Amaro-Seoane, Brem & Cuadra 2013; D’Orazio, Haiman & MacFadyen 2013; Muñoz & Lai 2016; Miranda, Muñoz & Lai 2017; Tang, MacFadyen & Haiman 2017) or counter-rotating (see e.g. Roedig & Sesana 2014; Nixon & Lubow 2015) with respect to the binary’s orbital motion. These discs are generally assumed to be well-defined, smooth, and relaxed, with no attempt to link their presence to the gaseous environment around the binary, nor to the fuelling mechanisms that bring gas to the nucleus. Furthermore, all these idealized scenarios are subject to the disc consumption problem, namely, if the disc dissolves through some process (e.g. star formation, active galactic nucleus (AGN)/supernovae feedback, Lupi et al. 2015), the evolution of the binary orbit stops. In fact, the evolution of MBHBs in gas-rich environments is intimately related to the unsolved problem of gas supply to the centre of galactic nuclei.

2021AandA...654A.124W__Tanvir_et_al._2017_Instance_1

The first multi-messenger GW event was discovered on 17 August, 2017. About 1.7 s after the GW170817 signal detected by LIGO and Virgo (Abbott et al. 2017a), the Fermi Gamma-ray Burst Monitor was successfully triggered by GRB 170817A (Abbott et al. 2017b; Goldstein et al. 2017; Zhang et al. 2018) and subsequently a large number of follow-up observations monitored the afterglow emission in different electromagnetic bands from the radio to X-rays (Alexander et al. 2017; Hallinan et al. 2017; Margutti et al. 2017; Troja et al. 2017; D’Avanzo et al. 2018; Ghirlanda et al. 2019; Lazzati et al. 2018; Lyman et al. 2018) and the kilonova AT 2017gfo in the ultraviolet–optical–infrared band (Abbott et al. 2017c; Andreoni et al. 2017; Arcavi et al. 2017; Chornock et al. 2017; Coulter et al. 2017; Covino et al. 2017; Cowperthwaite et al. 2017; Evans et al. 2017; Hu et al. 2017; Kilpatrick et al. 2017; Lipunov et al. 2017; Nicholl et al. 2017; Smartt et al. 2017; Soares-Santos et al. 2017; Tanvir et al. 2017). The observations of GRB 170817A and its afterglows robustly confirmed the long-standing hypothesis that SGRBs can originate from compact binary mergers. Moreover, it became possible to explore the angular structure of the SGRB jet from an off-axis view (Lamb & Kobayashi 2017; Granot et al. 2018; Lazzati et al. 2018; Mooley et al. 2018a,b; Li et al. 2019). Meanwhile, the observations of AT 2017gfo indicated the existence of the merger ejecta, which suggests that the progenitor binary should at least contain one NS. In more detail, the existence of a “blue” and possibly also a “purple” component in the AT 2017gfo emission further indicated that the merger product of the GW170817 event is very likely to be a hypermassive NS, which lasted for at least a few hundred milliseconds, as an immediately formed black hole can only be associated with a “red” kilonova1 (Cowperthwaite et al. 2017; Perego et al. 2017; Tanaka et al. 2017; Tanvir et al. 2017; Villar et al. 2017; Kawaguchi et al. 2018). Therefore, in summary, the progenitor of the GW170817 event can be identified as a DNS system, which is consistent with the result of the GW analysis.

2022AandA...658A.194P__Khata_et_al._2020_Instance_2

The stellar photospheric parameters we collected from literature for the benchmark stars are summarized in Table A.1. Although most benchmark stars have v sini 2 km s−1 (Reiners et al. 2018), there are two stars with larger values: J07558+833 (12.1 km s−1) and J13005+056 (16.4 km s−1). These stars are useful to investigate the performance of the algorithms when dealing with higher rotational velocities. The literature values were derived with different methods. These methods include: interferometry to estimate the stellar radius and Teff (Boyajian et al. 2012; Ségransan et al. 2003; von Braun et al. 2014; Berger et al. 2006; Newton et al. 2015), synthetic model fitting using BT-Settl models to determine Teff (Gaidos et al. 2014; Lépine et al. 2013; Gaidos & Mann 2014; Mann et al. 2015) and log g (Lépine et al. 2013), empirical relations to derive stellar mass in the form of mass-luminosity relations (Mann et al. 2015; Khata et al. 2020; Boyajian et al. 2012; Berger et al. 2006; Ségransan et al. 2003), along with the mass-magnitude relations (Maldonado et al. 2015), mass-radius relations (von Braun et al. 2014), mass–Teff relations (Gaidos & Mann 2014; Gaidos et al. 2014), empirical relations to derive the stellar radius in the form of mass-radius relations (Maldonado et al. 2015) and Teff–radius relations (Gaidos & Mann 2014; Gaidos et al. 2014; Houdebine et al. 2019), pEW measurements to determine Teff (Maldonado et al. 2015; Neves et al. 2014; Newton et al. 2015) and [Fe/H] (Maldonado et al. 2015; Neves et al. 2014; Gaidos et al. 2014; Mann et al. 2015), the definition of spectral indices such as the H2O-K2 index to estimate Teff (Rojas-Ayala et al. 2012), as well as the combination of the H2O-K2 index with pEWs to derive [Fe/H] (Rojas-Ayala et al. 2012; Khata et al. 2020), the stellar radius and Teff (Khata et al. 2020), and spectral curvature indices for the determination of Teff (Gaidos & Mann 2014). Additionally, [Fe/H] was derived by using color-magnitude metallicity relations (Dittmann et al. 2016), atomic line strength relations (Gaidos & Mann 2014), and spectral feature relations (Terrien et al. 2015). Terrien et al. (2015) used K-band magnitudes and the Dartmouth Stellar Evolution Program (Dotter et al. 2008) to derive the stellar radius, whereas Mann et al. (2015) employed the Boltzmann equation with Teff determined from synthetic model fits. Last, but not least, Houdebine et al. (2019) derived Teff from photometric colors. For more details on the individual methods, we refer to the descriptions in the corresponding works.

2022AandA...659A..44S__Gandolfi_et_al._2010_Instance_1

Discovery of exoplanetary systems has presented a rather more complex picture of planetary architectures. Transiting exoplanets, those that cross the visible disk of their host stars from our vantage point, permit the measurement of the spin-orbit misalignment between the planetary orbital plane and the stellar equatorial plane that is projected onto the sky, as well as other crucial characteristics (Triaud 2018). This is what is referred to as the sky-projected obliquity angle (λ hereafter). Its measurement is performed through the observations of the Rossiter-McLaughlin effect (Rossiter 1924; McLaughlin 1924). For exoplanets, it entails observations of the stellar radial velocity (RV) during the planetary transit. The anomaly in the measured RV values arises from the deformation of absorption lines from which they are determined, which is caused by the transiting planet occulting either the blue- or red-shifted portion of the spinning stellar disk. The measurement of this effect is possible thanks to precision, high dispersion spectrographs at large telescopes that allow for one to obtain high resolution and large signal-to-noise ratio (S/N) spectra at relatively high temporal sampling. The measurement of λ has been performed for a large number of transiting exoplanets, full details of which can be found in TEPCAT1 (Southworth 2011). These have revealed a surprising diversity in the orbital alignments (for example Queloz et al. 2000; Winn et al. 2005, 2006, 2009; Triaud et al. 2009; Gandolfi et al. 2010; Mancini et al. 2018; Yu et al. 2018; Lendl et al. 2020; Sedaghati et al. 2021), which is in contrast to the Laplacian ideals of planets forming inside a flat disk, coplanar with the stellar equator and staying there (de Laplace 1796). A surprising picture that has emerged is that a significant fraction of those close-in hot-Jupiter regime planets are on misaligned orbits, as is evident in panel b of Fig. 1 (Albrecht et al. 2012; Dawson 2014). Furthermore, the spectral type of the host also appears to play a role, whereby giant planets around hot stars seem to exist on more oblique orbits (panel a of Fig. 1), perhaps pointing to a different, more chaotic formation history, as compared to their cooler counterparts. The relation between the obliquity and the host star temperature was observed by Winn et al. (2010), who placed the boundary between the two regimes at T⋆ = 6250 K (namely theKraft break; Kraft 1967). Hébrard et al. (2011) also point out a lack of planets with masses > 3 MJup on retrograde orbits, the distribution for which is shown in panel c of Fig. 1. Tidal interactions over time with the host star are also expected to realign orbits of close-in, massive planets (Zahn 1977). Attempts have been made to study the impact of stellar age on the obliquity of planetary orbits (for example Safsten et al. 2020; Anderson et al. 2021), with Triaud (2011) finding that hot-Jupiters around younger A stars are more misaligned, setting the age barrier at 2.5 Gyr. However, a lack of precision in the measured stellar ages and the absence of uniform and homogeneous studies estimating those ages have hindered any concrete conclusions being drawn with regard to the impact of stellar ages on planetary orbital alignments. This fact is evident in panel d of Fig. 1.

2018AandA...619A..13V__Saviane_et_al._2012_Instance_1

The EWs were measured with the methods described in Vásquez et al. (2015). As in Paper I, we used the sum of the EWs of the two strongest CaT lines (λ8542, λ8662) as a metallicity estimator, following the Ca II triplet method of Armandroff & Da Costa (1991). Different functions have been tested in the literature to measure the EWs of the CaT lines, depending on the metallicity regime. For metal-poor stars ([Fe/H] ≲ −0.7 dex) a Gaussian function was used with excellent results (Armandroff & Da Costa 1991), while a more general function (such as a Moffat function or the sum of a Gaussian and Lorentzian, G + L) is needed to fit the strong wings of the CaT lines observed in metal-rich stars (Rutledge et al. 1997; Cole et al. 2004). Following our previous work (Gullieuszik et al. 2009; Saviane et al. 2012) we have adopted here a G+L profile fit. To measure the EWs, each spectrum was normalised with a low-order polynomial using the IRAF continuum task, and set to the rest frame by correcting for the observed radial velocity. The two strongest CaT lines were fitted by a G+L profile using a non-linear least squares fitting routine part of the R programming language. Five clusters from the sample of Saviane et al. (2012) covering a wide metallicity range were re-reduced and analysed with our code to ensure that our EWs measurements are on the same scale as the template clusters used to define the metallicity calibration. Figure 5 shows the comparison between our EWs measurements and the line strengths measured by Saviane et al. (2012) (in both cases the sum of the two strongest lines) for the five calibration clusters. The observed scatter is consistent with the internal errors of the EW measurements, computed as in Vásquez et al. (2015). The measurements show a small deviation from the unity relation, which is more evident at low metallicity. A linear fit to this trend gives the relation: ΣEW(S12) = 0.97 ΣEW(this work) + 0.21, with an rms about the fit of 0.13 Å. This fit is shown in Fig. 5 as a dashed black line. For internal consistency, all EWs in this work have been adjusted to the measurement scale of Saviane et al. (2012) by using this relation. In Table 3 we provide the coordinates, radial velocities, and the sum of the equivalent widths for the cluster member stars, both measured (“m”) and corrected (“c”) to the system of Saviane et al. 2012.

