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2020AandA...635A.154M__Hummels_et_al._(2017)_Instance_1

This paper presents a new 3D RT code, RAdiation SCattering in Astrophysical Simulations (RASCAS), which was designed to construct accurate multi-wavelength mock observations (spectra, images, or datacubes) from high-resolution simulations. RASCAS deploys a general two-step methodology (e.g. Hummels et al. 2017; Barrow et al. 2017). The first step consists in extracting all relevant information from the simulation outputs: (1) the information concerning the medium through which light will propagate, and (2) the information concerning the sources of radiation. Point (1), for example, determines the number density of H I atoms, their thermal velocity dispersion and bulk velocity, and the dust density, everywhere in a chosen volume. Fully coupled radiation-hydrodynamic simulations would naturally provide the information about ionised states, but retrieving this information in pure hydrodynamic simulations may be tricky. In such case, it is necessary to process the simulation outputs with additional software and models, typically with CLOUDY (Ferland et al. 2013), as in Hummels et al. (2017) and Barrow et al. (2017), or with independent codes which solve for H and He ionisation by propagating ionising radiation in post-processing (e.g. Li et al. 2008; Yajima et al. 2012). Point (2) is also involved to a greater or lesser extent, depending on the sources. Computing the continuum emission from star particles is relatively straightforward, using spectro-photometric models of stellar populations (e.g. Bruzual & Charlot 2003; Eldridge et al. 2017). However, computing the emission lines from the gas (e.g. in the Lyman-α line or in other nebular lines) again requires a detailed knowledge of the ionisation and thermal state of the emitting species. This may be provided by the simulation code, as is the case for H and He with RAMSES-RT (Rosdahl et al. 2013), or it may be necessary to post-process the simulation to estimate the emissivities of the gas. This first step is very simulation- and model-dependent, and RASCAS chooses to encapsulate it in a simulation-plugin module and to implement two stand-alone pre-processing codes which generate an adaptive mesh with all the needed physical information about the gaseous medium, and the initial conditions for light emission in the form of lists of photon packets. These datasets, which could easily be generated from other simulations with any post-processing code, serve as inputs to RASCAS to perform the radiative transfer computation.

2022AandA...663A.172M___2012_Instance_2

We note that Pavesi et al. (2019) derived a lower κs parameter log(κs) ≈ −1 for HZ10, by observing the CO(2-1) line, which implies a low star formation efficiency for this source. The conflict between the two results can be explained by the fact that Pavesi et al. (2019) estimated the gas mass by adopting a large CO-to-Mgas conversion factor αCO = 4.5 M⊙ (K km s−1 pc2)−1, a value that is close to the Galactic conversion factor αCO = 4.36 M⊙ (K km s−1 pc2)−1 (Bolatto et al. 2013). Although the Galactic conversion factor is a derived value for Milky Way and normal, star-forming galaxies in the local Universe, it may not be applicable for more extreme environments of starburst galaxies at high-z (see Carilli & Walter 2013 for a review). The conversion factor depends on the physical conditions of the gas in the ISM (temperature, surface density, dynamics, and metallicity), as well as the star formation and associated feedback (Narayanan et al. 2011, 2012; Genzel et al. 2012; Feldmann et al. 2012; Renaud et al. 2019; see, e.g., Bolatto et al. 2013 for a review). It is typically in the range between 0.8 and 4.36 M⊙ (K km s−1 pc2)−1 (see, e.g., Bolatto et al. 2013; Carilli & Walter 2013, and Combes 2018 for reviews). Low metallicities (Z = 0.6 Z⊙ for HZ10) will drive αCO towards values higher than the Galactic value (Narayanan et al. 2012; Genzel et al. 2012; Popping et al. 2014), although αCO spans a broad range of values of αCO ∼ 0.4 − 11 M⊙ (K km s−1 pc2)−1, due to large uncertainties (see, e.g., Fig. 9 of Bolatto et al. 2013). On the other hand, high values of temperature, surface density, and velocity dispersion in a turbulent ISM of starbursts and merging systems will shift αCO towards lower values (Narayanan et al. 2011, 2012; Vallini et al. 2018). HZ10 has an extremely high value of the burstiness parameter log(κs) ∼ 1.4 and high total density of the [C II] emitting gas log(n) ∼ 3.35 cm−3, and it is also a multi-component system (Jones et al. 2017, Carniani et al. 2018a). Thus, for this source we assumed αCO = 0.8 M⊙ (K km s−1 pc2)−1, usually adopted for starburst galaxies (e.g., Downes & Solomon 1998; Bolatto et al. 2013). We obtained log(κs) = 0.53 ± 0.34, which is within the 2σ uncertainties of the log ( κ s ) = 1 . 43 − 0.53 + 0.38 $ \log{(\kappa_s)} = 1.43_{-0.53}^{+0.38} $ , estimated exploiting the C III] emission and the Vallini et al. (2020) model.

2022MNRAS.511.4946N__Myers_et_al._2015_Instance_1

We validated our results against different selection effects due to redshift, luminosity, incompleteness of the FIRST survey, and incomplete radio counter-part identifications. However, we have not explicitly checked for any bias due to incomplete target selection in the DR16Q catalogue. As quasars are chosen for spectroscopic observations in SDSS primarily based on their photometric properties, our analysis can be biased due to the differential target selection completeness for BALQSOs and non-BALQSOs. As BALQSOs are significantly dust-reddened compared to non-BALQSOs, the completeness of BALQSOs is expected to be less. Allen et al. (2011) computed this difference in the selection probabilities using simulated BAL and non-BALQSO magnitudes and found that the completeness is very high for both BALQSOs and non-BALQSOs with z 2.1 and i 19.1, drops sharply for a narrow region close to z ∼ 2.6 and rises again for higher redshifts. This completeness difference can introduce some bias for analysis involving optically selected samples. To our rescue, eBOSS also targets all SDSS point sources that are within 1 arcsec of a radio detection in the FIRST point source catalogue (Myers et al. 2015). As our final sample is radio-selected BAL quasars and non-BAL quasars, we do not expect the behaviour of the BAL fraction to be severely influenced by any incompleteness effects. As with the case of dust-reddening, strong absorption troughs can make the broadband magnitude appear fainter for a BALQSO than an equivalent non-BALQSO. C iv BAL troughs fall in the SDSS i band for the redshift range 3.5 z 4.4. Our BAL quasar sample contains 82 quasars (4 per cent) in the redshift range where the i band luminosities are underestimated due to the presence of C iv BAL absorption. Additionally, a small fraction of quasars (1 per cent) should be LoBALs and FeLoBALs where the i-band luminosities are affected by Mg ii, Al iii, and Fe ii broad absorption. The orientation indicator, radio-to-optical core luminosity has the i-band optical luminosity in the denominator. Although the fraction of BALQSOs containing strong BAL features within the i-band wavelengths is less, any correction of the optical luminosities will further push these sources to lower log(RI) bins, thereby increasing the BAL fraction at higher orientation angles. Likewise, Hewett & Foltz (2003) suggest that optically bright BAL quasars are half as likely as non-BAL quasars to be detectable as S$_{1.4 \,\mathrm{ GHz}}\, \ge$ 1 mJy sources. To probe this, we divided the sample into three optical luminosity bins, (i) Log(Li band) ≤ 24 W/Hz, (ii) 24 W/Hz Log(Li band) ≤ 25 W/Hz, and (iii) Log(Liband) > 25 W/Hz, and studied the distribution of radio luminosity of BAL and non-BAL quasars. We do not see any difference in the distribution of radio luminosity between BAL and non-BAL quasars for the lower optical luminosity bins. But, for the highest luminosity bin, we see that the BAL quasars have statistically lower radio luminosities as compared to the non-BAL quasars (p-value of KS test 0.05). Thus, a flux-limited survey like FIRST would have missed a fraction of optically bright BAL quasars that have radio fluxes below the FIRST sensitivity. As these missed BAL quasars have low radio luminosities and high optical luminosities, a correction for the missed quasars would only populate the lower log(RI) bins. This again will amplify the already seen trend of BAL fraction increase at high orientation angles. To ensure that the optically bright sources are not biasing the BAL fraction trend, we excluded the optically bright sources from our sample and then studied the variation of BAL fraction as a function of orientation. The pruned sample also follows the trend of high BAL fraction for high orientation angles.

2021MNRAS.503.6170B__Santos-Santos,_Domínguez-Tenreiro_&_Pawlowski_2020_Instance_1

Flattened distributions of very likely co-orbiting satellite galaxies around the MW (Lynden-Bell 1976, 1982; Kroupa, Theis & Boily 2005; Pawlowski, Pflamm-Altenburg & Kroupa 2012) and M31 (Metz, Kroupa & Jerjen 2007; Ibata et al. 2013) have long posed a challenge to our understanding of galaxy formation in the ΛCDM context. Recent proper motion data confirm that most of the classical MW satellites do indeed have a common orbital plane (Pawlowski, Kroupa & Jerjen 2013; Pawlowski & Kroupa 2020) aligned with the plane normal defined by the satellite positions alone (Santos-Santos, Domínguez-Tenreiro & Pawlowski 2020). Their velocities show a very significant bias towards the tangential direction, as occurs for a rotating disc (Cautun & Frenk 2017). Proper motions of two M31 satellite plane members indicate that this structure is likely also coherently rotating (Sohn et al. 2020), as suggested by the RVs of satellites in this nearly edge-on structure (Ibata et al. 2013). After careful consideration of several proposed scenarios for how primordial CDM-rich satellites might end up in a thin plane, Pawlowski et al. (2014) concluded that none of them agree with observations for either the MW or M31. Structures as extreme as those observed are exceedingly rare in cosmological simulations (Ibata et al. 2014; Pawlowski & McGaugh 2014b), including hydrodynamical simulations (Ahmed, Brooks & Christensen 2017; Shao, Cautun & Frenk 2019; Pawlowski & Kroupa 2020) and simulations which model the effects of a central disc galaxy (Pawlowski et al. 2019). The arguments raised by Metz et al. (2009) and Pawlowski et al. (2014) against the group infall and filamentary accretion scenarios were later independently confirmed by Shao et al. (2018) using the EAGLE hydrodynamical cosmological simulation (Crain et al. 2015; Schaye et al. 2015). For a recent review of the satellite plane problem, we refer the reader to Pawlowski (2018), who considered both LG satellite planes and the recently discovered one around Centaurus A (Müller et al. 2018, 2021).

2016MNRAS.463..512D__Sutter_et_al._2014_Instance_1

The cosmic web, consisting of haloes, voids, filaments, and walls in large-scale structure is predicted by the cold dark matter model (Bond, Kofman & Pogosyan 1996; Pogosyan et al. 1998) and confirmed by large galaxy surveys (e.g. de Lapparent, Geller & Huchra 1986; Colless et al. 2003; Alam et al. 2015). Among these large-scale structures, the underdensities of the universe, i.e. cosmic voids, have been shown to have great potential for constraining dark energy and testing theories of gravity via several measurements. These measurements include: distance measurement via the Alcock–Paczyński test (Ryden 1995; Lavaux & Wandelt 2012; Sutter et al. 2014), weak gravitational lensing of voids (Krause et al. 2013; Clampitt & Jain 2015; Melchior et al. 2014; Gruen et al. 2016; Sánchez et al. 2016), the signal of the integrated Sachs–Wolfe effect associated with voids (Sachs & Wolfe 1967; Granett, Neyrinck & Szapudi 2008; Nadathur, Hotchkiss & Sarkar 2012; Flender, Hotchkiss & Nadathur 2013; Ilić, Langer & Douspis 2013; Cai et al. 2014; Planck Collaboration XIX 2014; Aiola, Kosowsky & Wang 2015; Kovács & Granett 2015; Planck Collaboration XXI 2015), void ellipticity as a probe for the dark energy equation of state (Lee & Park 2009; Lavaux & Wandelt 2010; Bos et al. 2012; Pisani et al. 2015; Sutter et al. 2015), void abundances and profiles for testing theories of gravity and cosmology (Li, Zhao & Koyama 2012; Clampitt, Cai & Li 2013; Barreira et al. 2015; Cai, Padilla & Li 2015; Lam et al. 2015; Massara et al. 2015; Zivick et al. 2015), coupled dark energy (Pollina et al. 2016), the nature of dark matter (Yang et al. 2015), baryon acoustic oscillations in void clustering (Kitaura et al. 2016; Liang et al. 2016), and redshift-space distortions in voids (Hamaus et al. 2015, 2016; Cai et al. 2016). Despite their popularity and great potential as a cosmological tool, a gap of knowledge between the evolution of individual voids through simulations and observations versus theory still persists. How voids evolve from the initial conditions and how dark energy or alternative theories of gravity shape this process still lacks a complete analytical understanding. As with the formation history of haloes, the initial conditions and evolution history of voids sets the base for their two fundamental properties: profile and abundance. As these are crucial for constraining cosmological parameters, it is therefore important to bridge the gap between theory and observations. This is the main goal of our study.