2015AandA...578A.124N__Jansen_et_al._(1995)_Instance_1

The Orion Bar is an ideal source for probing the excitation and chemistry of molecules in PDRs, thanks to its close distance of 414 pc (Menten et al. 2007) and its well-known structure and geometry. The Orion Bar is located between the Orion molecular cloud and an Hii region illuminated by the Trapezium cluster. The FUV radiation field of the Trapezium cluster at the location of the Orion Bar is equivalent to (1−4) × 104χ0 in Draine (1978) units. Its orientation changes from face-on to nearly edge-on where the molecular emissions peak. The observations presented in this paper also correspond to the nearly edge-on orientation part of the Orion Bar. The geometrical enhancement of the column densities toward the nearly edge-on part of the Orion Bar was derived by multiple studies and is in the range between 4 and 20. The tilt angle compared to a completely edge-on orientation was suggested to be 3° in the model of Hogerheijde et al. (1995) and Jansen et al. (1995). A tilt angle of 3° is equivalent to an enhancement factor of 20 for the measured column densities. Based on Oi 1.317 μm emission, Walmsley et al. (2000) find a model that requires a geometrical enhancement factor of 5 to convert the observed column densities into face-on values. Neufeld et al. (2006) find the geometrical enhancement factor to be 4 based on measured C+ column densities. Using a clumpy 3D PDR model, Andree-Labsch et al. (2014) successfully reproduced the Orion Bar stratification using a clumpy edge-on cavity wall, and they claim that a model of a convex filament fails to describe the structure of the Orion Bar. The average kinetic temperature was estimated to be 85 K (Hogerheijde et al. 1995). Closer to the ionization front, higher temperatures are also measured; for example, OH transitions observed with Herschel/PACS are consistent with 160−220 K gas (Goicoechea et al. 2011) and CH+ observations with temperatures around 500 K (Nagy et al. 2013). Part of the molecular line emission measured toward the Orion Bar corresponds to an “interclump medium” with densities between a few 104 and 2 × 105 cm-3 (Simon et al. 1997). It has been suggested that other molecular lines originate in clumps with densities in the range between 1.5 × 106 and 6 × 106 cm-3 (Lis & Schilke 2003).

2022AandA...663A.105P__Bonafede_et_al._2012_Instance_1

Cluster radio relics are usually found in the outskirts of merging galaxy clusters. They exhibit elongated morphologies and high degrees of polarisation above 1 GHz (up to 70%, Ensslin et al. 1998; Bonafede et al. 2014; Loi et al. 2019; de Gasperin et al. 2022). The resolved spectral index in radio relics shows a gradient: it steepens towards the cluster centre and flattens towards the outskirts. Their size can reach up to ∼2 Mpc, and high-resolution observations have revealed filamentary structures within relics themselves (Di Gennaro et al. 2018; Rajpurohit et al. 2020, 2022a,b; de Gasperin et al. 2022). The Largest Linear Sizes (LLS) and radio powers of relics are correlated, as well as the integrated spectral index and the radio power (van Weeren et al. 2009b; Bonafede et al. 2012; de Gasperin et al. 2014). Relics trace ICM shock waves with relatively low (M   3) Mach numbers (Finoguenov et al. 2010; Akamatsu et al. 2013; Shimwell et al. 2015; Botteon et al. 2016). The acceleration of electrons is believed to proceed via diffusive shock acceleration (DSA) in the ICM (Ensslin et al. 1998; Roettiger et al. 1999), in which particles scatter back and forth across the shock front gaining energy at every crossing. Nevertheless, this mechanism has been shown to be rather inefficient in accelerating electrons from the thermal pool (Vazza & Brüggen 2014; Vazza et al. 2016; Botteon et al. 2020a; Brüggen & Vazza 2020; see Brunetti & Jones 2014 for a review). Recently, it has been suggested that seed electrons could originate from the tails and lobes (driven by AGN outflows) of cluster radio galaxies (Bonafede et al. 2014; van Weeren et al. 2017; Stuardi et al. 2019), which alleviates the requirements of high acceleration efficiencies at cluster shocks (e.g., Markevitch et al. 2005; Kang et al. 2012, 2017; Botteon et al. 2016; Eckert et al. 2016). In some cases, double relics have been detected on opposite sides of the cluster centre (e.g., Rottgering et al. 1997; van Weeren et al. 2010, 2012b; Bonafede et al. 2012; de Gasperin et al. 2015a). In these clusters it is possible to constrain the merger history, providing important information about the formation processes of relics.

2019MNRAS.484.2605M__Umeda_et_al._2016_Instance_1

Remnant BHs of Population III stars with ${\sim }10^{2}\, \mathrm{M}_{\odot }$ are one of the candidates for such seeds (e.g. Madau & Rees 2001). They can grow SMBHs in the available time if either with continuous accretion at the Eddington limit or with short episode of super-Eddington growth. In reality, however, the BH’s growth can easily be hindered by its own radiative feedback (Milosavljević, Couch & Bromm 2009; Park & Ricotti 2011; Orofino, Ferrara & Gallerani 2018; Sugimura et al. 2018). An alternative and attractive pathway for seed BH formation is via the so-called direct collapse (e.g. Bromm & Loeb 2003), where a supermassive star (SMS) with ${\sim } 10^{5}\, \mathrm{M}_{\odot }$ collapses into a BH with a similar mass by general relativistic instability (Umeda et al. 2016; Woods et al. 2017; Haemmerlé et al. 2018). Here, SMSs are supposed to form from a primordial gas in some peculiar sites. Unlike in ordinary first star formation, which is driven by H2 cooling (see e.g. Bromm & Larson 2004; see also Glover 2013 for a review), H2 is dissociated by strong external far-ultraviolet (UV) radiation from nearby galaxies and the contraction of clouds is solely caused by H atomic cooling in the most intensively studied channel for SMS formation (Omukai 2001; Omukai, Schneider & Haiman 2008; Shang, Bryan & Haiman 2010; Regan, Johansson & Wise 2014; Sugimura, Omukai & Inoue 2014). Such clouds contract almost isothermally at ∼104 K without experiencing vigorous fragmentation. The protostar formed at the centre subsequently accretes the gas at a high rate of $10^{-1}\, \mathrm{M}_{\odot }\, \mathrm{yr}^{-1}$ due to high temperature (Latif et al. 2013; Inayoshi, Omukai & Tasker 2014; Becerra et al. 2015; Chon, Hosokawa & Yoshida 2018). Such rapidly accreting protostar inflates greatly in radius with effective temperature of several 1000 K and grows supermassive with ${\gtrsim } 10^{5}\, \mathrm{M}_{\odot }$ avoiding ionization radiation feedback on the accretion flow (Hosokawa, Omukai & Yorke 2012; Hosokawa et al. 2013), before collapsing by general relativistic instability.

2020AandA...640A..56R__Hosseinzadeh_et_al._2017_Instance_1

SN2006jc, PS15dpn and other narrow-line SNe. Two out of the three SNe we considered above are super-luminous, however the final collapse of a PPI+CC progenitor or PISNe does not need to be superluminous (Woosley 2017). The PPI is just one possible mechanism to create CSM, which can produce extreme luminosities by generating radiation from the kinetic energy of the ejecta and/or narrow emission lines (even if the luminosity does not reach extreme values). The detection of narrow H lines determines the classification of a SN as a type IIn, while the detection of narrow He emission lines determines the classification as type Ibn. Both kinds of event are too common to be entirely explained with PPI+CC progenitors, and it is likely that both classes contain events with a diversity of physical mechanisms (e.g., Pastorello et al. 2008 but see also Hosseinzadeh et al. 2017). Nevertheless, it is possible that at least some of these events might correspond to the observational counterpart of the death of PPI+CC progenitors. In particular, our simulations can produce several solar masses of H-free CSM moving at a few thousand km s−1, which correspond to the width of the He lines detected in some SN Ibn without any fine-tuning required. Even if the detection of narrow lines alone is not sufficient to associate a specific SN to a PPI event, combining evidences from previous coincident transients, large ejecta masses or long lightcurve durations, large 56Ni yields, an extremely young surrounding stellar population, and/or nucleosynthetic signatures might strengthen the case for associating specific event with this scenario. Possible examples of SN Ibn that might correspond to PPI+CC are SN2006jc and PS15dpn. The former showed relatively narrow He lines possibly hinting to asphericity of the CSM (Foley et al. 2007) and was spatially coincident with an unexplained outburst two years earlier (e.g., Pastorello et al. 2007; Foley et al. 2007). For the latter, Wang & Li (2019) proposed to fit the light curve by combining CSM interaction and radioactive decay, and inferred CSM and 56Ni masses of ∼0.8 M⊙ and ∼0.1 M⊙, respectively, in good agreement with our models.

2018MNRAS.476..184A__Rocha-Pinto_et_al._2000_Instance_1

The task of estimating stellar ages has been addressed by several authors and lots of different methods are found in the literature. For instance, there are (i) empirical methods, which use a deterministic relation between a given parameter and the age of a star (first proposed by Skumanich 1972). This is the case of gyrochronology (e.g. Barnes 2003, 2007; Mamajek & Hillenbrand 2008; Collier Cameron et al. 2009), decay of chromospheric activity (e.g. Soderblom, Duncan & Johnson 1991; Rocha-Pinto & Maciel 1998; Rocha-Pinto et al. 2000; Pace & Pasquini 2004; Lyra & Porto de Mello 2005; Pace et al. 2009; Zhao et al. 2011; Pace 2013), lithium depletion (Sestito & Randich 2005; Jackson & Jeffries 2014; Carlos, Nissen & Melendez 2016), and ‘magnetochronology’ (proposed by Vidotto et al. 2014). (ii) Model-dependent methods, which are based on the comparison between measurable physical quantities and the ones expected from stellar structure models that use age as one of its parameters. Isochrone fitting (Edvardsson et al. 1993; Nordström et al. 2004; Pont & Eyer 2004; Jørgensen & Lindegren 2005; Silaj & Landstreet 2014; Maxted, Serenelli & Southworth 2015) and asteroseismology (Cunha et al. 2007; Vauclair 2009; Metcalfe et al. 2010; Silva Aguirre et al. 2017) are classified in this category. (iii) Semifundamental methods, those that are based on well-known fundamental physics and employ only few assumptions. These are the cases for the method of cluster expansion (e.g. Makarov 2007) and nucleocosmocronology, known to predict unreliable ages (Ludwig et al. 2010). (iv) Statistical methods, which use statistical relations, like the age–metallicity relation (AMR) and the age–velocity dispersion relation (AVR), between a given property and the age. These relations have not been much explored in the literature as a direct tool to estimate stellar ages. Some few examples of its usage are found in Lachaume et al. (1999) and Maciel, Rodrigues & Costa (2011) (for the AVR) and Spina et al. (2016) (for the AMR, especially [Y/Mg] × age and [Y/Al] × age).

2015MNRAS.450.3458C__Cichowolski_et_al._2001_Instance_1

The kinetic energy stored in the CO shell can be estimated as $E_{\rm kin} = 0.5\, M_{\rm shell}\, V^2_{\rm exp}$, where Vexp is the expansion velocity of the shell and Mshell is the total (molecular, atomic, and ionized) shell mass. Adopting an expansion velocity equal to half the velocity interval where the structure is observed, Vexp = 7.0 ± 1.3 km s− 1 , the molecular mass given in Table 1 and the atomic and ionized masses estimated by Cichowolski et al. (2001), 1450 and 3000 M⊙, respectively, we obtain Ekin = (2.5 ± 1.0) × 1049 erg, assuming a 40 per cent error for the masses.. Although Cichowolski et al. (2001) concluded that WR 130 could have alone created the observed structure, it is important to note that they did not take into account the molecular mass present in the shell, which considerably increases the kinetic shell energy. Thus, we can compare now the new value obtained for Ekin with the mechanical energy deposited in the ISM by the wind of the WR star, Ew = (0.7–2.2) × 1050 erg (Cichowolski et al. 2001). We obtain ϵ = Ekin/Ew = 0.007–0.5. The ratio ϵ measures the energy conversion efficiency in the shell, and according to evolutionary models ϵ ≤ 0.2 (Koo & McKee 1992). Thus, not all the possible values of ϵ are compatible with the scenario where the energy injected during the WR phase is enough to create the structure. In this case, the contribution of the energy injected during the O-star phase and/or other massive stars, should be considered. As mentioned in the Introduction, WR 130 is a WNH star, and according to Smith & Conti (2008) its age would be of about 2–3 Myr and its initial mass of at least 60 M⊙. A rough estimation of the energy injected by such a star during its main sequence yields Ew = (2.5–3.5) × 1050 erg (de Jager, Nieuwenhuijzen & van der Hucht 1988), which would be enough to create the observed structure. We have nevertheless looked for the presence of other massive stars in the region. We queried the available catalogues such as the Galactic O-Star Catalog (Maíz Apellániz et al. 2013), the Early-Type Emission-Line Stars Catalogue (Wackerling 1970), the Catalogue of Be stars (Jaschek & Egret 1982), the H-alpha Stars in the Northern Milky Way Catalogue (Kohoutek & Wehmeyer 1997), and the Catalog of Galactic OB Stars (Reed 2003), for early-type and emission stars. No stars were found in any catalogue. The only massive star located nearby is, as mentioned by Cichowolski et al. (2001), an OB star, which has an uncertain spectral type and no distance estimate (Stock, Nassau & Stephenson 1960). It is located in projection not in the centre of the structure but on to the shell (there is a second OB star mentioned by Cichowolski et al. 2001 but its location is actually outside the structure, see fig. 1 of Cichowolski et al. 2001). Although we cannot completely rule out the possibility that the OB star may be playing a role in creating the shell structure, we think that the action of WR 130 is sufficient and most likely dominant in the region.

2020AandA...641A.139D__Dvorak_et_al._(2015)_Instance_1

The use of N-body simulations that include fragmentation allows us to perform a more detailed study of the final composition of the planets formed. In particular, we can study the water loss and/or accretion of the final planets more realistically than in the classic models of accretion. Marcus et al. (2010) presented two empirical models for the mantle stripping in differentiated planetary embryos after a collision. The authors set a simple planet structure of two layers, assuming differentiation in core and mantle, where the mantle could be composed by silicate or ice. In this work, the authors concluded that the more energetic the collision, the more mass from the mantle is lost. Therefore, for violent collisions, water could be more easily removed. Dvorak et al. (2015) performed SPH (smoothed particle hydrodynamics) simulations and studied water loss in planetary embryos and water retained in significant fragments after a collision. They concluded that the impact velocity and the impact angle play a key role in the water loss of a planetary embryo after a collision. The investigations developed by Marcus et al. (2010) and Dvorak et al. (2015) suggest that incorporating a realistic model of volatile transport and removal in an N-body code, may lead to reduced water contents on the resulting terrestrial-like planets, in comparison with those derived from classical models that assume perfect mergers. Burger et al. (2018) studied the volatile loss and transfer. The authors focused on hit-and-run encounters using SPH simulations. They concluded that the cumulative effect of several hit-and-run collisions could efficiently strip off volatile layers of protoplanets. Driven by this, Dugaro et al. (2019) studied the water delivery in planets formed in the habitable zone (HZ), using the mantle stripping models derived by Marcus et al. (2010) in their N-body simulationswith fragmentation. The authors showed that fragmentation is not a barrier for the surviving of water worlds in the HZ, and fragments may be important in the final water content of the potentially habitable terrestrial planets formed in situ.

2022MNRAS.515...22J__Newman_et_al._2013_Instance_2

In Fig. 5, we consider how the velocity dispersion profile scales with radius. Specifically, we plot the power-law index (η) versus the central velocity dispersion (σ0). The vast majority of the galaxies with σ0 ≲ 2.45 are BGGs and these have negative η values. This includes most of the Romulus galaxies (red filled and open circles), the L18 BGGs (blue crosses) and the early-type galaxies that comprise the SAURON sample (Cappellari et al. 2006; grey line and shaded area). In contrast, nearly all of simulated BGGs with σ0 ≲ 2.45) from the DIANOGA Hydro-10x simulations Marini et al. (2021) have positive η values. For σ0 ≳ 2.45, the spread of η for the observed galaxies (e.g. L18 and Newman et al. 2013 BCGs) broadens and spans both positive and negative η values. In fact, majority of the galaxies tend to have positive ηs. This change in behaviour is well known. A number of studies have noted that on the group-scale and lower, the stellar velocity dispersion profile of the central galaxies tend to decrease with increasing radius. On the cluster-scale, the BCGs typically have rising velocity dispersion profiles with increasing radius (Von Der Linden et al. 2007; Bender et al. 2015; Veale et al. 2017). The origin of this flip is still not well understood. We leave a more detailed investigation of this change to future work. Here, we simply mention two possible explanations: The change in slope may be a reflection of the differences in the dynamical state (e.g. mass-to-light ratio; M/L) at the outskirts of BCGs (Dressler 1979; Fisher, Illingworth & Franx 1995; Sembach & Tonry 1996; Carter et al. 1999; Kelson et al. 2002; Loubser et al. 2008; Newman et al. 2013; Schaller et al. 2015; Marini et al. 2021), or it could be due to increased contribution from the intragroup/intracluster light along the line-of-sight and the increased leverage of tangential orbits (Loubser et al. 2020). All of these effects are linked to the increased frequency of galaxy–galaxy interactions and more specifically, central-satellite interactions, implicated in the build-up of extended diffuse stellar component. And, as discussed by Schaye et al. (2015), Oppenheimer et al. (2021), and the EAGLE simulations clearly show that the extended stellar halo becomes increasingly more important, and hosts a non-trivial fraction of the total stellar mass towards the cluster scale.

2018AandA...610A..38F__Bisterzo_et_al._2017_Instance_1

Similarly to the [α/Fe] ratio, the ratio of the slow (s-) neutron capture process elements to iron can be regarded as a cosmic clock. Ba, Sr, La, and Y are mainly s-process elements produced on long timescales by low mass AGB stars (Matteucci 2012). Since a low mass star must evolve to the AGB phase before the s-process can occur, the s-process elements are characterized by a delay in the production, much like the delay of iron production by SNe Ia relative to the α elements production by core collapse SNe. Among the four s-process elements mentioned above, GES provides the abundances of Y II (the first s-process peak element) and Ba II (the second s-process peak element) for all our sample stars. Their abundances behave differently in the Galactic thick and thin discs (Bensby et al. 2005, 2014; Israelian et al. 2014; Bisterzo et al. 2017; Delgado Mena et al. 2017). Unlike the Galactic thick disc stars, which show an almost constant [Ba/Fe] abundance close to the solar value, the Galactic thin disc stars have their [Ba/Fe] abundances increasing with [Fe/H] and reaching their maximum values around solar metallicity, after which a clear decline is seen (see also Cristallo et al. 2015a,b, for the most recent s-process calculation in AGB yields). The same trend is observed in our sample. In Fig. 13 we display the Li-[Ba/Fe], [Ba/Fe] as a function of [Fe/H], and the evolution of absolute Ba abundance A(Ba), as derived from Ba II lines. Similar figures are also plotted for yttrium (Y II). [Ba/Fe] and [Y/Fe] values here are derived from MCMC simulations, taking into account the measurement uncertainties of A(Ba II)/A(Y II) and [Fe/H]. By applying the same MCMC setups used for [α/Fe] (see Sect. 3.1), we calculate the mean values of [Ba/Fe] and [Y/Fe] for each star. These values, together with their corresponding 1σ uncertainties, are listed in Table 1. In the literature there are several theoretical works on the evolution of [Ba/Fe] and [Y/Fe] in the Galactic thin disc (e.g. Pagel & Tautvaisiene 1997; Travaglio et al. 1999, 2004; Cescutti et al. 2006; Maiorca et al. 2012; Bisterzo et al. 2017). For comparison, we show in Fig. 13 the predictions of the most recent one (Bisterzo et al. 2017) where the updated nuclear reaction network was used.

2021ApJ...923..106Z__Gabici_et_al._2009_Instance_1

Diffusive shock acceleration (DSA) operating at expanding shock waves of supernova remnants (SNRs) is widely believed to be the mechanism converting the kinetic energy released by supernova explosions into the energy of cosmic rays (CRs) (e.g., Malkov & Drury 2001). In the DSA theory, CRs being accelerated at shocks must be scattered by self-generated magnetic turbulence. Since the highest-energy CRs in the shock precursor are prone to lack self-generated turbulence, they are expected to escape the shock. The DSA theory generally predicts that a substantial fraction of the shock energy is carried away by escaping CRs. In the presence of molecular clouds surrounding the SNR, escaping CRs can illuminate the clouds through pp interactions, producing gamma-ray emission with a flux depending on the amount of nuclear CRs released by an SNR and the diffusion coefficient in the interstellar medium (ISM; Aharonian & Atoyan 1996; Aharonian et al. 2004; Rodriguez Marrero et al. 2008; Gabici et al. 2009). High Energy Stereoscopic System (H.E.S.S.) observations reveal a complex of sources (HESS J1800-240A, B, and C) ∼0.5° south of the SNR W28, coincident with molecular clouds in the field, and the Large Area Telescope (LAT) on board the Fermi satellite reveals a similar structure in gigaelectronvolt energies (Abdo et al. 2010; Hanabata et al. 2014). The gigaelectronvolt–teraelectronvolt gamma-ray emission around W28 can be regarded as a realization of this scenario (Aharonian et al. 2008). Another example is the detection of two extended gamma-ray structures located at two opposite edges of SNR W44 by Fermi-LAT (Uchiyama et al. 2012; Peron et al. 2020). The gamma-ray emission coincides with the molecular cloud complex that surrounds SNR W44. The gamma-ray emission that appears to come from the surrounding molecular cloud complex can be ascribed to the CRs that have escaped from W44. The total kinetic energy channeled into the escaping CRs is estimated to be larger than a few 1049 erg in both W28 and W44, although the exact number depends on the value of the diffusion coefficient of escaping CRs.

2019AandA...622A.106M__Maddox_et_al._2018_Instance_1

The standard single-frequency detection methods for point sources in the CMB and far IR are based on wavelet techniques (Vielva et al. 2003; Barnard et al. 2004; González-Nuevo et al. 2006) or on the matched filter (or MF hereafter, Tegmark & de Oliveira-Costa 1998; Herranz et al. 2002; Barreiro et al. 2003; López-Caniego et al. 2006, see also Herranz & Vielva 2010 for a review.). Wavelets are well suited for the detection of compact sources due to their good position-scale determination properties, whereas the MF is the optimal linear detector-estimator because it provides the maximum signal-to-noise (S/N) amplification for a source with a known shape (usually the point-spread function, or PSF hereafter, of the telescope) embedded in statistically homogeneous and spatially correlated noise. By default, these techniques are applicable only to single-frequency sky images: even for multiwavelength observatories such as the Herschel Space Observatory (Pilbratt et al. 2010) or Planck (Tauber et al. 2010), the standard detection pipelines have produced individual source catalogs for each frequency band (see e.g., Planck Collaboration VII 2011; Planck Collaboration XXVIII 2014; Planck Collaboration XXVI 2016; Maddox et al. 2018). The next logical step is to boost the signal of faint sources by combining the different bands into a single detection, that is, “multifrequency detection”. Most of the blind component separation algorithms that are used for diffuse components in microwave and far IR astronomy can not deal with the high diversity of spectral behaviors associated to the different populations of extragalactic compact sources (see for example Leach et al. 2008). However, over the last few years a number of multifrequency compact source detection techniques have been proposed in the literature (Herranz & Sanz 2008; Herranz et al. 2009; Lanz et al. 2010, 2013; Planck Collaboration Int. LIV 2018). A review on the topic can be found in Herranz et al. (2012). In particular, if the spatial profile and the spectral energy distribution (SED) of the sources are known, and if the cross-power spectrum is known, or can be estimated from the data, the optimal linear detection method is the matched multifilter (or MMF hereafter, Herranz et al. 2002). Lanz et al. (2010) also showed that the MMF can be generalized for the case where the SED of the sources is not known. This generalization outperforms the single-frequency MF in terms of S/N and can be used to infer the spectral index of synchrotron-dominated radio sources, as shown in Lanz et al. (2013). However, in this paper we will incorporate a specific SED to the MMF in order to derive a photometric redshift estimation of dusty galaxies and high-redshift star forming galaxies detected in the IR part of the spectrum1. We will do so by applying the multifrequency MMF filter to the first and second data releases of the Herschel Astrophysical Terahertz Large Area Survey (the Herschel-ATLAS or H-ATLAS, Eales et al. 2010), the largest single key project carried out in open time with the Herschel Space Observatory. We restrict our multifrequency analysis to the three wavelength bands covered by the SPIRE instrument aboard Herschel (Griffin et al. 2010), centered around 250, 350 and 500 μm. As discussed in Hopwood et al. (2010), Lapi et al. (2011), González-Nuevo et al. (2012), Pearson et al. (2013) and Donevski et al. (2018), the SPIRE bands are ideal for capturing the peak in the SED corresponding to dust emission of star-forming galaxies at z ∼ 2, that is redshifted from its rest-frame wavelength around 70–100 μm to the SPIRE wavelengths: This is the redshift range where galaxies have formed most of their stars. At higher redshifts, dusty star-forming galaxies (DSFGs) occupy the most massive halos and are among the most luminous objects found at z ≳ 4 (Michałowski et al. 2014; Oteo et al. 2016; Ikarashi et al. 2017). These high-redshift DSFGs have markedly red colors as seen by SPIRE, with rising flux densities from 250 to 500 μm (the so-called “500 μm-risers”), and have received a great deal of attention in the recent years (see for example Ivison et al. 2016; Negrello et al. 2017; Strandet et al. 2017). The DSFGs, and particularly the 500 μm risers uncovered by Herschel, are providing much insight into the early star forming history of the universe. However, sensitivity and limited angular resolution severely constrain the power of this type of objects as astrophysical probes. The sensitivity of SPIRE allows for the direct detection of only the brightest, and thus rarest objects, at the bright end of the luminosity function. By means of our multifrequency MMF technique, we intend to enhance the detectability and statistical significance of very faint red objects in the H-ATLAS source catalog and so expand the list of reliable 500 μm-riser candidates.