2020MNRAS.492.5152Z__Samarasinha_&_Mueller_2013_Instance_1

Scheeres (2007) and Nesvornỳ & Vokrouhlickỳ (2007) established averaging methods for YORP effects experienced by small bodies (mostly asteroids) taking real-time insolation and shape into account. However, unlike thermal radiation, as Fig. 2 shows, the CO (or H2O) production rate variation versus solar distance is too complex to be written into a linear or polynomial formula (over the entire range we want to investigate). Sidorenko, Scheeres & Byram (2008) applied the averaging method to obtain evolutionary equations in order to study the long-term variations in the nucleus spin state induced by outgassing torques, but the illumination variation is not considered in their simplified model. There are further analytical approaches described in the literature (Samarasinha & Mueller 2013; Steckloff & Jacobson 2016; Steckloff & Samarasinha 2018), although these models predicted a change in the spin state of the nucleus without taking into consideration the exact 3D shape model and its variation induced by mass loss. Therefore, to our knowledge, there exists no approximate framework that is able to combine spin and mass loss together with orbital evolution for the 3D shapes (accounting for shadowing and self-heating) we are exploring in this paper. Currently, only fully numerical schemes are appropriate to investigate sublimation torques in our context. At the same time, it is not feasible to include such numerically expensive considerations when exploring the parameter space of orbits, mass-loss function and axis orientations. Therefore, in this work, we consider the rotation of the nucleus only for the stable case, without taking into consideration the wobbling rotation excitation and the change in spin states as a result of sublimation torque. However, we plan to perform these in the future, relying on the knowledge gained from physically and scientifically interesting cases in this work. As a general remark, the spin (and/or orientation) changes induced by sublimation torque are not expected to play a role only if the orientation variation time-scale is significantly larger than the time-scale of shape modification. However, if the time-scale is significantly shorter, new results are expected as the variation period of θ and φ might bring new periodical effects. A tumbling spin state with large procession angle or even a chaotic rotation may average the mass loss on the surface to yield an ‘averaged’ shape as a result. Therefore, if a nucleus exhibits an asymmetry shape believed to be driven by sublimation activity, it would indicate that the nucleus rotates in a stable stage for a long-term period in its dynamical history. In other words, this implies that the time-scale of wobbling excitation of such objects might be much longer than the one for shape modification.

2022MNRAS.515.1568W__Weinberg_et_al._2003_Instance_1

The temperature of the IGM can be measured using the effect of Doppler broadening on the forest of Ly α absorption line seen in the spectra of high-redshift quasars and galaxies (Rauch 1998; Savaglio, Panagia & Padovani 2002). Traditionally, the absorbing clouds were treated as being distinct and fitting Voigt profiles (e.g. van de Hulst & Reesinck 1947; Carswell & Webb 2014; Webb, Carswell & Lee 2021) to features seen in spectra leads to two parameters, column densities and temperatures (e.g. Hu et al. 1995). However, since the identification of the Ly α forest in hydrodynamic simulations (Cen et al. 1994; Zhang, Anninos & Norman 1995; Hernquist et al. 1996), it was realized that in the context of cosmological models for structure formation, the Ly α forest is due to a fluctuating, continuous IGM (e.g. Bi 1993; Weinberg et al. 2003). Because of this, Hubble flow is the major source of broadening, and fitting the width of features with a thermally broadened profile of a discrete object will not yield the temperature directly. Many other techniques have therefore been developed to constrain the IGM temperature from the Ly α forest. One is the relatively straightforward use of Voigt profile fit parameters to try to find the envelope that corresponds to a minimum IGM temperature (e.g. Garzilli, Theuns & Schaye 2020). Others include wavelet transforms (Meiksin 2000; Garzilli et al. 2012), or measuring statistical properties of the Ly α forest flux, such as the power spectrum (Croft et al. 1998; Lai et al. 2006), which respond to the small-scale smoothing that results from increased IGM temperatures. More recent ideas include the reconstruction techniques of Müller, Behrens & Marsh (2021) that use 3D tomographic data. In the current work, we will use a neural network (NN, see below) trained on simulated Ly α spectra to infer the temperature from the smoothness of absorption features. We will be looking in particular for discontinuous T jumps that could result from discrete sources of heating such as quasars reionizing He ii. We note that the temperature of gas will also influence the pressure smoothing scale (Gnedin & Hui 1998), which physically makes gaseous structures smoother than their underlying dark matter counterparts (Peeples et al. 2010). In our current preliminary work, we will not model this effect (see also the approach of McQuinn et al. 2011, who used a similar approximation), so that the smoothing of absorption features will be entirely attributed to Doppler broadening.

2020ApJ...899..118C__Wang_et_al._2019_Instance_1

The origin of giant pulses has been remaining a mystery since the discovery of giant pulses from Crab pulsar (Staelin & Reifenstein 1968). The generation of giant pulse activity was pointed to be an intrinsic phenomenon within the pulsar (Hankins 1971). The giant pulses are supposed to be the product of induced Compton scattering of the radio radiation off the plasma in the pulsar magnetosphere (Petrova 2006). The extremely high intensity is as well caused by an enhanced number of charges partaking in the nonthermal, coherent radiation processes (Hankins et al. 2003). Alternatively, the origination of giant pulses is proposed from the coherent instability of plasma near the magnetic equator of light cylinder (Wang et al. 2019). Singal & Vats (2012) suggested that the giant pulse emission and nulling may be opposite manifestations of the same physical process. The giant pulses are suggested to occur in pulsars with extremely high magnetic fields at the light cylinder of BLC > 105 G (Cognard et al. 1996). Therefore, the giant pulses are proposed to originate near the light cylinder (Istomin 2004). However, the giant pulses are also detected in the pulsars with ordinary magnetic fields at the light cylinder of BLC 100 G, such as PSRs B0031−07 (Kuzmin & Ershov 2004), B1112+50 (Ershov & Kuzmin 2003), J1752+2359 (Ershov & Kuzmin 2005), B0950+08 (Smirnova 2012), B0656+14 (Kuzmin & Ershov 2006), B1237+25 (Kazantsev & Potapov 2017), and B0301+19 (Kazantsev et al. 2019), and it does not seem to support the high BLC hypothesis. The Vela giant micropulse emission physics maybe independent on the high magnetic field at the light cylinder. Although Vela’s BLC is about 20 times smaller than that of PSR B1937+21 and the Crab pulsar, it is still in the top 5% of pulsars with BLC estimate. The giant pulses from PSR J1824−2452A occur in narrow phase windows that correlate in phase with X-ray emission, and the two emission phenomena likely originate from the similar magnetospheric regions but not the same physical mechanism (Knight et al. 2006). In order to reveal the nature of the giant micropulses, simultaneous radio and X-ray observations on the Vela pulsar will be required.

2015MNRAS.452.2837M__Mendigutía_2013_Instance_1

We constructed a sample of artificial stars representing the TT and HAeBe regime by using synthetic models of stellar atmospheres (Kurucz 1993). The properties of each object are provided in Table 1. Columns two and three show the stellar luminosity and effective temperature. From these, the stellar radii was derived, spanning between 0.7 and 4 R⊙ (column 4). The stellar masses (column 5) were derived assuming log g = 4, and cover the 0.2–6 M⊙ range. Magnetospheric accretion (MA) shock modelling was carried out for each star by adding (blackbody) accretion contributions to the photospheric (Kurucz) spectra (see e.g. the reviews in Calvet, Hartmann & Strom 2000; Mendigutía 2013). Two representative examples are presented in Fig. 2 (left-hand panel). The shock model was applied following the usual recipes for both the TTs and HAeBes, and we refer the reader to Calvet & Gullbring (1998); Mendigutía et al. (2011) and Fairlamb et al. (2015) for further details. Three different values for the UV excess in the Balmer region of the spectra (from ∼3500 to 4000 Å, as defined in Mendigutía et al. 2013) were modelled for each object assuming typical values for the inward flux of energy carried by the accretion columns (1012 erg cm2 s−1) and the disc truncation radius (5R*): a ‘maximum’ excess (0.70 mag), whose corresponding accretion contribution is Lacc ∼ L* for L* ≥ L⊙; a ‘minimum’ excess (0.01 mag) representative of the observational limit, and whose corresponding accretion contribution is Lacc ∼ 0.01L* for L* ≥ L⊙; and finally, a ‘typical’ excess in-between the two previous (0.12 mag). The resulting accretion luminosities are shown in the last three columns of Table 1. These are plotted versus the corresponding L* values (blue diagonal dashed lines in Fig. 1), matching the overall distribution of data. We note that excesses larger than 0.70 mag could still be measured for the less luminous sources (L* ≤ L⊙) without reaching the upper bound (Lacc ∼ L*).

2019MNRAS.490.5567Z__Aschwanden_et_al._1999_Instance_1

Coronal loops are curvilinear structures in the outer layer of the solar atmosphere, and they are formed by thermal plasmas confined by magnetic fields and well reflect the coronal magnetic field configurations. Because a number of active phenomena in the solar atmosphere, such as flares, the solar wind, coronal mass ejection (CME) and coronal oscillation, are associated with the coronal magnetic field, instead of direct observation of the coronal magnetic field, solar physicists are able to indirectly obtain the structure and evolution of the coronal magnetic field by observing and studying the kinetic characteristics of coronal loops. On the other hand, when flares and CME occur, the coronal magnetic field structure will undergo drastic changes, which will result in the oscillation of coronal loops (Li, Liu & Tam 2017). Therefore, on the basis of the oscillation of coronal loops, especially their oscillation characteristics in frequency, phase and attenuation coefficient, solar physicists can further understand the relationships between the coronal magnetic field, flares and CME (Aschwanden et al. 1999; Jain, Maurya & Hindman 2015) and obtain corresponding physical parameters associated with oscillating coronal loops (Aschwanden & Schrijver 2011). Meanwhile, the study on coronal loops is also useful for us to well understand the properties of coronal plasmas (Parnell & De Moortel 2012), plasma motion inside coronal loops (Winebarger, DeLuca & Golub 2001; Uritsky et al. 2013; Zhou & Liang 2016), the propagation of MHD waves in coronal loops (Wang, Ofman & Davila 2013), the evolution of active regions (Yan et al. 2012) and coronal heating (Aschwanden et al. 2007a; Aschwanden & Peter 2017). In addition, in modelling the coronal magnetic field, the observed coronal loops can be taken as a constraint condition so as to obtain more realistic extrapolated results of the non-linear force-free (NLFF) magnetic field model (Su et al. 2009; Aschwanden 2013). In particular, along with the enrichment of observational data in multiple wavebands, the classification and study of different temperatures and densities of the coronal loops will be further expanded, and the meaningful physical mechanism of these phenomena will also be obtained (Aschwanden & Boerner 2011; Huang et al. 2012; Aschwanden et al. 2013a). However, it must be emphasized that the current observational data of coronal loops are just a two-dimensional (2D) projective result of the real shape of coronal loops on to the plane of sky. Therefore, to obtain the genuine shape of coronal loops, a three-dimensional (3D) reconstruction of coronal loops is needed (Aschwanden et al. 2008b). It is desirable to reconstruct the real shape of coronal loops, resulting from the fact that identical coronal loops from the 2D observation data of multiple viewing angles (the observation data of the Solar Terrestrial Relations Observatory (STEREO), Uritsky et al. 2013) can be detected and extracted.

2021MNRAS.501.2897G__Pribulla_&_Rucinski_2006_Instance_1

EE Cet (ADS 2163 B) is the southern (slightly fainter) component of the visual binary WDS 02499+0856 (Mason et al. 2001). It was discovered by the HIPPARCOS mission (Perryman et al. 1997), by noticing the variability of the combined light of both visual components. Lampens et al. (2001) performed photometric measurements of the visual pair and gave (but only for one epoch) the following values V(A) = 9.47 mag and V(B) = 9.83 mag. Pribulla & Rucinski (2006) lists the orbital parameters (orientation and separation) of WDS 02499+0856 and gave θ = 194°, ρ = 5.66 arcsec and magnitude difference ΔV = 0.07 mag (the magnitude difference can be as large as ΔV = 0.36 mag, due to photometric variability of the eclipsing binary). WDS 02499+0856 turned out to be a quadruple system, when the northern component was found to be a double-lined (SB2) binary from the DDO spectroscopic observations (Pribulla & Rucinski 2006). D’Angelo et al. (2006) re-confirmed the multiplicity of the system, and listed it among the contact binaries with additional components. Radial velocity observations from Rucinski et al. (2002) resulted in a well-defined circular orbit of the contact binary, with K1 = 84.05 km s−1, K2 = 266.92 km s−1 (q = 0.315), and an F8V spectral type. Karami & Mohebi (2007) using their own velocity curve analysis method, arrived at almost identical results for the mass ratio. Djurašević et al. (2006) presented the first model, resulting in orbital inclination of i = 78.5° and a fill-out factor of f = 32.69 per cent, T2 = 6314 K, and T1 = 6095 K, when spots were added. Their no-spot model resulted in very close value for the fill-out factor but slightly different geometrical and orbital parameters. The physical parameters derived in this study were: M1 = 1.37 M⊙, M2 = 0.43 M⊙, and mean radii R1 = 1.35 R⊙, R2 = 0.82 R⊙. It is worth noting here that the light curves analysed by these authors included the visual component in the photometric aperture with a contamination of about 54 per cent.

2021MNRAS.503.3279S__Magrini_et_al._2017_Instance_2

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).