2018ApJ...858...91Y__Leroy_et_al._2008_Instance_1

Our spectroscopic coverage includes the damped Lyα absorption (DLA) feature from neutral hydrogen. Analysis of this feature is complicated by blending between the host and the companion, as well as uncertainties in the continuum modeling, and it is difficult to constrain the individual contributions of the two component systems to the overall line. Modeling the line as two separate, blended Voigt profiles, we can robustly constrain the total column density of the two systems together to 5 × 1019 cm−2 ≤ N(H i) ≤ 9 × 1019 cm−2; our best-fit estimate is (6.7 ± 1.2) × 1019 cm−2, making the system technically a sub-DLA (Péroux et al. 2003). This spread in N(H i) is due to uncertainties in the relative contributions of the two systems and continuum placement. The derived N(H i) is an order of magnitude less than a typical value through a disk of a spiral galaxy with stellar mass >1010 M⊙, measured by The H i Nearby Galaxy Survey (THINGS; Walter et al. 2008; Leroy et al. 2008). This result has two implications. One is that SN2017egm may have exploded on the near side of the galaxy, where there is less neutral H i material along the line of sight. One may argue for the second possibility that UV fluxes from the SN explosion could photoionize a large fraction of neutral H i in the disk of NGC 3191, and SN2017egm could be anywhere in the disk. To validate this hypothesis, we calculate the time required, tphot, to photoionize N(H i) ∼ 1021 cm−2 over a scale height R of an H i disk. H i-ionizing flux, JUV, at the time of SN explosion is poorly constrained by observation. Let us take JUV as a fraction of fUV of the peak bolometric luminosity (Lbol); thus we have . The Milky Way thin disk (stellar) has a scale height of 100 pc.7 7 The H i gas can be more extended (Marasco & Fraternali 2011). As the most conservative assumption, let us take R = 50 pc if the SN is at the mid-plane; thus we have cm−2 s−1. In this equation, without any knowledge of the early-time UV fluxes from SN 2017egm, we assume it is only 10% of the estimated bolometric luminosity (fUV = 0.01). Here, the maximum Lbol is 2 × 1044 erg s−1. To photoionize a column of 1021 cm−2 H i atoms, we need the same number of H i-ionizing photons, thus, over a timescale of tphot, we have JUVtphot ≃ 1021 cm−2, leading to tphot = 3 × 109 s. This is two orders of magnitude longer than the time lag between the explosion and the HST spectroscopy date for SN2017egm. Since , a larger fUV value will shorten the photoionization timescale tphot by a factor of a few, but not enough to change our conclusion. This result suggests that photoionization due to the SN explosion is probably localized within a 5 pc region.

2021MNRAS.503.3279S__Magrini_et_al._2017_Instance_1

Among the several features, the distribution of chemical elements across the Galactic disc historically constitutes the most important constraint to chemo-dynamical models of our Milky Way. A number of studies (e.g. Tosi 1988; Hayden et al. 2014, 2015; Anders et al. 2017) have shown the spatial distributions of chemical abundances and their ratios across the Galactic disc. However, these studies are mainly based on field stars, which also include very old populations that had time to migrate significantly and redistribute the chemical elements across the Galaxy (e.g. Sellwood & Binney 2002; Roškar et al. 2012; Martinez-Medina et al. 2016). Open clusters are a valuable alternative, being on average younger (Magrini et al. 2017), and therefore a better tracer of the gradients in the disc out of which the most recent stars formed. Since the work of Janes (1979), much observational evidence has established that the metallicity distribution (often abbreviated by the iron-to-hydrogen ratio [Fe/H]) traced by clusters throughout the Milky Way disc shows a significant decrease with increasing distance from the Galactic Centre. This ‘radial metallicity gradient’ – in its apparent simplicity – reflects a complex interplay between several processes that are driving the evolution of our Galaxy, including star formation, stellar evolution, stellar migration, gas flows, and cluster disruption (Cunha & Lambert 1992, 1994; Friel 1995; Stahler & Palla 2004; Carraro et al. 2006; Boesgaard, Jensen & Deliyannis 2009; Magrini et al. 2009; Frinchaboy et al. 2013; Netopil et al. 2016; Anders et al. 2017; Spina et al. 2017; Bertelli Motta et al. 2018; Quillen et al. 2018). Complementary to the study of the overall metallicity distribution, the abundance ratios of several other elements, such as α-elements, iron peak, odd-z, and neutron capture, can provide deep insight into the variety of nucleosynthesis processes, with their production sites and time-scales (e.g. Carrera & Pancino 2011; Ting et al. 2012; Reddy, Lambert & Giridhar 2016; Duffau et al. 2017; Magrini et al. 2017, 2018; Donor et al. 2020; Casamiquela et al. 2020). Therefore, understanding the distribution of metals traced by clusters across the Galactic disc is fundamental for explaining the birth, life, and death of both stars and clusters, the recent evolution of our own Milky Way, and the evolution of other spiral galaxies (Boissier & Prantzos 2000; Bresolin 2019).

2020ApJ...895..128M__Zaldarriaga_et_al._2018_Instance_2

We analyze the 10 BBH mergers reported by LIGO and Virgo in their O1 and O2 observing runs (Abbott et al. 2019a; LIGO Scientific Collaboration & Virgo Collaboration 2019). Before discussing results, it is useful to review expectations from the literature for the spin distributions resulting from different formation scenarios. Isolated binary evolution is predicted to yield black holes with spins preferentially aligned with their orbit. Although spin misalignments may be introduced by natal supernova kicks, episodes of mass transfer and tidal torques serve to realign component spins before the formation of the final black hole binary (Rodriguez et al. 2016; Zevin et al. 2017; Gerosa et al. 2018; Qin et al. 2018; Zaldarriaga et al. 2018; Bavera et al. 2020). The black holes’ spin magnitudes in this scenario are much more uncertain. Recent work indicates that angular momentum is efficiently transported away from stellar cores, leaving black holes with natal spins as low as a ∼ 10−2 (Qin et al. 2018; Fuller & Ma 2019). While tides on the progenitor of the second-born black hole can spin up the progenitor star (Zaldarriaga et al. 2018), this effect can be counteracted by mass loss in stellar winds, and more detailed simulations find only low or moderate spin increases due to tides (Qin et al. 2018; Bavera et al. 2020). Meanwhile, dynamically formed systems in dense stellar clusters have no a priori preferred axis, and so are likely to have random spin configurations (Rodriguez et al. 2016, 2018, 2019; Doctor et al. 2020). Once again, however, the expected spin magnitudes are largely unknown, subject to the same uncertainties mentioned above regarding natal black hole spins. One firm prediction of the dynamical scenario concerns the spins of second-generation binaries, whose components were themselves formed from previous mergers. Regardless of their component spins, black hole mergers generally yield remnants with a ∼ 0.7; thus the effective spin of two such second-generation binaries may be large (Fishbach et al. 2017; Gerosa & Berti 2017; Rodriguez et al. 2018, 2019; Doctor et al. 2020).

2015MNRAS.450..630S__Chung_et_al._2010_Instance_1

Many studies often have environmental classes simply divided into (relaxed) ‘clusters’ or ‘fields’. However, in a Λ cold dark matter (ΛCDM) Universe, most clusters are expected to be the result of group/smaller cluster mergers – some of which can be extremely violent. Little is known about the role of cluster and group mergers in galaxy formation and evolution, and whether they could be important in setting the environmental trends which have now been robustly measured and described. It is particularly important to understand if cluster mergers trigger star formation (e.g. Miller & Owen 2003; Ferrari et al. 2005; Owen et al. 2005; Hwang & Lee 2009; Wegner, Chu & Hwang 2015), if they quench it (e.g. Poggianti et al. 2004), or, alternatively, if they have no direct effect (e.g. Chung et al. 2010). Results from Umeda et al. (2004), studying a merging cluster at z ∼ 0.2 (Abell 521) found tentative evidence that merging clusters could perhaps trigger star formation. More recently, Stroe et al. (2014a) conducted a wide field Hα narrow-band survey over two merging clusters with a simple geometry, with the merger happening in the plane of the sky. Stroe et al. (2014a) find a strong boost in the normalization of the Hα luminosity function of the CIZA J2242.8+5301 (‘Sausage’) cluster, several times above the field and other clusters. The authors suggest that they may be witnessing star formation enhancement or triggered due to the passage of the shock wave seen in the radio and X-rays. Interestingly, Stroe et al. (2014a) do not find this effect on the other similar merging cluster studied (‘Toothbrush’), likely because it is a significantly older merger (about 1 Gyr older; cf. Stroe et al. 2014a, 2015), and thus displays only the final result (an excess of post-starburst galaxies instead of Hα emitters). The results are in very good agreement with simulations by Roediger et al. (2014) and recent observational results by Pranger et al. (2014).

2015ApJ...799...42D__Roberge_et_al._2012_Instance_1

The possible presence of dust in the habitable zones of nearby main-sequence stars is considered a major threat for the direct imaging and characterization of Earth-like extrasolar planets (exo-Earths) with future dedicated space-based telescopes. Several independent studies have addressed this issue and concluded that visible to mid-infrared direct detection of exo-Earths would be seriously hampered in the presence of dust disks 10 to 20 times brighter than the solar zodiacal cloud assuming a smooth brightness distribution (e.g., Beichman et al. 2006; Defrère et al. 2010; Roberge et al. 2012). The prevalence of exozodiacal dust at such a level in the terrestrial planet region of nearby planetary systems is currently poorly constrained and must be determined to design these future space-based instruments. So far, only the bright end of the exozodi luminosity function has been measured on a statistically meaningful sample of stars (Lawler et al. 2009; Kennedy & Wyatt 2013). Based on WISE observations and extrapolating over many orders of magnitude, Kennedy & Wyatt (2013) suggest that at least 10% of gigayear-old main-sequence stars may have sufficient exozodiacal dust to cause problems for future exo-Earth imaging missions. To determine the prevalence of exozodiacal dust at the faint end of the luminosity function, NASA has funded the Keck Interferometer Nuller (KIN) and the Large Binocular Telescope Interferometer (LBTI) to carry out surveys of nearby main-sequence stars. Science observations with the KIN started in 2008 and the results were reported recently (Millan-Gabet et al. 2011; Mennesson et al. 2014). One of their analyses focused on a sample of 20 solar-type stars with no far infrared excess previously detected (i.e., no outer dust reservoir). Assuming a log-normal luminosity distribution, they derived the median level of exozodiacal dust around such stars to be below 60 times the solar value with high confidence (95%). Yet, the state-of-the-art exozodi sensitivity achieved per object by the KIN is approximately one order of magnitude larger than that required to prepare future exo-Earth imaging instruments.