2018ApJ...854..167G__Meece_et_al._2017_Instance_1

In the turbulent gaseous halos of clusters, groups, and galaxies (particularly massive ones), extended filaments and clouds condense out of the hot plasma in a top-down nonlinear23 23 This nonlinear condensation process has properties significantly different from those of classic linear thermal instability (TI); the latter is mainly concerned with small overdensities overcoming buoyancy oscillations (e.g., Field 1965; Balbus & Soker 1989; Burkert & Lin 2000; Pizzolato & Soker 2005; McCourt et al. 2012—more in Section 5). condensation cascade, forming a chaotic multiphase rain. The thermal state and kinematics of the progenitor hot plasma halo drive the formation and evolution of all the condensed structures, which inherit some of the parent properties. Part of the inner condensed gas eventually accretes onto the central supermassive black hole (SMBH), igniting the feedback response and efficiently self-regulating the entire atmosphere over several gigayears (e.g., Gaspari et al. 2011a, 2011b, 2012a, 2012b; Li & Bryan 2014; Barai et al. 2016; Soker 2016; Yang & Reynolds 2016; Meece et al. 2017; Voit et al. 2017). This feeding process is known as chaotic cold accretion (CCA; Gaspari et al. 2013b) and can intermittently boost the accretion rates up to 100× the hot (Bondi) rate. If turbulence is subdominant, the halo tends instead to condense in a disk structure (due to the preservation of angular momentum), reducing feeding and feedback—this regime is more important for low-mass, spiral galaxies.24 24 The top-down rain differs from the bottom-up condensation in the disk of spiral galaxies, where the hot/warm phase is created in situ by supernovae, which drive compressive, non-solenoidal turbulence (e.g., McKee & Ostriker 1977; Kim et al. 2013). Nevertheless, the two complement each other, producing multiphase gas in the more extended halo and in the disk, respectively. Massive galaxies, groups, and clusters, lacking an extended disk (e.g., Werner et al. 2014), typically reside in the top-down condensation regime. Finally, if the entropy of the halo (or cooling time) becomes too high, the whole atmosphere may simply prevent condensation and remain hot for an extended period of time, dramatically stifling the feedback response. Overall, assessing the dynamical state of the multiphase halos is crucial to understand the past and to predict the future evolution of cosmic structures.

2020AandA...642A.170V__Engelbrecht_&_Burger_2010_Instance_1

Jovian electrons were used as test particles to model the charged-particle transport computationally (see e.g. Chenette et al. 1977; Conlon 1978; Fichtner et al. 2000; Zhang et al. 2007, and references therein) to ascertain the diffusion coefficients parallel and perpendicular to the Heliospheric Magnetic Field (HMF). This was usually done by comparing computed with measured electron intensities at Earth during periods of good or bad magnetic connection. Furthermore, given the demonstrated sensitivity of computed low-energy galactic electron intensities to various turbulence quantities (see Engelbrecht & Burger 2010, 2013; Engelbrecht 2019), it may be possible to draw conclusions from Jovian electrons to better understand the behaviour of those quantities in regions of the heliosphere where spacecraft observations of this character do not exist (see, e.g., Engelbrecht 2017). Since these transport parameters and the diffusion coefficients they depend on are spatially dependent, the time that particles reside in a certain part of the heliosphere may yield significant insights to the modulation of GCRs as well. Florinski & Pogorelov (2009) showed this dependency for GCR protons, investigating the time they spend in the heliotail, in the heliosheath, and in the solar wind within the termination shock, respectively. Utilising both galactic electrons and protons, Strauss et al. (2011a) focussed on the connection between thetotal propagation time and energy losses. They find a significant non-linear dependency on the total propagation times, which is strong enough to influence also the observations of Jovian electrons. These energy losses are entirely caused by adiabatic effects as other possible influences such as particle-particle interactions are negligible in the TPE due to a lack of significance in the interplanetary medium. As the adiabatic energy changes d E∕d t ~−2∕3 ⋅ EuSW∕r are connected to the radial position, the corresponding energy loss rate per step only depends on the temporal step size Δs and the radial position after the step. The radial direction of the step is thereby irrelevant. This leads to particles spending more simulation time at small radii losing more energy and implicitly to a statistical connection between the average energy losses and the particle’s mean free paths.

2015ApJ...815....7V__Bale_et_al._2005_Instance_1

Turbulence in plasmas is a complex phenomenon that is characterized by different regimes in different ranges of spatial and temporal scales. Turbulence in the solar wind has been extensively studied, both by detailed analyses of in situ measurements and from a theoretical point of view; see Bruno & Carbone (2005) for a review. Such studies often adopt complementary views that the turbulence may be described either as a collection of waves that interact nonlinearly, so-called wave turbulence, or else as a collection of broadband, essentially zero-frequency eddies or flux tubes that form a hierarchy of coherent structures. These approaches have been extensively reviewed (Barnes 1979; Matthaeus et al. 2015), and we do not attempt a critical comparison in the present work. Instead, we adopt mainly a wave taxonomy of the fluctuations based on linear theory in order to address a specific set of questions. As motivation, we note that a variety of observations in the solar wind (Bale et al. 2005; Sahraoui et al. 2012) have suggested that fluctuations near the end of the magnetohydrodynamic (MHD) inertial cascade range, and approaching the kinetic plasma range, may consist primarily of kinetic Alfvén waves (KAWs). Here we address in particular the nature of fluctuations produced due to nonlinear interactions near the proton inertial length dp and investigate in some detail the basis for identifying them as KAWs. We show how phase mixing of large-scale parallel-propagating Alfvén waves is an efficient mechanism for the production of KAWs at wavelengths close to dp and at a large propagation angle with respect to the magnetic field. To support the interpretation as KAWs, we perform and analyze MHD, Hall magnetohydrodynamic (HMHD), and hybrid Vlasov–Maxwell (HVM) simulations that model the propagation of Alfvén waves and their fully nonlinear interaction with a nonuniform plasma background. We will be able to characterize fluctuations produced by this phase-mixing-like interaction as highly oblique KAWs.

2018AandA...616A..11G__Forbes_et_al._2012_Instance_1

In addition to secular evolutionary processes, a disc galaxy like ours is expected to have experienced several accretion events in its recent and early past (Bullock & Johnston 2005; De Lucia & Helmi 2008; Stewart et al. 2008; Cooper et al. 2010; Font et al. 2011; Brook et al. 2012; Martig et al. 2012; Pillepich et al. 2015; Deason et al. 2016; Rodriguez-Gomez et al. 2016). While some of these accretions are currently being caught in the act, like for the Sagittarius dwarf galaxy (Ibata et al. 1994) and the Magellanic Clouds (Mathewson et al. 1974; Nidever et al. 2010; D’Onghia & Fox 2016), we need to find the vestiges of ancient accretion events to understand the evolution of our Galaxy and how its mass growth has proceeded over time. Events that took place in the far past are expected to have induced a thickening of the early Galactic disc, first by increasing the in-plane and vertical velocity dispersion of stars (Quinn et al. 1993; Walker et al. 1996; Villalobos & Helmi 2008, 2009; Zolotov et al. 2009; Purcell et al. 2010; Di Matteo et al. 2011; Qu et al. 2011; Font et al. 2011; McCarthy et al. 2012; Cooper et al. 2015; Welker et al. 2017), and second by agitating the gaseous disc from which new stars are born, generating early stellar populations with higher initial velocity dispersions than those currently being formed (Brook et al. 2004, 2007; Forbes et al. 2012; Bird et al. 2013; Stinson et al. 2013). These complementary modes of formation of the Galactic disc can be imprinted on kinematics-age and kinematics-abundance relations (Strömberg 1946; Spitzer & Schwarzschild 1951; Nordström et al. 2004; Seabroke & Gilmore 2007; Holmberg et al. 2007, 2009; Bovy et al. 2012a, 2016; Haywood et al. 2013; Sharma et al. 2014; Martig et al. 2016; Ness et al. 2016; Mackereth et al. 2017; Robin et al. 2017), and distinguishing between them requires full 3D kinematic information for several million stars, in order to be able to separate the contribution of accreted from in-situ populations, and to constrain impulsive signatures that are typical of accretions (Minchev et al. 2014) versus a more quiescent cooling of the Galactic disc over time. Accretion events that took place in the more recent past of our Galaxy can also generate ripples and rings in a galactic disc (Gómez et al. 2012b), as well as in the inner stellar halo (Jean-Baptiste et al. 2017). Such vertical perturbations of the disc are further complicated by the effect of spiral arms (D’Onghia et al. 2016; Monari et al. 2016b), which together with the effect of accretion events might explain vertical wave modes as observed in SEGUE andRAVE (Widrow et al. 2012; Williams et al. 2013; Carrillo et al. 2018), as well as in-plane velocity anisotropy (Siebert et al. 2012; Monari et al. 2016b). Mapping the kinematics out to several kiloparsec from the Sun is crucial for understanding whether signs of these recent and ongoing accretion events are visible in the Galactic disc, to ultimately understand to what extent the Galaxy can be represented as a system in dynamical equilibrium (Häfner et al. 2000; Dehnen & Binney 1998), at least in its inner regions, or to recover the nature of the perturber and the time of its accretion instead from the characteristics and strength of these ringing modes (Gómez et al. 2012b).

2017AandA...608A..75C__Osten_et_al._2005_Instance_1

The spectral energy distribution of the flare determines the altitude range in the planet’s atmosphere that is affected by the flare. Intense flares on AU Mic display a strong continuum emission enhancement in the XUV (see Fig. 2c) which results in increased ionisation over a broad altitude range in the thermosphere. Large continuum enhancement during flares have also been seen in other wavebands. Strong increases in the FUV have been observed on AU Mic (Robinson et al. 2001), and also on another active M dwarf, AD Leo (Hawley & Pettersen 1991). More recently, Kowalski et al. (2010) showed that continuum emission may be the dominant luminosity source in the near ultraviolet (NUV) during flares. There have not been many simultaneous multi-wavelength studies of flaring stars (Hawley et al. 2003; Osten et al. 2005). There is a particular dearth of simultaneous data in the EUV which is critical for studies of exoplanetary upper atmospheres, but where measurements are difficult due to ISM absorption. More observations are needed, but if young, magnetically active stars display broadband continuum enhancements during flares, similar to AU Mic, this would mean that large altitude ranges in planetary atmospheres are affected. Programmes such as Measurements of the Ultraviolet Spectral Characteristics of Low-mass Exoplanetary Systems (MUSCLES) have begun to provide more information on the high-energy spectral shape of K and M dwarf stars, including in the EUV (France et al. 2016; Youngblood et al. 2016; Loyd et al. 2016). However, in these studies, the EUV flux is computed using reconstructed Lyman alpha flux assuming a spectral energy distributio similar to the Sun. This approach could lead to incorrect results for active stars. Further development of coronal models driven by multi-wavelength observations would provide the most accurate high energy spectra for active low-mass stars. Such observations should be provided by the Multiwavelength Observations of an eVaporating Exoplanet and its Star (MOVES) program which has begun to undertake a long-term study of the HD 189733 system (Fares et al. 2017).

2017MNRAS.469.3108C__Schweizer_&_Seitzer_1992_Instance_1

Having intermediate colours between the blue cloud and the red sequence, galaxies populating the so-called green-valley (e.g. Salim 2014; Schawinski et al. 2014) are generally considered as the transiting objects par excellence (Martin et al. 2007; Mendel et al. 2013; Salim 2014; Schawinski et al. 2014). Among these, the most interesting population certainly consists of those galaxies which have just entered the quenching phase (within a few Myr). Although hampered by the short duration of the quenching process, the search for galaxies in this critical phase of evolution has been carried on by several authors in the past decades. Galaxies characterized by both a tidally disturbed morphology and intermediate colours (e.g. Schweizer & Seitzer 1992; Tal et al. 2009) or low level of recent SF (Kaviraj 2010), young elliptical galaxies (Sanders et al. 1988; Genzel et al. 2001; Dasyra et al. 2006) and very recent post-merger remnants with strong morphological disturbances (Hibbard & van Gorkom 1996; Rothberg & Joseph 2004; Carpineti et al. 2012) have been considered as valid 'recent time' quenching candidates. Moreover, many attempts aimed at spectroscopically identifying quenching galaxies come from the investigations of the post-starburst (E+A or K+A) galaxies' UV and optical spectra, whose strong Balmer absorption lines and missing [O ii] λ3727 (hereafter [O ii]) and Hα emission lines (Couch & Sharples 1987; Poggianti et al. 2004; Quintero et al. 2004; Balogh et al. 2011; Muzzin et al. 2012; Mok et al. 2013; Wu et al. 2014) have been interpreted as signs of a recent halt of the SF (Dressler & Gunn 1983; Zabludoff et al. 1996; Quintero et al. 2004; Poggianti et al. 2008; Wild et al. 2009). The scarcity of galaxies that are in the transition phase suggests that, whatever mechanism may be responsible for the SF shut-off, it has to happen on short time-scales (Tinker, Wechsler & Zheng 2010; Salim 2014). The relatively short duration of the quenching process is also suggested by the surprising identification of a significant number of galaxies that look already quiescent at z ∼ 4–5, when the Universe was only ∼1–1.5 Gyr old (e.g. Mobasher et al. 2005; Wiklind et al. 2008; Juarez et al. 2009; Brammer et al. 2011; Marsan et al. 2015; Citro et al. 2016). However, a general and coherent picture concerning the SF quenching is still lacking. Very recently, evidence that the quenching of the SF could be a separated process with respect to the morphological transformation has come from the photometric and spectroscopic investigations of passive spiral galaxies (Fraser-McKelvie et al. 2016).

2022ApJ...929...32S__Singh_et_al._2017_Instance_1

The 21 cm global spectrum experiments aim to measure the sky-averaged spectrum with high precision so as to probe the early epochs of the universe. There are a number of such ground-based experiments, including the Experiment to Detect the Global Epoch-of-Reionization Signature (EDGES; Bowman et al. 2008; Bowman & Rogers 2010; Monsalve et al. 2017), the Sonda Cosmológica de las Islas para la Detecciónde Hidrógeno Neutro (SCI-HI; Voytek et al. 2014), the Probing Radio Intensity at high-z from Marion (PRIzM; Philip et al. 2019), the Shaped Antenna measurement of the background RAdio Spectrum (SARAS; Patra et al. 2013; Singh et al. 2017, 2018), the Cosmic Twilight Polarimeter (CTP; Nhan et al. 2019), the Broadband Instrument for Global Hydrogen Reionization Signal (BIGHORNS; Sokolowski et al. 2015), the Large-Aperture Experiment to Detect the Dark Age (LEDA; Bernardi et al. 2016; Bernardi 2018; Price et al. 2018), and the Radio Experiment for the Analysis of Cosmic Hydrogen (REACH; de Lera Acedo 2019). Compared to the 21 cm tomography experiments, measurement of the global 21 cm emission has a higher raw sensitivity and requires smaller collecting area, so that it could be conducted even with a single antenna. The EDGES (Bowman et al. 2018) reported the detection of a strong absorption feature at ∼78 MHz, which has a cosmic dawn 21 cm spectrum interpretation, though it has an unexpectedly large amplitude (0.5 K) and an unusual flattened profile. If it originated from the cosmic 21 cm spectrum, this would suggest possibly new physics or astrophysics (Chen & Miralda-Escudé 2004, 2008; Creasey et al. 2011; Nelson et al. 2013; Barkana 2018; Fialkov et al. 2018; Fraser et al. 2018; Barkana et al. 2018; Slatyer & Wu 2018; Li et al. 2021; Houston et al. 2018; Hirano & Bromm 2018; Muñoz et al. 2018; Yang 2021), though this result was not confirmed by a recent measurement of the SARAS experiment (Singh et al. 2022). It is imperative to check this result and improve upon it with further and more precise observations.

2022MNRAS.512.1629F__Fioroni,_Savage_&_DeYonker_2019_Instance_1

The ORCA software (version 4.0.2) (Neese 2012) was used for all geometry minimizations, potential energy surface (PES), and vibrational frequency analyses using the global hybrid functional PW6B95 (Zhao & Truhlar 2005) coupled to the split valence triple-ζ def2-TZVPP basis set with two sets of polarization functions (Weigend & Ahlrichs 2005) and the atom-pairwise dispersion correction energy with Becke–Johnson damping (D3BJ) (Grimme et al. 2010; Grimme, Ehrlich & Goerigk 2011). The selected level of theory (PW6B95-D3BJ/def2-TZVPP) is a reliable and accurate theoretical tool in the estimation of general main group thermochemistry, kinetics, and non-covalent interactions after the double hybrid functionals (Goerigk et al. 2017). The reliability of the used method is also underlined by the good qualitative agreement between the Density Functional Theory (DFT) and MP2-F12 calculations as found in previous works (Fioroni & DeYonker 2016; Fioroni et al. 2018; Fioroni, Savage & DeYonker 2019). To speed up calculations, the RI (Resolution of the Identity) (Neese 2003) and RIJCOSX (Neese et al. 2009b) algorithms were used coupling the Coulomb-fitting basis sets def2/J (Weigend 2006). Because all the considered TSs involve a simple bond breaking/formation or a dihedral rotation, after a PES search performed on the desired reaction coordinate, the eigenvector following method (Schlegel 1982; Horn et al. 1991; Eckert, Pulay & Werner 1997), as implemented in ORCA, was used. Furthermore, the computed structures were verified to represent a minimum or a transition state by analysis of harmonic vibrational frequency calculations. Finally, the visualization of the normal mode associated to the TS was analysed. The obtained enthalpies: (HTot = [EEl. + EZPE + EVib. + ERot. + ETrans.] + kBT) and S values (STot = SEl. + SVib. + SRot. + STrans.) were used to estimate the free energies (G) at T = 200 K. The selected T = 200 K is lower bound to the HCN polymerization to progress efficiently. When referring to astronomical bodies, such temperatures can be experienced, for example, by comets where temperature rises periodically by surface heating to release HCN and H molecules (Hoang et al. 2019) or by dust particles or greater bodies in the turbulent phase of a proto-planetary disc and planetary system evolution.

2016MNRAS.461.1719C__Clements,_Dunne_&_Eales_2010_Instance_1

The early history of galaxy clusters is a poorly constrained aspect of galaxy and large-scale structure formation. Hierarchical clustering models predict that massive elliptical galaxies will form in the cores of what will become the most massive galaxy clusters today, but the epoch of the bulk of star formation for these galaxies is unclear. Observations of high redshift clusters (z = 1–1.5) by the ISCS project (IRAC Shallow Cluster Survey; Eisenhardt et al. 2008) suggest that this is at z > 3, and the presence of well-defined red sequences of galaxies in clusters out to z ∼ 2 (Andreon & Huertas-Company 2011; Gobat et al. 2011; Santos et al. 2011; Pierini et al. 2012) supports this conclusion. Theoretical models by Granato et al. (2004) suggest that forming clusters will go through a phase in which multiple members will undergo near-simultaneous massive bursts of star formation. The spectral energy distribution of these objects would be dominated by the far-IR, as is the case for local massive starbursts (e.g. Clements, Dunne & Eales 2010). A galaxy cluster or protocluster (we use the term protocluster to indicate a structure that has yet to become virialized) going through such a formative phase would appear as a clump of dusty protospheroidal galaxies, and might be detected by observations in the far-IR and submm bands. Hints of such objects may already have been found by Spitzer (Magliocchetti et al. 2007) and SCUBA (Ivison et al. 2000; Priddey, Ivison & Isaak 2008; Stevens et al. 2010 and references therein). A recent study by Ivison et al. (2013) has uncovered a group of HLIRGs and ULIRGs at z = 2.41 thought to be the progenitor of a 1014.6 M⊙ cluster. At still higher redshifts, the highest redshift protocluster currently known, at z ∼ 5.3 (Riechers et al. 2010; Capak et al. 2011), and a group of objects associated with a z = 5 quasar (Husband et al. 2013) both contain at least one submm-luminous object, while the best studied group of high z submm-luminous sources to date is probably the four objects associated with a source in the GOODS-North field designated GN20, all lying at z = 4 (Daddi et al. 2009; Carilli et al. 2011), though this group is extended over a broad range of redshifts Δz ∼ 0.1.

2020ApJ...898L..33P__Delrez_et_al._2018_Instance_2

For the TRAPPIST-1 system, data obtained by HST provide initial constraints on the extent and composition of the planet’s atmospheres, suggesting that the four innermost planets do not have a cloud/haze-free H2-dominated atmosphere (de Wit et al. 2016, 2018). However, follow-up work by Moran et al. (2018) have shown that HST data can also be fit to a cloudy/hazy H2-dominated atmosphere. Complementary to HST, NASA’s Spitzer Space Telescope—which played a major role in the discovery and orbital determination of TRAPPIST-1d, e, f, and g (Gillon et al. 2017)—has also allowed us to put additional constraints on the atmospheric composition of TRAPPIST-1b. Transit observations with Spitzer (Delrez et al. 2018) have found a +208 ± 110 ppm difference between the 3.6 and 4.2 μm bands, suggesting CO2 absorption. Spitzer also showed that transit depth measurements do not show any hint of significant stellar contamination in the 4.5 μm spectral range. Morris et al. (2018) reached the same conclusion using a “self-contamination” approach based on the Spitzer data set. Spitzer's “Red Worlds” Program encompassed over 1000 hours of observations of the TRAPPIST-1 system, whose global results have been presented (Ducrot et al. 2020). HST and Spitzer measurements have also been combined with transit light curves obtained from space with K2 (Luger et al. 2017) and from the ground with the SPECULOOS-South Observatory (Burdanov et al. 2018; Gillon 2018) and Liverpool Telescope (Steele et al. 2004) where Ducrot et al. (2018) produced featureless transmission spectra for the planets in the 0.8–4.5 μm wavelength range, showing an absence of significant temporal variations of the transit depths in the visible. Additional ground-based observations with the United Kingdom Infra-Red Telescope, Anglo-Australian Telescope, and Very Large Telescope also show no substantial temporal variations of transit depths for TRAPPIST-1 b, c, e, and g (Burdanov et al. 2019). While the K2 optical data set detected a 3.3 day periodic 1% photometric modulation, it is not present in the Spitzer observations (Delrez et al. 2018). Further constraints on the molecular weight and presence/absence of atmospheres on the TRAPPIST-1 planets will require additional observations with future facilities.

2019MNRAS.490..157M__Yu_&_Tremaine_2003_Instance_2

As a class, the fastest stars in our Galaxy are expected to be hypervelocity stars (HVSs). These were first theoretically predicted by Hills (1988) as the result of a three-body interaction between a binary star and the massive black hole in the Galactic Centre (GC), Sagittarius A*. Following this close encounter, a star can be ejected with a velocity ∼1000 km s−1, sufficiently high to escape from the gravitational field of the MW (Kenyon et al. 2008; Brown 2015). The first HVS candidate was discovered by Brown et al. (2005); a B-type star with a velocity more than twice the Galactic escape speed at its position. Currently about ∼20 unbound HVSs with velocities ∼300–700 km s−1 have been discovered by targeting young stars in the outer halo of the MW (Brown, Geller & Kenyon 2014). In addition, tens of mostly bound candidates have been found at smaller distances but uncertainties prevent the precise identification of the GC as their ejection location (e.g. Hawkins et al. 2015; Vickers, Smith & Grebel 2015; Zhang, Smith & Carlin 2016; Marchetti et al. 2017; Ziegerer et al. 2017). HVSs are predicted to be ejected from the GC with an uncertain rate around 10−4 yr−1 (Yu & Tremaine 2003; Zhang, Lu & Yu 2013), two orders of magnitude larger than the rate of ejection of RSs with comparable velocities from the stellar disc (Brown 2015). Because of their extremely high velocities, HVS trajectories span a large range of distances, from the GC to the outer halo. Thus, HVSs have been proposed as tools to study the matter distribution in our Galaxy (e.g. Gnedin et al. 2005; Sesana, Haardt & Madau 2007; Kenyon et al. 2014; Fragione & Loeb 2017; Rossi et al. 2017; Contigiani, Rossi & Marchetti 2018) and the GC environment (e.g. Zhang et al. 2013; Madigan et al. 2014), but a larger and less observationally biased sample is needed in order to break degeneracies between the GC binary content and the Galactic potential parameters (Rossi et al. 2017). Using the fact that their angular momentum should be very close to zero, HVSs have also been proposed as tools to constrain the solar position and velocity (Hattori, Valluri & Castro 2018a). Other possible alternative mechanisms leading to the acceleration of HVSs are the encounter between a single star and a massive black hole binary in the GC (e.g. Yu & Tremaine 2003; Sesana, Haardt & Madau 2006, 2008), the interaction between a globular cluster with a single or a binary massive black hole in the GC (Capuzzo-Dolcetta & Fragione 2015; Fragione & Capuzzo-Dolcetta 2016), and the tidal interaction of a dwarf galaxy near the centre of the Galaxy (Abadi et al. 2009). Another possible ejection origin for HVSs and high-velocity stars in our Galaxy is the Large Magellanic Cloud (LMC; Boubert & Evans 2016; Boubert et al. 2017; Erkal et al. 2018), orbiting the MW with a velocity ∼380 km s−1 (van der Marel & Kallivayalil 2014).