2016MNRAS.455.2959D__Church_et_al._2014_Instance_1

Here, we invoke an extend accretion disc corona (ADC) model to explain the long-term time lags detected in NS-LMXBs, including the long-term time lags of GX 349+2 that we derive in this work. Analysing the dip and non-dip spectra of NS-LMXBs, Church & Bałucińska-Church (1993, 1995) proposed a Birmingham model which consists of a blackbody component interpreted as the emission from a point source, i.e. the NS, and a power-law component that might be resulted from the Comptonization of thermal emission in an ADC above the accretion disc. Through dip ingress time technique, Church & Bałucińska-Church (2004) measured the radius of the ADC and developed the Birmingham model into an extended ADC model. The measured radius of a thin, hot corona above the accretion disc varies in the range of ∼(2–70)× 104 km. Therefore, the corona is very extended and the disc is substantially covered by the corona. In the extended ADC model, almost all soft X-ray photons from the accretion disc are inversely Comptonized by the energetic electrons from the extended ADC, which produces the observed hard X-rays, while the observed soft X-rays are interpreted as the emission from the NS; the accretion disc is illuminated by the emission of the NS, leading to the production of the extended ADC above the disc. This model was successfully applied to Cyg-like Z sources (Church, Halai & Bałucińska-Church 2006; Jackson, Church & Bałucińska-Church 2009; Bałucińska-Church et al. 2010) and Sco-like Z sources (including GX 349+2) (Church et al. 2012), as well as atoll sources (Church et al. 2014), so it could be a universal model for NS-LMXBs. Since the extended ADC model is a unified model for NS-LMXBs, we try to interpret the long-term time lags in NS-LMXBs with the help of this model. The extended ADC and the NS are two independent emitting regions, which satisfies the request that the hard and soft X-rays for long-term time lags are emitted from two distant regions, as discussed above. In order to explain the long-term time lags detected in NS-LMXBs in terms of the extended ADC model, we introduce two time-scales. One is the Comptonization time-scale during which the disc seed photons are inversely Comptonized by the high-energy electrons in the extended ADC, and another is the viscous time-scale in the order of hundreds of seconds (Lei et al. 2008), during which the accreting matter flows from the disc on to the NS. The hard X-ray time lags will be produced if the Comptonization time-scale is less than the viscous time-scale, and, contrarily, the soft X-ray time lags will be observed if the Comptonization time-scale is larger than the viscous time-scale. It is noted that a minority of positively correlated short-term time lags (1 s) are listed in Tables 1 and 3, which are derived with the CCF method in our work. These short-term time lags cannot be explained by the models reviewed in section 4.1, because those models are used to interpret the short-term time lags produced in two adjacent energy intervals, while these short-term time lags obtained in this work are derived from two distant energy intervals, i.e. 2–5 kev and 16–30 keV energy intervals. In the frame of the extended ADC model, we propose that these short-term time lags will be observed under the circumstance that the Comptonization time-scale is comparable with the viscous time-scale.

2021MNRAS.500.2577K__Mathys_2017_Instance_1

The binary characteristics of early-type magnetic stars may provide crucial clues, allowing one to test alternative fossil field hypotheses. The non-magnetic chemically peculiar stars of Am (A-type stars with enhanced lines of Fe-peak elements) and HgMn (late-B stars identified by strong lines of Hg and/or Mn) types are frequently found in close binaries (Gerbaldi, Floquet & Hauck 1985; Ryabchikova 1998; Carquillat & Prieur 2007), including eclipsing systems (Nordstrom & Johansen 1994; Strassmeier et al. 2017; Takeda et al. 2019). In contrast, only about ten close (Porb 20 d) spectroscopic binaries containing at least one magnetic ApBp star are known (Landstreet et al. 2017). The overall incidence rate of magnetic upper main sequence stars in close binaries is less than 2 per cent (Alecian et al. 2015), although this fraction is significantly higher if one includes wide long-period systems (Mathys 2017). This low incidence of magnetic ApBp stars in close binaries is frequently considered as an argument in favour of the stellar merger origin of fossil fields (de Mink et al. 2014; Schneider et al. 2016). In this context, confirmation of magnetic ApBp stars in short-period binary systems gives support to alternative theories or, at least, demonstrates that early-type stars may acquire magnetic fields through different channels. In addition, detached close binary stars, particularly those showing eclipses, are valuable astrophysical laboratories that provide model-independent stellar parameters and allow one to study pairs of co-evolving stars formed in the same environment. Until recently, no early-type magnetic stars in eclipsing binaries were known. The first such system, HD 66051, was identified by Kochukhov et al. (2018). The second system, HD 62658 containing twin components of which only one is magnetic, was found by Shultz et al. (2019). Several other eclipsing binaries containing candidate ApBp stars were proposed (Hensberge et al. 2007; González, Hubrig & Castelli 2010; Skarka et al. 2019), but the magnetic nature of these stars has not been verified by direct detections of their fields using the Zeeman effect. In this paper, we put a spotlight on another candidate eclipsing magnetic Bp star, which received little attention prior to our work despite being significantly brighter than the confirmed magnetic eclipsing systems HD 62658 and HD 66051.

2021MNRAS.506.5836R__Lyne_&_Manchester_1988_Instance_1

Below, we describe a simple emission model that can explain most of the key emission features of the pulsars presented in this paper. It draws significantly from the model proposed in Timokhin (2010) that explains nulling and mode changing in pulsars by shrinking and expanding the magnetosphere of the neutron star. The model assumes a dipole magnetic field line structure and a schematic diagram is shown in Fig. 10. The emission beam is assumed to be a ‘fan beam’ with multiple flux tubes along the open field lines (Karastergiou & Johnston 2007; Oswald, Karastergiou & Johnston 2019). We assume the fan beam to be “patchy” and partially filled meaning that only a portion of the tube is emitting radiation. The patchy beam scenario is one of the common beam models that has been used to explain the emission properties of pulsars (see Lyne & Manchester 1988; Manchester et al. 2010). As shown in Fig. 10, it is assumed that the emission patch is fixed within the polar cap region, i.e. the region consists of open magnetic field lines with respect to the boundary of the comoving magnetosphere (known as the light cylinder). When the magnetosphere shrinks the polar cap region expands accordingly with the dipole field lines and changes the orientation of the emission flux tube produced from the patchy region (see Fig. 10b). Due to these changes, our line of sight (LoS) encounters a different part of the flux tube, resulting in variation in the observed pulse profile shape, switching the pulsar from the normal to swoosh emission. It has been postulated that low-frequency radio emission is produced at a higher altitude compared to the high-frequency emission in the magnetosphere (i.e. – RFM, Cordes 1978; Oswald et al. 2019). Therefore, due to the curvature of the dipole magnetic field lines, the flux tube of the patchy beam at a lower frequency can be oriented in a direction that is out of our LoS (see Fig. 10b). This results in apparent nulls at low frequencies, which is consistent with the observations of PSR B0919+06 (see Fig. 1, and also Shaifullah et al. 2018).

2020MNRAS.497...52H__Sereno_&_Umetsu_2011_Instance_1

In Fig. 11, we compared the WL-derived masses (MWL) with those derived from the dynamical analysis (Mdyn) and listed in Table 1. The dynamical masses were computed under the assumption of the singular isothermal model and velocity dispersions (Haines et al. 2018). We obtained the WL masses for the four massive clusters (A 3556, A 3558, A 3560, and A 3562) with the MCMC method. On the other hand, we only gave the upper limit of the masses for six out of seven low-mass clusters due to the large shape noise in the WL analysis. In the figure, we labelled the low-mass clusters as black crosses, AS 0726 as black box and the four massive clusters as cyan circles. For AS 0726, we only indicatively adopted the average mass for the low-mass clusters derived using the stacked shear profile. We notice that (i) the masses obtained from the dynamical and WL analysis are consistent within 1σ for all clusters except A 3554, A 3558, and AS 0726; (ii) the dynamical masses turn out to be systematically higher than the WL-derived ones. Previous studies showed that WL masses obtained from the tangential shear fitting were biased low up to 10 per cent with a scatter of ∼25 per cent (Oguri et al. 2005; Sereno & Umetsu 2011; Sereno & Ettori 2015). The main source of the bias are due to substructures and triaxiality. When a cluster whose major axis is perpendicular to the line of sight, i.e elongated in the sky-plane, a mass obtained with the spherical NFW profile is typically underestimated. The presence of substructures around clusters and uncorrelated large-scale structures along the line of sight also generate the biases for the estimation of the WL masses (Meneghetti et al. 2010; Becker & Kravtsov 2011; Giocoli et al. 2012, 2014). In addition, we point out that the dynamical mass of AS 0726 is actually an upper limit since the velocity distribution of member galaxies is strongly bimodal, and certainly not Gaussian (see fig. 14 in Haines et al. 2018). This system probably consists of two groups with velocity dispersions ∼300 km s−1 rather than one single system with σ ∼600 km s−1. This would reduce the mass estimate by a factor of 4. The complex structure of A 3558 and, in general, the dynamical activity in the SSC core (see Bardelli et al. 1998; Ettori et al. 2000; Finoguenov et al. 2004; Rossetti et al. 2007a) may explain the systematic differences between the two mass determinations quoted above, since the virial mass tends to overestimate the mass of unrelaxed clusters. Moreover, Rossetti et al. (2007b) studied A 3558 with an X-ray observation and showed the possibility of the presence of substructures along the line of sight, which interact with the cluster. Since such structures along the line of sight broaden velocity distribution, masses obtained from the dynamical analysis can be overestimated up to 100 per cent (Takizawa, Nagino & Matsushita 2010; Pratt et al. 2019). Fig. 14 in Haines et al. (2018) showed the broad velocity distribution of galaxies for the cluster. This indicates the presence of the substructures along the line of sight and the possibility for overestimating the dynamical mass. A 3554 also shows strong substructures in the velocity distribution diagram.

2020AandA...637A..59A__Massalkhi_et_al._2019_Instance_1

Silicon monoxide (SiO) is predicted to be the most abundant Si-bearing molecule in the entire 1–10 R* range in the atmospheres of M stars. In S-type atmospheres, the calculated abundance of SiO decreases by two orders of magnitude in the 1–5 R* but retains a very high abundance beyond, and the same occurs in C-rich atmospheres, although in this case, the abundance drop in the 1–5 R* is even more pronounced (see Fig. 2; see also Agúndez & Cernicharo 2006). Observations indicate that the abundance of SiO does not differ significantly between envelopes around M-, S-, and C-type stars, although in all them the SiO abundance decreases with increasing mass-loss rate (González Delgado et al. 2003; Schöier et al. 2006; Ramstedt et al. 2009; Massalkhi et al. 2019, 2020). This decline in the SiO abundance with increasing envelope density is not a consequence of chemical equilibrium (Massalkhi et al. 2019), but has been interpreted as evidence that SiO disappears from the gas phase at high densities to be incorporated into dust grains (González Delgado et al. 2003; Schöier et al. 2006; Ramstedt et al. 2009; Massalkhi et al. 2019, 2020). It therefore appears that the gradual abundance decline calculated for SiO in the 1–5 R* region from stellar type in the sense M → S → C does not have a direct consequence in the SiO abundance that is injected into the expanding wind. However, this behavior predicted by chemical equilibrium probably explains why SiO masers are observed in M-type stars but not toward carbon stars (e.g., Pardo et al. 2004). Except for these details, chemical equilibrium and observations agree in the fact that SiO is one of the most abundant carriers of silicon in the atmospheres of M-, S-, and C-type stars. Calculations and observations also agree for SiS in that it is an abundant molecule regardless of the C/O. However, observations indicate a differentiation between C- and O-rich envelopes, with SiS being on average one order of magnitude more abundant in carbon-rich sources (Schöier et al. 2007; Danilovich et al. 2018; Massalkhi et al. 2019, 2020). Moreover, in some oxygen-rich envelopes, the fractional abundance of SiS relative to H2 is as low as ~10−8, which is well below the predictions of chemical equilibrium (Danilovich et al. 2019; Massalkhi et al. 2020).