2022ApJ...927..138L__Lucas_et_al._2018_Instance_1

A color–color diagram in V − R versus B − V of the individual SSCs projected against the central spiral is shown in Figure 2 (left panel). The manner in which photometry of the individual stellar clusters was performed, including background subtraction, is described at length in Lim et al. (2020). In brief, we used the StarFinder algorithm (Diolaiti et al. 2000) to perform PSF-fitting photometry that includes subtraction of the local background. Only objects that exceed 4σ local, where σ local is the local root-mean-square noise level, are accepted as detections. Conversions to magnitude are based on the standard zero-points in the Vega system as described in the ACS Data Handbook (Lucas et al. 2018), and corrected for Galactic extinction. Two age loci, each of which is based on a model single stellar population (SSP; i.e., population of stars all having the same age and metallicity) as taken from Zackrisson et al. (2011), are plotted in Figure 2 for different metallicities of Z = 0.4 Z ⊙ (black) and Z = Z ⊙ (yellow). The model SSPs are based on those utilized in the Starburst99 software (Leitherer et al. 1999; Vázquez & Leitherer 2005), and their colors include both continuum and line emission from H ii regions corresponding to an adopted unity filling factor for the gas left over from star formation. The resulting line emission, in particular Hα+[N ii], that is contained in the R band causes the steep rise in V − R starting below B − V ≈ 0.0 when the star clusters are younger than ∼10 Myr. The two loci having different metallicities closely overlap, such that the inferred age at a given color differs little between the two loci. The SSCs selected for study as indicated in Figure 1 (lower row) are concentrated around B − V ≈ 0.35, corresponding to an age around ∼500 Myr (more details below). The spread in their colors is larger than can be accounted for by photometric uncertainties alone, although there may well be a degree of contamination by stellar clusters associated with the HVS, as well as the chance projection of SSCs lying beyond 5 kpc but positioned along the sightline toward the central spiral. By contrast, as shown in the color–color diagram of Figure 2 (right panel), the SSCs located beyond the central spiral (omitting the region occupied by the HVS and the outer regions of NGC 1275 dominated by GCs, as described by Lim et al. 2020) span a continuous range of ages from a few Myr to at least ∼1 Gyr, beyond which they cannot be distinguished from the even more numerous GCs around NGC 1275.

2018MNRAS.479..615M__Shakura_&_Sunyaev_1973_Instance_1

We also detect a Compton hump at around 15–30 keV during the 2016 NuSTAR observation. The inclusion of the 10–50 keV spectral data does not affect the spectral model parameters (disc inclination angle, spin, emissivity indices, and break radius) obtained from fitting of the 0.3–10 keV spectrum only. The best-fitting value of the disc electron density as derived from the modelling of the broad-band (0.3–50 keV) spectral data is $n_{\rm e}=5.2^{+5.2}_{-4.2}\times 10^{16}$ cm-3. Mrk 1044 is known to be a highly accreting AGN with the dimensionless mass accretion rate of $\dot{m}=\frac{\dot{M}c^{2}}{L_{\rm E}}=16.6^{+25.1}_{-10.1}$ (Du et al. 2015). At high accretion rate, the inner region of a standard α-disc (Shakura & Sunyaev 1973) is radiation pressure dominated and the electron density of the disc can be written as (Svensson & Zdziarski 1994) (11) \begin{eqnarray*} n_\mathrm{ e}=\frac{1}{\sigma _{\rm T}R_{\rm S}} \frac{256\sqrt{2}}{27}\alpha ^{-1}r^{3/2}\dot{m}^{-2} [1-(3/r)]^{-1} (1-f)^{-3}. \end{eqnarray*} where σT = 6.64 × 10−25 cm2 is the Thomson scattering cross section, RS = 2GMBH/c2 is the Schwarzschild radius, MBH is the black hole mass, α = 0.1 is the disc viscosity parameter, r = R/RS, R is the characteristic disc radius, $\dot{m}=\frac{\dot{M}c^{2}}{L_{\rm E}}$ is the dimensionless mass accretion rate, and f is the fraction of the total power released by the disc into the corona. The variation of the disc electron density (ne) with the dimensionless mass accretion rate ($\dot{m}$) for α = 0.1, $M_{\rm BH}=3\times 10^{6}\,\mathrm{M}_{\odot }$, f = 0.9, and r = 10 is shown as the solid curve in Fig. 17. As evident from Fig. 17, the assumption of constant disc density (ne = 1015 cm-3) is not physically realistic for low-mass AGNs even when the mass accretion rate is very high. The observed best-fitting value for the disc electron density of the source and its 90 per cent confidence limits are shown as the dotted and dashed lines in Fig. 17, respectively. The corresponding dimensionless mass accretion rate of Mrk 1044 estimated using equation (11) is $\dot{m}\approx 10-32$, which is in agreement with that found by Du et al. (2015). We further verified the SMBH mass with the use of X-ray variability techniques as pioneered by Ponti et al. (2012). The relation between the SMBH mass (MBH, 7) in units of $10^{7}\,\mathrm{M}_{\odot }$ and normalized excess variance ($\sigma _{\rm NXS}^{2}$) in the 2–10 keV light curves of 10 ks segments and the bin size of 250 s, can be written as (12) \begin{eqnarray*} \log (\sigma _{\rm NXS}^{2})=(-1.83\pm 0.1)+(-1.04\pm 0.09)\log (M_{\rm BH,7}). \end{eqnarray*} The SMBH mass of Mrk 1044 measured using equation (12) is $M_{\rm BH}=(4-5)\times 10^{6}\,\mathrm{M}_{\odot }$ which is close to that measured by Du et al. (2015).

2021AandA...649A.142A__Zhang_et_al._2019_Instance_1

An et al. (1988) and Wu et al. (1990) investigated the effects of plasma injection on the formation of the Kippenhahn-Schlüter model of prominence in optimum conditions. These authors found that for high values of the plasma-β parameter (the ratio of plasma pressure to magnetic pressure) the magnetic arcade develops a magnetic dip at the centre of the structure that supports the prominence plasma. However, comparing with our study, in the low plasma-β regime (or under others injection conditions) they found that the dip is less deep and the system develops two additional plasma enhancements located at the lateral edges of the magnetic arcade. Recent works suggest that the deformation of the magnetic field lines is determined by the parameter δ (the ratio of the gravity to the magnetic pressure) (Zhou et al. 2018; Zhang et al. 2019). An et al. (1988) suggested that the steady lateral plasma accumulates because of both the injection process and because the field lines without dips do not geometrically contain the injected plasma, but Wu et al. (1990) proposed that the prominence mass is also supported by an increase in the pressure gradient. Since in this study we consider that magnetic field lines do not change owing to the presence of the dense thread we investigate in detail the results of An et al. (1988) and Wu et al. (1990) in part II of this paper. On the contrary, studies of the formation of 1D filament threads by chromospheric heating in the presence of non-adiabatic effects, such as radiative losses and thermal conduction, show that for magnetic loops without a dip, the plasma condenses but it streams along the magnetic field and disappears after falling to the footpoints (Antiochos et al. 2000; Karpen et al. 2006). Moreover, when the thread is initially in a thermal and force-balance equilibrium state but it is disturbed by a strong velocity perturbation, the prominence mass drains down to the chromosphere. Dense blobs of falling plasma have been habitually observed (Schrijver 2001; de Groof et al. 2005), therefore it seems that threads cannot be held static along vertical magnetic flux tubes in the corona. The coronal part of the tube can only slow down the falling blobs. Müller et al. (2004) proposed that the acceleration reduces because the pressure of the cooling plasma underneath the radiating blobs slows down the descent, and Oliver et al. (2014, 2016) and Martínez-Gómez et al. (2020) argue that pressure gradient is the main force that opposes the action of gravity. Our study proposes that the pressure gradient can cause the equilibrium of threads in quasi-vertical flux tubes without dips even though it has not been corroborated by observations. Besides, our model is relatively simple to study the stability of filament threads in the magnetic field without dips. Other processes such as radiation and heat conduction must be considered, which might change the stability results.

2022MNRAS.517.4529B__Boruah,_Rozo_&_Fiedorowicz_2022_Instance_1

The other criteria that we can use to categorize the reconstruction methods is whether the reconstruction is performed using forward-modelling or uses a direct inversion from the data. Inverting non-linear problems from partial, noisy, observations is an ill-posed inverse problem, which makes forward-modelled Bayesian methods particularly suitable for the task of reconstruction of high-dimensional fields. Bayesian reconstruction methods have become increasingly popular in cosmology and have been applied in a range of different applications such as initial conditions reconstruction (Jasche & Wandelt 2013; Modi, Feng & Seljak 2018; Jasche & Lavaux 2019), weak lensing (Fiedorowicz et al. 2022; Porqueres et al. 2021, 2022; Boruah, Rozo & Fiedorowicz 2022), and CMB lensing (Millea et al. 2021; Millea, Anderes & Wandelt 2020). Such methods have also been used for the local velocity field reconstruction. The simplest of such methods uses a Wiener filtering technique (Zaroubi, Hoffman & Dekel 1999). This approach assumes that the density/velocity field is described as a Gaussian random field and the Wiener filtered reconstruction is the maximum-a-posteriori (MAP) solution for the problem. The Wiener filtering approach has been extended to account for uncertainties and biases in the reconstruction using a constrained realization approach (Hoffman & Ribak 1991; Hoffman, Courtois & Tully 2015; Hoffman et al. 2018; Lilow & Nusser 2021) An alternative way to account for the biases in the reconstruction in Wiener filtering is using the unbiased minimal variance approach (Zaroubi 2002). Another similar approach is the Bayesian hierarchical method, virbius (Lavaux 2016), which is based on the constrained realization approach but accounts for many different systematic effects in its analysis. This approach has been been applied to the Cosmicflows-3 (Tully, Courtois & Sorce 2016) data set by Graziani et al. (2019). A similar reconstruction code, hamlet, was introduced in Valade et al. (2022). However, these methods fail to account for the inhomogeneous Malmquist (IHM) bias which is an important source of systematic error in peculiar velocity analysis. The IHM bias arises from an incorrect assumption on the distribution of peculiar velocity tracers due to neglecting the line-of-sight inhomogeneities.

2021ApJ...908..187W__Hayakawa_et_al._2020b_Instance_1

Before 1500 A.D., when the magnetic latitude of China was higher than that at present, most of the observed aurorae were caused by CIRs and moderate CMEs. After 1500 A.D., the GNP moved to Canada. This caused the geomagnetic field latitude of China to decrease considerably. Meanwhile, the field intensity decreased to its minimum value in the last 2000 yr. Under these conditions, it would have been very rare to observe the aurora in most places in China after the 16th century, just like the present case (Wu et al. 2016a, 2016b; Hayakawa et al. 2020b, 2020c). However, this provides the best opportunity to investigate the existence of great-storm CMEs, which generate a wider auroral belt and equatorward shift of the EBAO and the EBAV (Boudouridis et al. 2003; Shue et al. 2009; Sigernes et al. 2011). If auroras were observed in China at lower magnetic latitudes than the EBAV related to the great storms, this indicates that the strong CMEs occurred. To quantify our results, we applied the classification of magnetic storms at the great level having Dst −350 nT (Loewe & Prölss 1997). According to the EBAV of the great level shown as the red dashed line in Figure 2(b), the auroras caused by great-storm CMEs could be identified, which were below the red dashed line. Surprisingly, there were many great-storm CMEs between 1500 and 1900, when Spörer minimum (1390–1550), Maunder minimum (1645–1715), and Dalton minimum (1797–1827) were inside (Lean et al. 1995; Solanki & Fligge 2000; Usoskin et al. 2015; Cliver & Herbst 2018; Hayakawa et al. 2020e). There were auroral sighting records in the same year, such as 1620 and 1646, from different places in China. As previously reported by Hayakawa et al. (2018b) there were simultaneous auroral records on the same day from different places in China in 1730. There are quite a few studies about the aurorae in September 1770 (Willis et al. 1996; Ebihara et al. 2017; Hayakawa et al. 2017a). Apart from the case analyses for extreme space weather events (Hattori et al. 2019; Isobe et al. 2019), our results indicate that there are more great-storm CMEs in the past 400 yr. Some of the great-storm CMEs happened in the solar maximum years, and some happened in the solar minimum years, as shown in Figure 7.

2022MNRAS.515.5416Y__Wechsler_et_al._2022_Instance_1

There are several different methods used in the literature for creating mock catalogues and light-cones. In purely empirical methods such as the JAdes extraGalactic Ultradeep Artificial Realizations (jaguar) models used to create mock catalogues in support of the JADES survey (Williams et al. 2018), observed galaxy properties are interpolated or extrapolated, and there is no underlying physics model nor setting within a Λ cold dark matter (ΛCDM) context. In what are sometimes called ‘semi-empirical’ methods [also called subhalo abundance matching (SHAM) or halo occupation distribution (HOD) models; see Wechsler & Tinker 2018], galaxy properties are mapped on to the properties of dark matter haloes such that a set of observational quantities is reproduced (Behroozi, Conroy & Wechsler 2010; Moster, Naab & White 2013, 2018; Behroozi et al. 2019; Wechsler et al. 2022). Both of these methods have the advantage that they are computationally efficient, are not dependent on a specific model for galaxy formation, and are guaranteed to match the observations that were used to calibrate them. However, they have the disadvantage that using them for forecasts for new observations is highly uncertain, and they are of limited use for interpretation. Semi-empirical models are typically calibrated using derived physical properties such as stellar masses and star formation rates (SFRs), which are highly uncertain at high redshifts, leading to models that are nominally calibrated on the same observations, but which have very different predictions for the link between galaxy and dark matter halo properties (see e.g. Yung et al. 2019b). We note that this is only a general overview for the semi-empirical modelling approach. These models are designed with different purposes in mind and adopt different calibration criteria. For example, UniverseMachine used high-redshift ultraviolet (UV) luminosity functions (LFs) to calibrate galaxy growth at the highest redshifts (Behroozi et al. 2019, 2020) and the semi-empirical model presented in Behroozi & Silk (2015) allows forecasts under the assumption that galaxy–halo growth relationships are given by power laws.

2021ApJ...914...88P__Forgan_et_al._2018b_Instance_1

Observing with instruments such as the Atacama Large Millimeter/submillimeter Array (ALMA) is crucial to our understanding of planet-formation mechanisms, as we can observe at wavelengths that trace continuum emission from the cold midplane (e.g., Testi et al. 2014), where we expect planets to be forming or have already formed. In the case of midplane spiral structures, their origin may be linked to the presence of a companion—stellar, fly-by, or planetary (Pohl et al. 2015; Bae & Zhu 2018a; Dong et al. 2018; Forgan et al. 2018b; Cuello et al. 2019; Keppler et al. 2020). Spirals may also be excited if the system is gravitationally unstable. Gravitationally instability is expected in cool and massive disks, where the disk-to-star mass ratio is larger than 0.1 (Bell et al. 1997; Gammie 2001; Lodato & Rice 2004; Cossins et al. 2009; Hall et al. 2016; Kratter & Lodato 2016; Rice 2016; Hall et al. 2019; Zhang & Zhu 2020). To date, not many spirals in dust continuum emission have a clear origin, except for those in multiple systems where the presence of spirals has been linked to stellar interactions (Kurtovic et al. 2018; Rosotti et al. 2020). On the other hand, there are disks where spirals have been reported at millimeter wavelengths and where no companion to which the spiral origin may be linked has been detected yet (to date these are Elias 27, IM Lup, WaOph 6, and MWC 758; Pérez et al. 2016; Dong et al. 2018; Huang et al. 2018c). If no companion is detected and the disk is massive compared to the host star mass, the gravitational instability (GI) scenario arises as a possible explanation for the origin of the observed spirals. Studying disks undergoing GI is important, as population synthesis models show that GI primarily ends up forming brown dwarf mass objects (Hall et al. 2017; Forgan et al. 2018a). It seems that giant-planet formation through GI is rare (Rice et al. 2015), but it may still be the formation mechanism for important systems like HR 8799 (Vigan et al. 2017).

2017AandA...601A..87C__Falcke_(1996)_Instance_2

In a quasi-isothermal jet, Uj is (17)\begin{equation} \label{eq:U_j_quasi} U_{\rm j} = \zeta n_0 m_{\rm p} c^2\left(\frac{\gamma_{\rm j}\beta_{\rm j}}{\gamma_0\beta_0}\right)^{-\Gamma}\left(\frac{z}{z_0}\right)^{-2} \cdot \end{equation}Uj=ζn0mpc2γjβjγ0β0−Γzz0-2·Substituting Eqs. (17) and (13) into Eq. (10), and assuming the jet is launched with an initial γ0β0 equal to the sound speed (Eq. (16)), the 1D Euler equation that results is \begin{eqnarray} \label{eq:AGNJET_Corrected} &&\left\{\gamma_{\rm j}\beta_{\rm j}\frac{\Gamma+\xi}{\Gamma-1}-\Gamma\gamma_{\rm j}\beta_{\rm j}-\frac{\Gamma}{\gamma_{\rm j}\beta_{\rm j}}\right\}\frac{\partial \gamma_{\rm j}\beta_{\rm j}}{\partial z} = \frac{2}{z}; \\ &&\xi = \frac{1}{\zeta}\left(\frac{\gamma_{\rm j}\beta_{\rm j}}{\gamma_0\beta_0}\right)^{\Gamma-1}; \qquad \gamma_0\beta_0=\sqrt{\frac{\zeta\Gamma(\Gamma-1)}{1+2\zeta\Gamma-\zeta\Gamma^2}} \cdot \end{eqnarray}γjβjΓ+ξΓ−1−Γγjβj−Γγjβj∂γjβj∂z=2z;ξ=1ζγjβjγ0β0Γ−1; γ0β0=ζΓ(Γ−1)1+2ζΓ−ζΓ2·The above equation should reduce to the jet Lorentz factor profile used in Falcke (1996), Markoff et al. (2005) when ζ = 1. However, it differs from Eq. (2) in Falcke (1996): (20)\begin{equation} \label{eq:Heino96} \left\{\gamma_{\rm j}\beta_{\rm j}\frac{\Gamma+\xi}{\Gamma-1}-\frac{\Gamma}{\gamma_{\rm j}\beta_{\rm j}}\right\}\frac{\partial \gamma_{\rm j}\beta_{\rm j}}{\partial z} = \frac{2}{z}; \end{equation}γjβjΓ+ξΓ−1−Γγjβj∂γjβj∂z=2z;(21)\begin{equation} \xi = \left(\gamma_{\rm j}\beta_{\rm j}\frac{\Gamma+1}{\Gamma(\Gamma-1)}\right)^{1-\Gamma} \cdot \end{equation}ξ=γjβjΓ+1Γ(Γ−1)1−Γ·The difference between our equation and the equation in Falcke (1996) can be accounted for as follows: the − Γγjβj term in Eq. (18) results from a neglected \hbox{$\frac{\partial}{\partial z}(U_{\rm j}/n)$}∂∂z(Uj/n) term, the difference in the exponent in ξ results from an arithmetic error, and finally the difference in the inside of the parenthesis of ξ terms is from setting \hbox{$\gamma_0\beta_0 = \beta_{\rm s0}^{2}$}γ0β0=βs02 instead of using the proper value given in Eq. (16). The difference between the solutions of Eqs. (18) and (20) are small and shown in Fig. 1. In Fig. 1, we also include solutions to the 1D Euler equations when the jet is isothermal (Tj = const., i.e., Eq. 20 with ξ = 1) and adiabatic (Tj ∝ (γjβj)1 − Γz2 − 2Γ, see Eq. (25)).

2019MNRAS.482.3288G__Orazio,_Haiman_&_MacFadyen_2013_Instance_1

The orbital decay of BSBHs may slow down or stall at ∼pc scales (e.g. Begelman et al. 1980; Milosavljević & Merritt 2001; Zier & Biermann 2001; Yu 2002; Vasiliev, Antonini & Merritt 2014; Dvorkin & Barausse 2017; Tamburello et al. 2017), or the barrier may be overcome in gaseous environments (e.g. Gould & Rix 2000; Escala et al. 2004; Hayasaki, Mineshige & Sudou 2007; Hayasaki 2009; Cuadra et al. 2009; Lodato et al. 2009; Chapon, Mayer & Teyssier 2013; Rafikov 2013; del Valle et al. 2015), in triaxial or axisymmetric galaxies (e.g. Yu 2002; Berczik et al. 2006; Preto et al. 2011; Khan et al. 2013, 2016; Vasiliev, Antonini & Merritt 2015; Gualandris et al. 2017; Kelley, Blecha & Hernquist 2017a), and/or by interacting with a third SMBH in hierarchical mergers (e.g. Valtonen 1996; Blaes, Lee & Socrates 2002; Hoffman & Loeb 2007; Kulkarni & Loeb 2012; Tanikawa & Umemura 2014; Bonetti et al. 2018). The accretion of gas and the dynamical evolution of BSBHs are likely to be coupled (Ivanov, Papaloizou & Polnarev 1999; Armitage & Natarajan 2002; Haiman, Kocsis & Menou 2009; Bode et al. 2010, 2012; Farris, Liu & Shapiro 2010, 2011; Kocsis, Haiman & Loeb 2012; Shi et al. 2012; D’Orazio, Haiman & MacFadyen 2013; Shapiro 2013; Farris et al. 2014, 2015) such that the occurrence rate of BSBHs depends on the initial conditions and gaseous environments at earlier phases (e.g. thermodynamics of the host galaxy interstellar medium; Dotti et al. 2007, 2009; Dotti, Sesana & Decarli 2012; Fiacconi et al. 2013; Mayer 2013; Tremmel et al. 2018). Quantifying the occurrence rate of BSBHs at various merger phases is therefore important for understanding the associated gas and stellar dynamical processes. This is a challenging problem for three main reasons. First, BSBHs are expected to be rare (e.g. Foreman, Volonteri & Dotti 2009; Volonteri, Miller & Dotti 2009), and only a fraction of them accrete enough gas to be ‘seen’. Secondly, the physical separations of BSBHs that are gravitationally bound to each other (≲a few pc) are too small for direct imaging. Even VLBI cannot resolve BSBHs except for in the local universe (Burke-Spolaor 2011). CSO 0402+379 (discovered by VLBI as a double flat-spectrum radio source separated by 7 pc) remains the only secure case known (Rodriguez et al. 2006; Bansal et al. 2017, see Kharb, Lal & Merritt 2017; however, for a possible 0.35-pc BSBH candidate in NGC 7674). Thirdly, various astrophysical processes complicate their identification such as bright hot spots in radio jets (e.g. Wrobel, Walker & Fu 2014b). Until recently, only a handful cases of dual active galactic nuclei (AGNs) – galactic-scale progenitors of BSBHs – were known (Owen et al. 1985; Junkkarinen et al. 2001; Komossa et al. 2003; Ballo et al. 2004; Hudson et al. 2006; Max, Canalizo & de Vries 2007; Bianchi et al. 2008; Guidetti et al. 2008). While great strides have been made in identifying dual AGNs at kpc scales (e.g. Gerke et al. 2007; Comerford et al. 2009, 2012, 2015; Green et al. 2010; Liu et al. 2010, 2013, 2018; Fabbiano et al. 2011; Fu et al. 2011, 2012, 2015a,b; Koss et al. 2011, 2012, 2016; Rosario et al. 2011; Teng et al. 2012; Woo et al. 2014; Wrobel, Comerford & Middelberg 2014a; McGurk et al. 2015; Müller-Sánchez et al. 2015; Shangguan et al. 2016; Ellison et al. 2017; Satyapal et al. 2017), there is no confirmed BSBH at sub-pc scales (for recent reviews, see e.g. Popović 2012; Burke-Spolaor 2013; Bogdanović 2015; Komossa & Zensus 2016).

2018ApJ...855...26A__Karim_et_al._2013_Instance_1

The uncertainties in number counts were derived from Poisson statistics, which apply when event rates are calculated from small numbers of observed events (Gehrels 1986). Our results are given in Table 6 and plotted in Figure 7. For comparison, we also show the integral number counts from the lensing cluster surveys of Knudsen et al. (2008) and Johansson et al. (2011), from the SCUBA Half-Degree Extragalactic Survey (SHADES; Coppin et al. 2006), from LESS (Weiß et al. 2009), from SCUBA-2 (Hsu et al. 2016), and from the high-resolution ALMA follow-up of LESS (Karim et al. 2013). We find that, for the intrinsic flux density range covered by our survey, results are consistent within uncertainties with previous single-dish surveys conducted in blank fields (e.g., Coppin et al. 2006), toward lensing clusters (Knudsen et al. 2008; Johansson et al. 2011), and combining both cluster and blank fields (Hsu et al. 2016). The exception is the data point at Sint = 6.3 mJy, which is fainter than the 4σ detection threshold for all clusters and therefore comprises sources that are necessarily magnified. The discrepancy is possibly due to the uncertainties in our analytical lens models, which may generally underestimate magnification factors relative to those derived from strong-lensing models, as suggested by the comparison presented in Figure 5. If magnification factors are minimally increased across the field, intrinsic flux densities and binned number counts do not vary significantly, but the detectable area Asource where μ > 4σ/Sint is increased, thus affecting the number counts per unit area. To test this hypothesis, we repeated our calculations but slightly scaled our analytical magnification maps by a factor of ∼1. We find that a satisfactory match between our resulting number counts at Sint = 6.3 mJy and previous surveys can be reached if all magnification estimates are varied by only ∼5%, which is within the uncertainties obtained for μ and listed in Table 5.

2022ApJ...936...16M__Dubrulle_et_al._1995_Instance_1

Our assumption of a constant f dg does not account for vertical settling and depletion of dust in the disk atmosphere, which could in principle reduce the height of the different τ = 1 surfaces shown in Figure 6. Even though the Stokes number remains smaller than 1 for all considered particle sizes well above the τ = 1 surfaces for irradiation, the actual dust distribution in the atmosphere depends on the balance between turbulent stirring and vertical settling. The dust distribution away from the midplane is better captured by hydrodynamical simulations than by simple prescriptions relying on a parameterization of the turbulence strength (see, e.g., Dubrulle et al. 1995; Dullemond & Dominik 2004b), since it depends on the particular source of turbulence. An example of this is the anisotropic turbulence produced by the VSI, whose vertically elongated modes significantly increase the vertical stirring of dust with respect to models of homogeneous isotropic turbulence (Stoll & Kley 2016; Stoll et al. 2017). We note that these authors obtain a vertical Gaussian dust distribution of micron-sized particles with the same scale height as the gas in the entirety of a domain reaching z = 5H at 5 au, which supports the validity of our prescription. On the other hand, dust sedimentation of small grains in outer regions can even be affected by nonideal magnetohydrodynamical effects and magnetized winds (Riols & Lesur 2018; Booth & Clarke 2021; Hutchison & Clarke 2021). In principle, we do not expect dust settling effects to be relevant for our work as long as they occur in optically thin regions where radiative transport prevents any shadowing from occurring. Future disk models could test this hypothesis by studying the stability of disks in which the opacity is computed as a function of a dynamically evolving small dust distribution. We have also assumed instantaneous thermal equilibrium of gas and dust particles, which is not verified at high altitudes, as collisions between dust and gas particles become less frequent for smaller densities (see, e.g., Malygin et al. 2017; Pfeil & Klahr 2021). We do not expect this effect to alter our results, since at most it could increase the time it takes to form temperature perturbations in such regions.