2021AandA...656A.148R__Wiel_et_al._2019_Instance_1

After the gravitational collapse and if the total mass of the individual cloud is approximately the mass of the Sun (2 × 1030 Kg; (van Dishoeck 2014), a new astrophysical system forms that is dominated gravitationally by a low-mass protostar known as a young stellar object (YSO). The protostar is in the center of the system and is surrounded by a Keplerian-rotating envelope of dust and gas, that is gravitationally connected and in which the angular momentum is conserved (Cassen & Moosman 1981). The distance to the star will define the surrounding energy, which is dominantly thermal and capable of heating the more distant dustgrain mantles. The processes progressively inject chemical constituents into the gas-phase (Ceccarelli et al. 2001)and determine what types of physical-chemical processes govern in every region of the disk. Circumstellar envelopes oflow-mass protostars (CELMP) are environments that are extraordinarily rich in organic molecules as H2CO or HNCO and in iCOMs such as CH3CN, CH3CHO, and C2 H5OH (Schöier et al. 2002), in addition to other O- and N-bearing complexes (Jørgensen et al. 2012). IRAS 16293-2422 (hereafter IRAS 16293) was chosen for this work as the quintessential example of such an object. IRAS 16293 is adequate for this role because formaldehyde has previously been detected with notable variations in abundances in three differentiated regions of its protodisk (Ceccarelli et al. 2001; Jørgensen et al. 2012; Jaber et al. 2014; van der Wiel et al. 2019). Additionally, glycolaldehyde (C2 H4O2), the simplest form of sugar and one of the first intermediates in the formose reaction (Larralde et al. 1995), has also been detected in this object for the first time in space in 2012 (Jørgensen et al. 2012). The more distant regions of the disk (>4000 AU) contain species such as CO, H2CO, CH3OH, or H2O (van Dishoeck et al. 1995) at low temperatures (10–20 K) where the gas is slightly warmer than the dust grains as they are tightly coupled to them. Energy from collisions among dust and gas is therefore considered to be the main heating mechanism in this region. Nevertheless, the thermal energy generated by those collisions is not enough to activate the formation of molecules with barriers at or below 20 K (0.0397 kcal mol−1). The gas column density of molecular hydrogen has been estimated to be N(H2) = 1.3 × 1023 cm−2 (Ward-Thompson et al. 1999), with a fractional abundance of formaldehyde – N(H2CO)/N(H2) – ~ 4 × 10−10 cm−3 in the gas-phase (Ceccarelli et al. 2001). When the temperature rises above ~ 20 K, CO starts to desorb from the ice grains and enters the gas-phase with an increase of ~ 103 cm−3 in detected densities with respectto H2 (Cassen & Moosman 1981; Aikawa et al. 2015). Formaldehyde starts to deplete from frozen grains at around ~ 40 K and it is fully desorbed at ~ 60 K (Ceccarelli et al. 2001). The additional H2CO mixes with the existing circumstellar mass of gas, which may justify why at ~ 700 AU from the core and at gas temperatures between 80 and 100 K ~ 50 kcal mol−1), the detected fractional abundances of formaldehyde reach N(H2CO)/N(H2) = ~ 4.0 × 10−9 cm−3 (Ceccarelli et al. 2001). This implies an H2 column density that is estimated to be N(H2) = ~ 5.0 × 1021 cm−2 (Bottinelli et al. 2014). The inner part of the envelope at ~ 150 AU in a region with temperatures of 100–150 K has a higher density of formaldehyde with an N(H2CO)/N(H2) of ~ 10 × 10−7 cm−3, as well as an increase in fractional abundances for H2O (which desorbs from iced mantles at ~80 K) (Ceccarelli et al. 2001). This region also produces new molecules principally due to the thermal energy emitted from the YSO (99.99 kcal mol−1). One example is trans-HONO. This chemical compound has recently been detected for first time in space and in this part of the disk (Coutens et al. 2019). Its proposed formation has inspired some reactions proposed in this work that may lead to H2CO. In this region, a column density for molecular hydrogen is considered like that in region II (N(H2) = ~ 5.0 × 1021 cm−2). The three regions of IRAS 16293 dictate the physical parameters for the presentation of our computations which are defined as follows: Region I/d ~ 4000 AU, Tgas = 20 K, Pgas = 2.29 × 107 K cm−3; Region II/d~ 700 AU, Tgas = 80 K, Pgas = 7.06 × 107 K cm−3; Region III/d~150 AU, Tgas = 150 K, Pgas = 6.08 × 108 K cm−3.

2021MNRAS.500.5009M__Criscienzo_et_al._2006_Instance_1

RR Lyrae are old low-mass stars that, during the central helium-burning phase, show mainly radial pulsation while crossing the classical instability strip in the colour–magnitude diagram. From the observational point of view, they represent the most numerous class of pulsating stars in the Milky Way and, being associated with old stellar populations, are typically found in globular cluster and abundant in the Galactic halo and bulge. The investigation of RR Lyrae properties is motivated by their important role both as distance indicators and tracers of old stellar populations. In particular, evolving through the central helium-burning phase, they represent the low-mass, Population II counterparts of Classical Cepheids, as powerful standard candles and calibrators of secondary distance indicators. In particular, they can be safely adopted to infer distances to Galactic globular clusters (see e.g. Coppola et al. 2011; Braga et al. 2016, 2018, and references therein), the Galactic centre (see e.g. Contreras Ramos et al. 2018; Marconi & Minniti 2018; Griv, Gedalin & Jiang 2019), and Milky Way satellite galaxies (see e.g. Coppola et al. 2015; Martínez-Vázquez et al. 2019; Vivas et al. 2019, and references therein). Being associated with old stellar populations, they represent the basis of an alternative Population II distance scale (see e.g. Beaton et al. 2016, to the traditionally adopted Classical Cepheids), more suitable to calibrate secondary distance indicators that are not specifically associated with spiral galaxies (e.g. the globular cluster luminosity function, see Di Criscienzo et al. 2006, and references therein). The properties that make RR Lyrae standard candles are (i) the well-known relation connecting the absolute visual magnitude MV to the metal abundance [Fe/H] (see e.g. Sandage 1993; Caputo et al. 2000; Cacciari & Clementini 2003; Catelan, Pritzl & Smith 2004; Di Criscienzo, Marconi & Caputo 2004; Federici et al. 2012; Marconi 2012; Marconi et al. 2015, 2018; Muraveva et al. 2018, and references therein); (ii) the period–luminosity relation in the near-infrared (NIR) filters and in particular in the K 2.2 μm band (see e.g. Longmore et al. 1990; Bono et al. 2003; Dall’Ora et al. 2006; Coppola et al. 2011; Ripepi et al. 2012; Coppola et al. 2015; Marconi et al. 2015; Muraveva et al. 2015; Braga et al. 2018; Marconi et al. 2018, and references therein). In spite of the well-known advantage of using NIR filters (see e.g. Marconi 2012; Coppola et al. 2015, and references therein), in the last decades there has been a debate on the coefficient of the metallicity term of the KB and PL relation (see e.g. Bono et al. 2003; Sollima, Cacciari & Valenti 2006; Marconi et al. 2015, and references therein). On the other hand, it is interesting to note that many recent determinations (see e.g. Sesar et al. 2017; Muraveva et al. 2018) seem to converge towards the predicted coefficient by Marconi et al. (2015), with values in the range 0.16-0.18 mag dex−1. As for the optical bands, our recently developed theoretical scenario (Marconi et al. 2015) showed that, apart from the MV−[Fe/H] relation that is affected by a number of uncertainties (e.g. a possible non-linearity, the metallicity scale with the associated α elements enhancement and helium abundance variations, as well as evolutionary effects, see Caputo et al. 2000; Marconi et al. 2018, for a discussion), the metal-dependent Period–Wesenheit (PW) relations are predicted to be sound tools to infer individual distances. In particular, for the B-, V- band combination, Marconi et al. (2015) demonstrated that the inferred PW relation is independent of metallicity. In order to test this theoretical tool, we need to compare the predicted individual distances with independent reliable distance estimates, for example, the astrometric ones recently obtained by the Gaia satellite (Gaia Collaboration 2016). To this purpose, in this paper we transform the predicted light curves derived for RR Lyrae models with a wide range of chemical compositions (Marconi et al. 2015, 2018) into the Gaia bands, derive the first theoretical PW relations in these filters and apply them to Gaia Data Release 2 Data base (hereinafter Gaia DR2; Gaia Collaboration 2018; Clementini et al. 2019; Ripepi et al. 2019). The organization of the paper is detailed in the following. In Section 2, we summarize the adopted theoretical scenario, while in Section 3 we present the first theoretical light curves in the Gaia filters. From the inferred mean magnitudes and colours, the new theoretical PW relations are derived in Section 4 that also includes a discussion of the effects of variations in the input chemical abundances. In Section 5, the obtained relations are applied to Gaia Galactic RR Lyrae with available periods, parallaxes, and mean magnitudes to infer independent predictions on their individual parallaxes, to be compared with Gaia DR2 results. The conclusions close the paper.

2016MNRAS.461..248S__Munari_et_al._2013_Instance_3

In Sifón et al. (2013), we used the σ–M200 scaling relation of Evrard et al. (2008) to estimate dynamical masses. As discussed in Section 1, the scaling relation of Evrard et al. (2008) was calibrated from a suite of N-body simulations using DM particles to estimate velocity dispersions. However, the galaxies, from which velocity measurements are made in reality do not sample the same velocity distribution as the DM particles. They feel dynamical friction and some are tidally disrupted, which distorts their velocity distribution and biases their dispersion (e.g. Carlberg 1994; Colín et al. 2000). Recent high-resolution hydrodynamical simulations of ‘zoomed’ cosmological haloes have shown that there is a significant difference between the velocity distributions of DM particles and galaxies themselves; whether galaxies (i.e. overdensities of stars in hydrodynamical simulations) or DM subhaloes are used makes comparatively little difference (Munari et al. 2013). Results from state-of-the art numerical simulations depend on the exact definition of a galaxy and the member selection applied, but the current consensus is that galaxies are biased high (i.e. at a given mass the velocity dispersion of galaxies or subhaloes is larger than that of DM particles) by 5–10 per cent with respect to DM particles (Lau et al. 2010; Munari et al. 2013; Wu et al. 2013), translating into a positive 15–20 per cent bias in dynamical masses when using DM particles. This is illustrated in Fig. 5: DM particles are not significantly impacted by either dynamical friction or baryonic physics; therefore, the scaling relations for DM particles are essentially the same for all simulations. In contrast, DM subhaloes are affected by baryons in such a way that including baryonic feedback (most importantly feedback from active galactic nuclei – AGN, but also from cooling and star formation) makes their velocity dispersions much more similar to those of simulated galaxies. This means we can rely on our analysis of the previous section, based on DM subhaloes, to correct the velocity dispersions measured for ACT clusters, and then estimate dynamical masses using predictions obtained either from galaxies or subhaloes. The difference between the Saro et al. (2013) and Munari et al. (2013) galaxy scaling relations depends on the details of the semi-analytic and hydrodynamical implementations used in Saro et al. (2013) and Munari et al. (2013), respectively. The different cosmologies used in the Millenium simulation (in particular, σ8 = 0.9; Springel et al. 2005) by Saro et al. (2013) and the simulations by (Munari et al. 2013, σ8 = 0.8) may also play a role.

2017MNRAS.469.2859S__Ramella_et_al._2002_Instance_1

The difficulty resides in the definition of ‘group’ itself. If on the simulation side, groups are well defined thanks to an access to the entire three-dimensional information, on the observational side, calling an ensemble of galaxies a group constitutes a great challenge because of a restricted access to the information. In observations, knowing precisely the fraction of collapsed material becomes quite problematic. Still several schemes have been developed to define groups within galaxy catalogues. They mainly invoke Friends of Friends (FoF) like algorithms based on projected separation, radial velocities and even luminosities to identify what are called ‘groups’ of galaxies (e.g. Huchra & Geller 1982; Geller & Huchra 1983; Ramella et al. 2002; Eke et al. 2004; Yang et al. 2005; Crook et al. 2007; Lavaux & Hudson 2011; Makarov & Karachentsev 2011; Old et al. 2014; Tempel et al. 2014; Old et al. 2015). This paper does not aim at scrutinizing in detail the methods used to group catalogues. It aims at testing two recently released versions of groups for galaxies in the local Universe to understand the differences in the reconstructions generated by two various grouping schemes as described below: Tempel et al. (2016) introduced a new grouping method (hereafter Tempel Grouping scheme). This method is based on a widely used FoF percolation method, where different linking lengths in radial (along the line of sight) and in transversal (in the plane of the sky) directions are used but the conventional FoF groups are refined using multimodality analysis. More precisely, Tempel et al. (2016) use a model-based clustering analysis to check the multimodality of groups found by the FoF algorithm and they separate nearby/merging systems. In the current paper, we use published catalogues of groups detected using this new method.Tully Grouping scheme is based on literature groups and in that respect is not a systematic scheme. Within 30 Mpc, groups are those identified by Tully (1987), further away groups are those given in the literature like Abell’s catalogue (Abell, Corwin & Olowin 1989). Recently, Tully (2015a,b) published a more systematic way of deriving groups based on radii of second turn around and iterations. After comparisons, we find that the catalogue grouped with this last scheme is an intermediate between the catalogues obtained with Tully and Tempel Grouping schemes and as such will result in more mitigated conclusions would we compare it to Tempel Grouping scheme. In addition, Tully Grouping scheme has been used so far with the second catalogue to build constrained initial conditions. We thus stick to Tully Grouping scheme in the rest of the paper.4

2022MNRAS.511.1714T__Quataert,_Jiang_&_Thompson_2022_Instance_1

Outflows present similarly confounding puzzles, e.g. the existence and survival of cool and low-ionization gas moving at high speeds in observed outflows (e.g. Veilleux, Cecil & Bland-Hawthorn 2005; Tremonti, Moustakas & Diamond-Stanic 2007; Zhang et al. 2017; Cashman et al. 2021) and high-velocity clouds (HVCs; e.g. Putman et al. 2012; Richter et al. 2017). These clouds should be shredded and destroyed before they can attain the observed velocities if they are accelerated by the ram pressure of a hot wind (e.g. Zhang et al. 2017). Possibly the material is accelerated by radiation pressure (e.g. Murray, Quataert & Thompson 2005; Murray, Ménard & Thompson 2011; Hopkins, Quataert & Murray 2012) or cosmic rays (CRs; e.g. Everett, Zweibel & Benjamin 2008; Brüggen & Scannapieco 2020; Quataert, Jiang & Thompson 2022), but alternatively the high-speed cool gas may be due rapid radiative cooling in some situations. If a cloud is sufficiently large, then mixing of the cold cloud with the hotter wind can lead to a region of mixed material with a cooling time less than the cloud-destruction time, and this cooling region can cause a cloud’s mass to grow (Armillotta, Fraternali & Marinacci 2016; Gronke & Oh 2018, 2020; Schneider, Robertson & Thompson 2018; Kanjilal, Dutta & Sharma 2021, but see caveats in S5.4 of Schneider et al. 2020). This multiphase cloud growth could explain the presence of cool gas at high speeds and the pervasive low- and high-ionization metals found in the CGM (e.g. Tumlinson et al. 2011; Werk et al. 2013; Burchett et al. 2019). Similar conclusions have been reached about inflowing gas: galactic accretion is now recognized to sometimes occur in cold, filamentary streams (Kereš et al. 2005; Dekel et al. 2009), and Mandelker et al. (2020) have shown that if a cold stream has a large enough radius, it can grow in mass due to cooling in a mixing layer. Models of HVCs moving through a galactic halo also find that the HVCs may be disrupted (or grow very little) if they are small (Heitsch & Putman 2009; Marinacci et al. 2010), but they can grow substantially if they are large enough (Fraternali et al. 2015; Gritton, Shelton & Galyardt 2017). Brüggen & Scannapieco (2016) have shown that thermal conduction, while causing evaporation, can actually extend the lifetime of cold clouds (see also Vieser & Hensler 2007 in a somewhat different context).

2015MNRAS.447.3832D__Gandhi_et_al._2008_Instance_1

GX 339-4 is a recurrent X-ray transient and the system is a confirmed black hole X-ray binary with a low-mass companion star. Although the black hole mass, the system inclination angle and distance are still unknown, they range between 5.8 and 10 M⊙ (Hynes et al. 2003; Muñoz-Darias, Casares & Martínez-Pais 2008; Shidatsu et al. 2011), 20° and 50° (Miller et al. 2006; Done & Diaz Trigo 2010; Shidatsu et al. 2011) and 6 and 15 kpc (Hynes et al. 2004; Zdziarski et al. 2004; Shidatsu et al. 2011), respectively. The source exhibits multiwavelength variability on a broad range of time-scales (Motch, Ilovaisky & Chevalier 1982; Fender, Hanson & Pooley 1999; Corbel et al. 2003, 2013; Dunn et al. 2008; Gandhi 2009; Casella et al. 2010). In addition, it also shows evidence of relativistic jets (Fender et al. 1997; Corbel et al. 2000; Markoff et al. 2003; Gandhi et al. 2008). The observations we used in this work are part of a multiwavelength study of GX 339-4 (Cadolle Bel et al. 2011; Corbel et al. 2013), and in particular of the first mid-infrared study of the source published in Gandhi et al. (2011) and obtained on 2010 March 11. GX 339-4 was observed with theWide-field Infrared Survey Explorer (WISE; Wright et al. 2010) satellite in four bands (1.36 × 1013, 2.50 × 1013, 6.52 × 1013 and 8.82 × 1013 Hz, respectively, W4, W3, W2 and W1), at 13 epochs, sampled at multiples of the satellite orbital period of 95 min and with a shortest sampling interval of 11 s, when WISE caught the source on two consecutive scans. Radio data were obtained with the Australian Telescope Compact Array during two days – close to but not simultaneous with WISE data – on 2010 March 7 and 14. The mean fluxes are 9.1 ± 0.1 and 9.7 ± 0.1 mJy at 5.5 and 9 GHz, respectively. X-ray data were quasi-simultaneous with WISE, taken between epochs 12 and 13 with the Rossi X-ray Timing Explore (RXTE) satellite. Gandhi et al. (2011) confirm the detection in the mid-infrared of a synchrotron break associated with the compact jet in GX 339-4 (Corbel & Fender 2002), and report the first clear detection of its strong variability. This detection of the jet's intrinsic variability and the overall properties of GX 339-4 make it the ideal source to test our model.

2017ApJ...839...72A__Emsellem_et_al._1994_Instance_2

We fit the radial dispersion profiles of each UCD to dynamical models using the Jeans Anisotropic Models (JAM) method with the corresponding code discussed in detail in Cappellari (2008). To briefly summarize, the dynamical models are made in a series of steps making two general assumptions: (1) the velocity ellipsoid is aligned with the cylindrical coordinate system ( R , z , ϕ ), (2) the anisotropy is constant. Here, the anisotropy is defined as β z = 1 − ( σ z / σ R ) 2 where σ z is the velocity dispersion parallel to the rotation axis and σ r is the velocity dispersion in the radial direction in the plane of the galaxy. The first step in the dynamical modeling process is to construct a three-dimensional mass model by deprojecting the two-dimensional mass model MGEs discussed in the previous section. In the self-consistent case, the luminosity and mass profile are the same. However, in our case, we used the mass profile to construct the potential and we used the light profile to calculate the observable properties of the model, both described below. The choice to parameterize the light profile with MGEs is motivated by the ease of deprojecting Gaussians and the accuracy in reproducing the surface brightness profiles (Emsellem et al. 1994; Cappellari 2002). The second step in the dynamical modeling process is to construct a gravitational potential using our mass model. This potential also contains a Gaussian to represent a supermassive BH with the axis ratio, q = 1, and width, σ ≲ r min / 3 , where rmin is the smallest distance from the BH that needs to be accurately modeled. Although a supermassive BH can be modeled by adding a Keplerian potential, it is much simpler to model the BH as this small Gaussian (Emsellem et al. 1994). Next, the MGE formalism is applied to the solution of the axisymmetric anisotropic Jeans equations (see Section 3.1.1 of Cappellari 2008). Finally, the intrinsic quantities are integrated along the LOS and convolved with the PSF from the kinematic data to generate observables that can be compared with the radially binned dispersion profiles. Supermassive BH masses are frequently measured with dynamical models that allow for fully general distribution functions (e.g., Schwarzschild), which is important to include because of the BH mass-anisotropy degeneracy in explaining central dispersion peaks in galaxies. Since plunging radial orbits have an average radius that is far from the center of the galaxy, these orbits can raise the central dispersion without significantly enhancing the central mass density. Similarly, a supermassive BH also raises the dispersion near the center of the galaxy. Other dynamical modeling techniques break this degeneracy by fitting the full orbital distribution without assumptions about the anisotropy. However, given the quality of our kinematic data, a more sophisticated dynamical modeling technique is not feasible; we further discuss the assumptions and limitations of our modeling at the beginning of Section 5.1.

2022ApJ...925..203J__Combes_et_al._2019_Instance_1

The ALMA results mentioned earlier (Alonso-Herrero et al. 2020; García-Burillo et al. 2021) add yet another scale given that the KDC contains both an r ∼ 150–200 pc molecular gas ring and an inner r 50 pc torus-like structure. This smaller nuclear disk/ring may correspond to the structure predicted by a radiation-driven fountain model, where AGN radiation feedback induces vertical gas flows that result in a geometrically thick torus (Wada 2012). This mechanism would lead to tori that are a few tens of parsec wide and are dynamic, evolving structures as proposed to interpret several recent observational studies and compilations (e.g., Ramos Almeida & Ricci 2017; Combes et al. 2019; Hönig 2019). Furthermore, Alonso-Herrero et al. (2021) analyzed high-resolution mid-IR imaging of NGC 7582 from VLT/VISIR and found both an unresolved component and an extended polar dust component. These authors argue that these observations can be interpreted with a torus+wind model, according to which IR radiation pressure creates a dusty wind component that contributes to AGN obscuration (e.g., Venanzi et al. 2020). Recent models with a realistic 3D distribution of clumpy dusty material can also reproduce polar mid-IR emission starting with a standard clumpy model, depending on the torus opening angle and scale height (Nikutta et al. 2021). Subparsec-resolution observations will be needed to better constrain torus parameters. For example, NGC 1068 observations with the GRAVITY instrument on the European Southern Observatory Very Large Telescope Interferometer revealed a thin ring with an inner radius of r = 0.24 pc, close to the sublimation radius and inconsistent with a geometrically and optically thick torus on these small scales (Gravity Collaboration et al. 2020). Future high-resolution observations of the nuclear regions of AGN hosts will augment our understanding but will likely still need to be combined with probes on a range of physical scales to establish the full picture of AGN obscuration and AGN outflows.

2020ApJ...890...89G__Bieler_et_al._2015_Instance_1

Consequently, the neutral gas measured in situ in the coma of comet 67P by the ROSINA experiment (and also MIRO, VIRITS, and Alice) on board Rosetta likely originated several tens of meters beneath the primordial surface of the comet. ROSINA observations provided evidence that this comet is formed from pristine material that has not been significantly altered after its formation in the first Myr of the solar nebula stage. The high abundance of super-volatiles like CO and CO2 (Le Roy et al. 2015), the detection of argon (Balsiger et al. 2015), of molecular nitrogen (Rubin et al. 2015), of molecular oxygen (Bieler et al. 2015), of a high D/H in HDO/H2O and D2O/HDO and HDS/H2S (Altwegg et al. 2015, 2017), and of hydrogen halides (De Keyser et al. 2017; Dhooghe et al. 2017), coupled with the low density, high porosity, and homogeneity of the nucleus (Pätzold et al. 2016) and the absence of signatures of aqueous alteration (see Capaccioni et al. 2015; Davidsson et al. 2016; Quirico et al. 2016; Bardyn et al. 2017) all indicate that comet 67P formed at low temperature and did not experience any substantial global-scale heating after its formation. This suggests that 67P is representative of the solar nebula material from which the solar system had formed. This has strong implications not only for how the measurements made in cometary environments can be used to constrain the protosolar environment but also for the contribution of comets to Earth’s composition. For instance, the measurement of the D/H isotopic ratio in 67P (Altwegg et al. 2015) suggests that comets cannot be considered as the main source of water on Earth. The discovery of significant amounts of O2 in comets (Bieler et al. 2015) was not predicted by astrochemical models and challenges our understanding of the chemistry of molecular clouds and of the protosolar nebula. However, the Jupiter-family comets (JFCs; which include 67P) are a diverse groups. Indeed, even if Giotto measurements indicate that comet 1P/Halley contains similar amounts of O2 (Rubin et al. 2015), different D/H ratios (lower than observed for 67P and compatible with the D/H ratio in the Earth’s oceans) have been measured for other JFC comets like Hartley 2 (Balsiger et al. 2015) and 46P/Wirtanen (Lis et al. 2019). The causes for this diversity may be already present at the formation of these comets or may result from a different evolution after their formation.