2015ApJ...806...20B__Bartoli_et_al._2012a_Instance_1

The ARGO-YBJ detector, hosted in a building at the YangBaJing Cosmic Ray Observatory (Tibet, China, 90°31′50″E, 30°06′38″N), 4300 m above sea level, has been designed for very high-energy (VHE) gamma-ray astronomy and cosmic-ray observations. It is made up of a single layer of resistive plate chambers (RPCs) operated in streamer mode, 2.850 m × 1.225 m each, organized in a modular configuration to cover a surface of about 5600 m2 with an active area of about 93%. The RPCs detect the charged particles in air showers with an efficiency ≥98%. To improve the shower reconstruction, other chambers are deployed around the central carpet for a total instrumented area of 100 m × 110 m. A highly segmented readout is performed by means of 55.6 cm × 61.8 cm external electrodes, called “pads,” whose fast signals are used for triggering and timing purposes. These pads provide the digital readout of the detector up to 22 particles m−2, allowing the count of the air shower charged particles without any significant saturation up to primary cosmic-ray energies of about 200 TeV (Bartoli et al. 2012a). In order to extend the dynamical range to PeV energies each RPC is also equipped with two large size pads (139 cm × 123 cm), allowing the collection of the total charge developed by the particles hitting the detector (Aielli et al. 2012). The digital output of each pad is splitted in two signals sent to the logic chain that builds the trigger and to the 18,360 multi-hit time-to-digital converters, which are routinely calibrated with 0.4 ns accuracy by means of an off-line method using cosmic-ray showers (He et al. 2007; Aielli et al. 2009a). More details about the detector and the RPC performance can be found in Aielli et al. (2006, 2009b). The detector is connected to two independent acquisition systems corresponding to two different operation modes, referred to as the shower mode and the scaler mode (Aielli et al. 2008). The data used in this paper were recorded by the digital readout in shower mode. This mode is implemented by means of an inclusive trigger based on the time correlation between the pad signals, depending on their relative distance. In this way the data acquisition is triggered when at least 20 pads in the central carpet are fired in a time window of 420 ns. By means of this trigger the energy threshold for gamma-induced showers can go down to 300 GeV with an effective area depending on the zenith angle (see Figure 1 in Bartoli et al. 2013).

2021AandA...650A.164M__Davies_et_al._2012_Instance_3

The GMC associated with G305 is one of the most massive and luminous clouds in the Milky Way (Fig. 1). It is located in the Galactic plane at l ~ 305°, b ~ 0° and at a kinematic distance of 4 kpc (derived from a combinationof radio and Hα observationsby Clark & Porter (2004); Davies et al. (2012) measured its spectrophotometric distance to be 3.8 ± 0.6 kpc and most recently Borissova et al. (2019) measured the Gaia DR2 average distance to be 3.7 ± 1.2 kpc); this places it in the Scutum-Crux spiral arm. Given this distance, the complex has a diameter of ~ 30 pc (Clark & Porter 2004) and a molecular mass of ~6 × 105 M⊙ (Hindson et al. 2010). The G305 complex consists of a large central cavity that has been cleared by the winds from massive stars belonging to two visible central clusters (Danks 1 and 2) and the Wolf-Rayet star (WR48a; Clark & Porter 2004; Davies et al. 2012). The cavity is surrounded by a thick layer of molecular gas (traced by CO and NH3 emission; Hindson et al. 2010, 2013). Radio continuum observations by Hindson et al. (2012) have revealed that the cavity is filled with ionized gas and identified six ultra-compact HII (UC HII) regions and also one bright rimmed cloud (BRC) at the periphery of the cavity, indicating molecular gas irradiated by UV radiation (Sugitani & Ogura 1994; Thompson et al. 2004), which may cause implosion (Bertoldi 1989) or evaporation. A number of studies havereported star formation tracers (water and methanol masers, HII regions and massive young stellar objects, MYSOs; Clark & Porter 2004; Lumsden et al. 2013; Urquhart et al. 2014; Green et al. 2009, 2012). Furthermore, Hindson et al. (2010) found the concentration of star formation tracers to be enhanced inside a clump of NH3 bearing molecular gas that faces the ionizing sources, which is consistent with the hypothesis that the star formation has been triggered. Analysis of the stellar clusters in the complex reveals them to have ages of 1.5 Myr for Danks 1 and 3 Myr for Danks 2,with the former possibly being triggered by the latter (Davies et al. 2012). Additionally, a diffuse population of evolved massive stars was also found to exist within the confines of the G305 complex that had formed around the same time as the two clusters (Leistra et al. 2005; Shara et al. 2009; Mauerhan et al. 2011; Davies et al. 2012; Faimali et al. 2012; Borissova et al. 2019).

2022MNRAS.513.5377F__Fulle_et_al._2020b_Instance_1

Cometary activity is driven by the gas pressure P(s), which does not depend on the ice abundance, but only on the gas temperature: also minor species can drive cometary activity, provided that heat transfer inside a pebble is faster than ice depletion. This condition fixes an upper limit for the refractory-to-ice mass ratio δi (Fulle 2021) (8)$$\begin{eqnarray*} \delta _i \lt {\lambda _s \over {3 ~Q ~R ~c_p}} - 1 , \end{eqnarray*}$$where cp ≈ 103 J kg−1 K−1 is the heat capacity of the pebbles (Blum et al. 2017). In order to fulfil equation (2) during the whole inbound orbit, cometary activity is driven by at least the five ices listed in Table 2, reporting the nucleus and gas coma parameters computed by means of the activity model (Fulle et al. 2020b). Thus, the less abundant the ice, the shorter the rh-range where it can drive cometary activity (e.g. ethane in Table 2). The upper limit of each water-to-ice mass ratio is δi/δw, and in the protoplanetary disc δw ≈ 5 (Cambianica et al. 2020). The probable activity due to further ices not listed in Table 2 and the decrease of cp with the temperature (Takahashi & Westrum 1970; Shulman 2004; Bouziani & Jewitt 2022) significantly increase the upper limits of δi. However, e.g. formaldehyde has unknown thermodynamical parameters (Fray & Schmitt 2009), and e.g. ethylene and nitric oxide were not detected in 67P (Rubin et al. 2020), thus preventing a realistic computation of e.g. evolving cp values. According to the activity model, the distribution of water-ice is very inhomogeneous in the nucleus (Ciarniello et al. 2022), with water-rich pebbles, depleted of supervolatiles, embedded in a matrix of water-poor pebbles, which are rich of the ices listed in Table 2. Therefore, at rh > 3.8 au, dust is ejected from water-poor pebbles only, characterized by δw ≈ 50 (Fulle 2021), so that equation (2) is surely verified. In water-poor pebbles the water ice is less abundant than all other ices (excluded ethane, Table 2), so that these ices cannot be trapped inside a less abundant water ice. The observed activity of C/2017K2 at rh = 23.7 au (Jewitt et al. 2017) excludes also that ices may be trapped inside CO2-ice, because the CO2-driven activity onsets at rh = 13 au (Table 2).

2016MNRAS.457.3191D__Martin_et_al._2005_Instance_1

TYC 9486-927-1 was observed by Torres et al. (2006) as part of the Search for Associations Containing Young stars (SACY) programme (Torres et al. 2008). They assigned a spectral type of M1 and measured a radial velocity of vrad = 8.7 ± 4.6 km s−1 from 10 observations. The large uncertainty is likely due to the star's high rotational velocity (vsin i = 43.5 ± 1.2 km s−1); suggesting it is either a single rapid rotator or a spectroscopic binary with blended lines. TYC 9486-927-1 also shows signs of activity in X-ray (Thomas et al. 1998), H α emission (Torres et al. 2006) and the UV (using GALEX data from Martin et al. 2005 we find log FFUV/FJ = −2.49, log FNUV/FJ = −2.11). 2MASS J2126−8140 is an L3 first identified by Reid et al. (2008, although referencing Cruz, Kirkpatrick & Burgasser 2009 as the discovery paper). Subsequently Faherty et al. (2013) classified it as a low gravity L3γ (using the gravity classification system of Cruz et al. 2009). Recent VLT/ISAAC observations by Manjavacas et al. (2014) find it is a good match to the young, L3 companion CD-35 2722B (Wahhaj et al. 2011). These authors also used the spectral indices of Allers & Liu (2013) to confirm that the 2MASS J2126−8140 is an L3 and shows low gravity spectral features. Manjavacas et al. (2014) also used the BT-Settl-2013 atmospheric models (Allard, Homeier & Freytag 2012) to derive Teff = 1800 ± 100 K, log g = 4.0 ± 0.5 dex, albeit with better fits to supersolar metallicity models. Filippazzo et al. (2015) use photometry, a trigonometric parallax of 31.3 ± 2.6 mas (referenced to Faherty et al., in preparation) and evolutionary models to derive an effective temperature of 1663 ± 35 K. They also derived a mass of 23.80 ±1 5.19 MJ assuming a broad young age range of 10–150 Myr. Gagné et al. (2014) listed 2MASS J2126−8140 as a high probability candidate member of Tucana–Horologium association (TucHor) but noted that its photometric distance would be in better agreement with its TucHor kinematic distance if it were an equal mass binary.

2015AandA...584A.103S__Potekhin_et_al._2013_Instance_2

Douchin & Haensel (2001; DH) formulated a unified EoS for NS on the basis of the SLy4 Skyrme nuclear effective force (Chabanat et al. 1998), where some parameters of the Skyrme interaction were adjusted to reproduce the Wiringa et al. calculation of neutron matter (Wiringa et al. 1988) above saturation density. Hence, the DH EoS contains certain microscopic input. In the DH model the inner crust was treated in the CLDM approach. More recently, unified EoSs for NS have been derived by the Brussels-Montreal group (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013). They are based on the BSk family of Skyrme nuclear effective forces (Goriely et al. 2010). Each force is fitted to the known masses of nuclei and adjusted among other constraints to reproduce a different microscopic EoS of neutron matter with different stiffness at high density. The inner crust is treated in the extended Thomas-Fermi approach with trial nucleon density profiles including perturbatively shell corrections for protons via the Strutinsky integral method. Analytical fits of these neutron-star EoSs have been constructed in order to facilitate their inclusion in astrophysical simulations (Potekhin et al. 2013). Quantal Hartree calculations for the NS crust have been systematically performed by (Shen et al. 2011b,a). This approach uses a virial expansion at low density and a RMF effective interaction at intermediate and high densities, and the EoS of the whole NS has been tabulated for different RMF parameter sets. Also recently, a complete EoS for supernova matter has been developed within the statistical model (Hempel & Schaffner-Bielich 2010). We shall adopt here the EoS of the BSk21 model (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013; Goriely et al. 2010) as a representative example of contemporary EoS for the complete NS structure, and a comparison with the other EoSs of the BSk family (Chamel et al. 2011; Pearson et al. 2012; Fantina et al. 2013; Potekhin et al. 2013) and the RMF family (Shen et al. 2011b,a) shall be left for future study.

2017AandA...600A.123D__Coupeaud_et_al._(2011)_Instance_1

Despite the differences of the dust analogues retained in previous studies (Mennella et al. 1998; Boudet et al. 2005; Coupeaud et al. 2011) and in the present one, the spectroscopic properties and temperature dependent behavior of all these analogues remain qualitatively similar: the MAC value is correlated with the dust temperature and has a complex spectral shape differing from a simple asymptotic behavior in λ-2. At the same time, because of these differences between the samples in terms of internal structure, composition, porosity, homogeneity, the shape of the MAC in the FIR varies. Consequently, the MAC value at a given wavelength of all samples from this study and from previous studies spans a large range of values (see Table 1 for the MAC value of the samples studied here and Table 1 from Demyk et al. 2013, for previous studies at 1 mm). It must be noted that the MAC in Boudet et al. (2005) has been corrected for grain shape effect whereas in Coupeaud et al. (2011) and Mennella et al. (1998) and in the present study this correction was not applied (see Sect. 2.3). This partly explains why the MAC value are smaller in Boudet’s study, together with the effect of differences in the samples in terms of composition and structure. At 100 μm, the MAC values of all the samples from this study and from previous work are similar at 300 and 10 K (50–300 cm2 g-1 at 300 K and 40–260 cm2 g-1 at 10 K). At 500 μm, the MAC is greater at 300 K than at 10 K (2–20 cm2 g-1 at 300 K and 0.7–13 cm2 g-1 at 10 K). This is also the case at 1 mm where the MAC is in the range 0.1–11 cm2 g-1 at 300 K and 0.12–7 cm2 g-1 at 10 K. We note that for each sample the MAC at 300 K is always greater than at 10 K. Furthermore, the fact that the range of values of the MAC at 300 K and 10 K overlaps results from the dispersion of the measured spectra. This diversity of the MAC value and spectral shape that vary as a function of the materials studied can be problematic for astrophysical applications since one has to decide what analog is the most relevant and should be used in the modeling. This is considered in more detail in Sect. 5.