2022MNRAS.512.3137Z__Katz_et_al._1999_Instance_1

However, it is not straightforward to explain H2 formation in astronomical sources even when the catalytic roles of dust grains are introduced into models. Interstellar species are believed to be formed on cold grain surfaces via the so called Langmuir–Hinshelwood mechanism (Watson & Salpeter 1972; Pickles & Williams 1977; Hasegawa, Herbst & Leung 1992). To form H2, H atoms accrete on dust grains and then bind weakly with surfaces, which is known as physisorption. They can overcome the diffusion barrier and move on the grain surfaces via quantum tunnelling or thermal hopping. However, laboratory and theorectical studies showed that quantum tunnelling does not contribute much to the mobility of H atoms on silicate, carbonaceous or solid amorphous water (ASW) surfaces (Pirronello et al. 1997, 1999; Katz et al. 1999; Nyman 2021). If H atoms encounter other H atoms, then H2 molecules are formed. But H atoms can also desorb and leave grain surfaces. A hydrogen atom must reside on a grain long enough to find a partner H atom to form H2. As the dust temperature increases, the H atom desorption and diffusion rates also increase. So the temperature of grain surfaces must be sufficiently low so that an H atom can encounter another one before it desorbs. On the other hand, the temperature of grain surfaces must be high enough so that H atoms can diffuse on the grain surface. The parameter that measures how strongly species are to bound to grain surfaces is called desorption energy. It was found that if we assume a single H desorption energy in models, the dust temperature range over which efficient H2 formation occurs is narrow (6–10 K for olivine grains) (Katz et al. 1999). Moreover, it was found that the highest dust temperature at which H2 can be formed efficiently is less than 17 K (Katz et al. 1999). However, the grain surface temperature in the unshielded diffuse clouds, where hydrogen molecules are believed to be efficiently formed, is around 20 K (Li & Draine 2001).

2016ApJ...822L..10I__Imanishi_&_Dudley_2000_Instance_1

We measured the total continuum flux in the SW star-forming region (rectangular with a width of 07 in the east–west × a width of 21 in the north–south) (02h42m4059–4064, −00°00′4789–5000)J2000 to be ∼10 mJy. If this is solely due to the thermal free–free emission inside star-forming H ii-regions, then the corresponding far-infrared (40–500 μm) luminosity becomes ∼6 × 1043 (erg s−1), or there is a star formation rate of ∼3 M⊙ yr−1 (Kennicutt 1998), when Equation (1) of Nakanishi et al. (2005) is used. If dust thermal radiation contributes in some way to the continuum flux there, the estimated star formation luminosity will be smaller. Previous infrared spectroscopy failed to clearly detect the signatures of ongoing active star formation at the central few arcsec region of the NGC 1068 nucleus due to the lack of polycyclic aromatic hydrocarbon (PAH) emission features (Imanishi et al. 1997; Le Floc’h et al. 2001), which are a good probe of star formation activity (Moorwood 1986; Imanishi & Dudley 2000). It was also argued that the molecular gas properties at the NGC 1068 nucleus are dominated by AGN radiation rather than star formation (Usero et al. 2004; Garcia-Burillo et al. 2010). Thus, our continuum emission map provides a new signature for the detectable amount of star formation activity in the nuclear few arcsec region of NGC 1068, thanks to the high sensitivity of ALMA. The PAH emission flux within the nuclear 38 × 38 region in infrared spectroscopy is estimated to be 2.7 × 1040 (erg s−1) (Imanishi 2002), which corresponds to star formation-originated far-infrared luminosity with 2.7 × 1043 (erg s−1) (Mouri et al. 1990). This upper limit is apparently smaller than the above estimate but can be reconciled because (1) not all of the SW star-forming region was covered by previous infrared slit spectroscopy (Imanishi et al. 1997), (2) the estimated star formation luminosity is reduced if dust thermal radiation contributes to the observed continuum emission at ∼266 GHz, and (3) some fraction of the PAHs can potentially be destroyed by the AGN's strong X-ray radiation in the close vicinity of the AGN in NGC 1068 (Voit 1992).

2020ApJ...898...25T__Spera_et_al._2019_Instance_1

Recent detections of gravitational waves (GWs) have shown evidence for a high rate of black hole (BH)–BH and neutron star (NS)–NS mergers in the universe (Abbott et al. 2016a, 2016b, 2017a, 2017b, 2017c, 2019a; Zackay et al. 2019, 2020; Venumadhav et al. 2020). However, the proposed astrophysical pathways to mergers remain highly debated. Possible compact-object merger pathways include isolated binary evolution (Dominik et al. 2012; Kinugawa et al. 2014; Belczynski et al. 2016, 2017; Breivik et al. 2016; Giacobbo et al. 2018; Bavera et al. 2019; Spera et al. 2019) accompanied by mass transfer (Inayoshi et al. 2017a; Pavlovskii et al. 2017; van den Heuvel et al. 2017), common-envelope ejection (e.g., Paczynski 1976; Ivanova et al. 2013), envelope expansion (Tagawa et al. 2018), or chemically homogeneous evolution in a tidally distorted binary (de Mink & Mandel 2016; Mandel & de Mink 2016; Marchant et al. 2016), evolution of triple or quadruple systems (Antonini et al. 2017; Liu & Lai 2017, 2018, 2019; Silsbee & Tremaine 2017; Arca-Sedda et al. 2018; Hoang et al. 2018b; Randall & Xianyu 2018; Fragione & Kocsis 2019; Fragione et al. 2019; Michaely & Perets 2019), gravitational capture (O’Leary et al. 2009; Kocsis & Levin 2012; Gondán et al. 2018b; Rodriguez et al. 2018; Rasskazov & Kocsis 2019; Zevin et al. 2019; Samsing et al. 2020), dynamical evolution in open clusters (Banerjee 2017, 2018a, 2018b; Bouffanais et al. 2019; Kumamoto et al. 2019; Rastello et al. 2019) and dense star clusters (e.g., Portegies Zwart & McMillan 2000; O’Leary et al. 2006, 2016; Samsing et al. 2014; Ziosi et al. 2014; Mapelli 2016; Rodriguez et al. 2016a, 2016b; Askar et al. 2017; Fujii et al. 2017; di Carlo et al. 2019; Zevin et al. 2019; Zhang et al. 2019), and dynamical interaction in gas-rich nuclear regions (McKernan et al. 2012, 2014, 2018; Bellovary et al. 2016; Bartos et al. 2017; Stone et al. 2017; Leigh et al. 2018; Tagawa & Umemura 2018; Yi et al. 2018; Secunda et al. 2019; Yang et al. 2019a, 2019b; Gayathri et al. 2020; McKernan et al. 2020; Tagawa et al. 2020).

2021ApJ...923L..22A__Rosado_et_al._2015_Instance_2

Pulsar timing experiments (Sazhin 1978; Detweiler 1979) allow us to explore the low-frequency (∼1–100 nHz) part of the gravitational-wave (GW) spectrum. By measuring deviations from the expected arrival times of radio pulses from an array of millisecond pulsars, we can search for a variety of GW signals and their sources. The most promising sources in the nanohertz part of the GW spectrum are supermassive binary black holes (SMBHBs) that form via the mergers of massive galaxies. Orbiting SMBHBs produce a stochastic GW background (GWB; Lommen & Backer 2001; Jaffe & Backer 2003; Volonteri et al. 2003; Wyithe & Loeb 2003; Enoki et al. 2004; Sesana et al. 2008; McWilliams et al. 2012; Sesana 2013; Ravi et al. 2015; Rosado et al. 2015; Kelley et al. 2016; Sesana et al. 2016; Dvorkin & Barausse 2017; Kelley et al. 2017; Bonetti et al. 2018; Ryu et al. 2018), individual periodic signals or continuous waves (CWs; Sesana et al. 2009; Sesana & Vecchio 2010; Mingarelli et al. 2012; Roedig & Sesana 2012; Ravi et al. 2012, 2015; Rosado et al. 2015; Schutz & Ma 2016; Mingarelli et al. 2017; Kelley et al. 2018), and transient GW bursts (van Haasteren & Levin 2010; Cordes & Jenet 2012; Ravi et al. 2015; Madison et al. 2017; Islo et al. 2019; Bécsy & Cornish 2021). We expect to detect the GWB first, followed by detection of individual SMBHBs (Siemens et al. 2013; Rosado et al. 2015; Taylor et al. 2016; Mingarelli et al. 2017) that stand out above the GWB. Detection of GWs from SMBHBs will yield insights into galaxy mergers and evolution not possible through any other means. Other potential sources in the nanohertz band include cosmic strings (Damour & Vilenkin 2000, 2001; Berezinsky et al. 2004; Damour & Vilenkin 2005; Siemens et al. 2006, 2007; Ölmez et al. 2010; Sanidas et al. 2013; Blanco-Pillado et al. 2018; Chang & Cui 2021; Ghayour et al. 2021; Gorghetto et al. 2021; Wu et al. 2021a; Blanco-Pillado et al. 2021; Lin 2021; Chiang & Lu 2021; Lazarides et al. 2021; Chakrabortty et al. 2021; Ellis & Lewicki 2021), phase transitions in the early universe (Witten 1984; Caprini et al. 2010; Addazi et al. 2021; Arzoumanian et al. 2021; Di Bari et al.2021; Borah et al. 2021; Nakai et al. 2021; Brandenburg et al.2021; Neronov et al. 2021), and relic GWs from inflation (Starobinskiǐ 1979; Allen 1988; Lazarides et al. 2021; Ashoorioon et al. 2021; Yi & Zhu 2021; Li et al. 2021; Poletti 2021; Vagnozzi 2021; Sharma 2021), all of which would provide unique insights into high-energy and early-universe physics.

2022AandA...659A.124H__Liu_et_al._(2013b)_Instance_1

Combining different samples from various instruments at different redshifts therefore inevitably introduces ENLR size–luminosity relations with different slopes α depending on the details of target selection and analysis approaches. Slopes ranging from α = 0.22 ± 0.04 (Greene et al. 2012), α = 0.25 ± 0.02 (Liu et al. 2013b), α ∼ 0.3–0.4 (Hainline et al. 2013; Chen et al. 2019a), to α ∼ 0.5 (Bennert et al. 2002; Husemann et al. 2014) are reported in the literature. The slopes solely inferred from the CARS data are consistent with those reported by Greene et al. (2012) and Liu et al. (2013b) and are therefore on the shallower side of previous estimates. Nevertheless, the scatter in the observed relation is significant and measured slope variations might be entirely attributed to the observationally induced biases as discussed above. A slope of α = 0.5 is reminiscent of the BLR size-luminosity relation, but would require a constant ionization parameter U that demands a constant density with radius. This is not observed for the ENLR on kiloparsec scales (e.g., Bennert et al. 2006; Kakkad et al. 2018) and more detailed photoionization calculations are required to predict the shallower slopes inferred for most studies (Dempsey & Zakamska 2018). We cannot study the radial variations of U as our snapshot MUSE observations are not deep enough to map the electron density given the too low S/N of the [S II] doublet on kpc scales. However, the photoionization calculations do not take into account variable ionizing flux from AGN on 105 yr time scales (Schawinski et al. 2015) and the various geometrical intersections of the ionizing radiation field with the gas distribution of the galaxies. The CARS survey is least biased with regard to RENLR given the narrow redshift range and large dynamic range offered by MUSE (see Fig. 13). Therefore, the CARS survey is one of the best data set to explore the origin of the significant scatter in ENLR size–luminosity relation and search for additional factors or more fundamental parameters controlling the ENLR size.