2020ApJ...905..111Z__Jirička_et_al._2001_Instance_3

Surveys of radio bursts in decimetric wavelengths is presented in papers by Isliker & Benz (1994) and Jirička et al. (2001), within 1–3 GHz and 0.8–2.0 GHz frequency ranges, respectively. Some of these bursts are still not well understood. This is a case of the slowly positively drifting bursts (SPDBs). They appear in groups or as single bursts, with a duration of an individual burst from 1 to several seconds and their frequency drift is lower than about 100 MHz s−1 (Jirička et al. 2001). The SPDBs seem to be similar to the reverse type III bursts (Aschwanden 2002) but their frequency drift is much smaller. The majority of observed SPDBs are connected to solar flares (Jirička et al. 2001), and they appear many times at the very beginning of the flares (Benz & Simnett 1986; Kotrč et al. 1999; Kaltman et al. 2000; Karlický et al. 2018). Kaltman et al. (2000) reported on several SPDBs observed during three solar flares in the 0.8–2 GHz frequency range. They found frequency drifts of the observed SPDBs to be within the 20–180 MHz s−1 range. Kotrč et al. (1999) studied one of those flares. By combining the radio and spectral plus imaging Hα observations, they explained the observed SPDBs as radio emission generated by downwards propagating shock waves. Based on numerical simulations of the formation of thermal fronts in solar flares, Karlický (2015) proposed that SPDBs observed in the 1–2 GHz range could be a signature of a thermal front. Furthermore, Karlický et al. (2018) reported the observation of an SPDB (1.3–2.0 GHz) observed during the impulsive phase of an eruptive flare. They found time coincidence between the SPDB occurrence, an appearance of an ultraviolet (UV)/EUV multithermal plasma blob moving down along the dark Hα loop at approximately 280 km s−1, and the observed change of Hα profile at the footpoint of that dark loop. Combining these observations they concluded that observed SPDB was likely generated by the thermal front formed in front of the falling EUV blob.

2020ApJ...896...12X__Rosenberg_&_Coleman_1969_Instance_1

The QBOs are also found in the local wavelet power spectra of the Bx, By, and Bz that are displayed in the left panel of Figure 2. As this figure shows, the significant regions of above 95% confidence level in the range of 256–512 days (peak at 1.01 yr) for Bx intermittently appear during 1975–2000, and those in the range of 256–600 days (peak at 1.02 yr) for By are also intermittently found during 1975–2000. The QBOs for Bz only appear in solar cycle 22, which corresponds to the significant period of 0.90 yr, and also peak at 1.58 and 2.77 yr. The possible period of 3.45 yr for Bx does not show the corresponding significant region in the local wavelet power spectrum. The significant region that corresponds to the possible period of 2.37 yr for By appears near 1992. Early study proved that the solar QBOs can be transmitted into interplanetary space by the open magnetic flux (Lockwood 2001; Bazilevskaya et al. 2014); thus, the QBOs found in the Bx, By, and Bz components should be related to the solar QBOs. On the other hand, the annual variation in the IMF polarity in the band of 256–512 days, which is referred to the Rosenberg–Coleman effect (Rosenberg & Coleman 1969), only appears in the ascending phase of solar cycles by studying the IMF polarity date for the years 1927–2002 through the wavelet analysis method (Echer & Svalgaard 2004). The authors indicated that such a result should be attributed to a more stable and flat heliospheric current sheet that only appears in the ascending phase of solar cycles and strong disturbance of the heliospheric current sheet that is present in the declining phase and minimum time of solar cycles, and the Rosenberg–Coleman effect had been confirmed by the IMF Bx component during 1964–2002. The wavelet power spectra of the IMF Bx and By components in Figure 2 show that the annual variation in two time series can also be found in some, but not all, ascending phases of solar cycles, which is partly similar to the wavelet map of the IMF polarity in Echer & Svalgaard (2004). Thus, the annual variation in the IMF Bx and By components is also modulated by the stability or strong disturbance of the heliospheric current sheet. However, the wavelet power spectra of the IMF Bz show a different result, which indicates that the annual variation in this time series should not be related to the heliospheric current sheet.

2022MNRAS.509..314F__Spitkovsky,_Levin_&_Ushomirsky_2002_Instance_1

Magnetohydrodynamic (MHD) shallow water equations are an alternative to complete system of MHD equations for plasma. In this approximation, a thin layer of plasma with a free boundary in a gravity field is studied (Gilman 2000). Shallow water flows with rotation are usually considered in case of large-scale flows in plasma astrophysics (Gilman 1967) and play an important role in understanding of various astrophysical objects. Such a model is used to study large-scale flows of the solar tachocline (a thin layer inside the Sun, located above the convective zone) (Gilman 2000; Dikpati & Gilman 2001; Miesch & Gilman 2004; Hughes, Rosner & Weiss 2007), flows of accreting matter in neutron stars (Inogamov & Sunyaev 1999, 2010; Spitkovsky, Levin & Ushomirsky 2002), dynamics of the atmospheres of neutron stars (Heng & Spitkovsky 2009), and magnetoactive tidally locked atmospheres of exoplanets (Cho 2008; Heng & Showman 2015; Batygin, Stanley & Stevenson 2017; Pierrehumbert & Hammond 2019). MHD shallow water equations are obtained by depth-averaging three-dimensional MHD equations of plasma layer with respect to pressure being hydrostatic and the height of the layer being much smaller than characteristic horizontal scale of motion. However, the depth-averaging procedure does not always lead to shallow water equations. Although the equations obtained by integrating over the height of the studied layer of the liquid will have a form similar to the equations of shallow water (Klimachkov & Petrosyan 2017b).1 Equations obtained in this paper are similar to MHD shallow water equations, but they have additional terms and equations referred to vertical magnetic field (Klimachkov & Petrosyan 2017a; Fedotova, Klimachkov & Petrosyan 2020). These new equations transform into common MHD shallow water equations (Gilman 2000) in case of zero vertical magnetic field. Due to this, hereinafter we name our approximation as quasi-two-dimensional MHD approximation and equations are named as quasi-two-dimensional equations for rotating astrophysical plasma with vertical magnetic field.2 Detailed review of wave processes in magnetohydrodynamics of astrophysical plasma with vertical magnetic field is presented in Petrosyan et al. (2020). Extensions of magnetohydrodynamics in plasma astrophysics for vertically stratified flows with vertical magnetic field can be found in Fedotova, Klimachkov & Petrosyan (2021).

2020ApJ...904..119F__Raaijmakers_et_al._2019_Instance_1

In this work, the parameter ranges are for 68% credibility interval unless specifically mentioned. With Equation (1), the amount of the post-merger gravitational radiation can be reasonably/qualitatively evaluated as long as (i.e., the EoS) is known. However, various EoS models have been proposed in the literature and it is not possible to be uniquely determined even in the foreseeable future. Fortunately, under the reasonable assumption that all NSs follow the same EoS, their properties can be jointly/reliably constrained with the nuclear data, the GW data, the measured masses, and the estimated radii of some NSs (e.g., Lattimer & Prakash 2016; Abbott et al. 2017a; Tews et al. 2017; Most et al. 2018; Landry & Essick 2019). The masses of NSs in some binary systems have been accurately measured and there is a robust lower limit on MTOV ≥ 2 M⊙ (Cromartie et al. 2020; Kandel & Romani 2020). The radii of NSs, however, usually are just evaluated indirectly and suffer from large systematical uncertainties. Thanks to the successful performance of the Neutron Star Interior Composition Explorer, the situation has changed and very recently the first-ever accurate measurement of mass and radius together for PSR J0030+0451, a nearby isolated quickly rotating NS, has been achieved (Miller et al. 2019; Riley et al. 2019), which favor a stiffer EoS than the data of GW170817. Hence, GW170817, PSR J0030+0451, some nuclear data as well as the lower limit on MTOV can be combined to reliably constrain the EoS as well as the bulk properties of NSs. This can be done either in the EoS parameterizing methods (Raaijmakers et al. 2019; Jiang et al. 2020) or the nonparametric approach (Essick et al. 2020; Landry et al. 2020), and the results are well consistent with each other. Here we directly adopt posterior samples of {MA, MB, ΛA, ΛB} obtained in Jiang et al. (2020) to calculate the for GW170817. Note that the region of represents the prompt black hole formation, which is irrelevant to GW170817 because of the delayed collapse of the remnant (Metzger 2019). So we neglect the posterior samples that give for GW170817. At 90% credible level, for the piecewise polytropic expansion method we have , while for the spectral decomposition method we have . We also adopt the method described in Kumar & Landry (2019) to evaluate the nonparametric posterior of PSRs+GWs+x-ray/Riley case in Landry et al. (2020) and get for GW1708017. The incorporation of the strong phase transition possibility by Landry et al. (2020) favors lower k2T than ours (note that the region is excluded), but has an overall agreement with the piecewise result and the spectral result (as shown in upper panel of Figure 1). For this reason we combine an equal sample of k2T calculated from these three different parameterization methods to perform all the calculations in this work unless specially specified. Clearly, the inferred is well within the region that predicts the very prominent post-merger GW radiation, which is rather encouraging. The post-merger energy is then estimated to be (90% confidence level) when the fitting error is considered for the combined posterior (see the upper panel of Figure 2). For B1534+12, B2127+11C, J1757-1854, and J0453+1559, we expect that they would emit almost the same amount of energy as GW170817 in the post-merger phase. This is understandable considering the comparable total mass of these systems. For lighter BNS systems like J0514-4002A, the expected post-merger energy is relatively small because of the large . While for heavier BNS systems like GW190425, we predict a prompt collapse scenario and thus emit a small amount of energy in the post-merger phase (see the lower panels of Figures 1 and 2). To our knowledge, ours is the first study to combine the intriguing numerical finding of Zappa et al. (2018) with the EoS constrained with the multimessenger information of NSs and then to demonstrate that GW170817 is likely the most efficient post-merger GW emitter among the observed BNS GW events.

2017MNRAS.470.4075L__Janev_&_Reiter_2004_Instance_1

In order to determine the unknown rate constant that will be used in the network, we used a methodology developed in previous articles (Loison et al. 2014a,b, 2015) and summarized in Appendix A. This methodology includes an extensive literature review, various Density Functional Theory (DFT) and ab initio calculations for critical gas phase reactions, namely H + l-C3H2, H + t-C3H2, O + c-C3H2, O + l-C3H2, N + C3, N + c-C3H2, N + l-C3H2, H + C3O, O + C3O, O + c-C3H3+, OH + C3, OH + c-C3H2, H2 + l-C3H and H2 + c-C3H, to determine the presence, or not, of a barrier. When there is no barrier in the entrance valley and exothermic bimolecular exit channels, we chose to use the capture rate constant or sometimes a fraction of the capture rate constant by comparison with similar reactions (the capture rate is the upper limit of the rate constants for barrierless reactions). The dissociative recombination (DR) of c,l-C3H2+ and c,l-C3H3+ is an important source of c,l-C3H and is the main source c,l,t-C3H2 in our network. The first step of c,l-C3H2+ and c,l-C3H3+ DR is the formation of highly excited C3H2** and C3H3**, which leads to bond fragmentation. Angelova et al. (2004) have shown that the DR of c-C3H2+ leads to 87.5 per cent of C3Hx and 12.5 per cent of C2Hy + CHz, and the DR of c-C3H3+ leads to 90.7 per cent of C3Hx and 9.3 per cent of C2Hy + CHz. Moreover, in DR processes, the H ejection is in general favoured more than H2 ejection (Plessis et al. 2010, 2012; Janev & Reiter 2004). Considering the exothermicity for the ejection of two hydrogen atoms (endothermic for c-C3H3+ DR and only slightly exothermic for l-C3H2+, c-C3H2+ and l-C3H3+ DR, see Appendix B), this process will have a low branching ratio. Then, the dissociation of C3H2** and C3H3** will produce mainly C3H + H and C3H2 + H, both C3H and C3H2 species being also excited considering the exothermicity of the DR and the fact that the hydrogen atom will carry only a limited part of the available energy through kinetic energy. Part of the excited C3H* and C3H2* molecules will lead to dissociation when they are populated above the dissociation limit, but most of them will relax through radiative emission of an infrared photon. As noted by Herbst et al. (2000), the typical time-scale for isomeric conversion is much shorter than that for relaxation by one infrared photon. Thus, because radiative relaxation occurs slowly, isomeric conversion leads to equilibrated isomeric (c-C3H $\leftrightarrows $ l-C3H, c-C3H2$\leftrightarrows $ l-C3H2) abundances at each internal energy. The final balance is determined at or near the effective barrier to isomerization, which corresponds to the energy of the transition state. The ratio between the isomeric forms are then approximated by the ratio of the rovibrational densities of states of the isomers at the barrier to isomerization calculated using the MESMER program (Glowacki et al. 2012). Fig. 2 shows the isomerization pathway calculated at the DFT level. The calculated geometries of the stationary point can be found in Appendix A. The t-C3H2 has a triplet ground state and its production in the excited singlet ground state is neglected here. The production of t-C3H2 from the DR of c,l-C3H3+ is supposed to come from c,l-C3H3+ + e− → c,l-C3H3 → t-C3H2 + H, which is supposed to be a minor channel in comparison to c,l-C3H3+ + e− → c,l-C3H3 → c,l-C3H2 + H (t-C3H2 has a ground triplet state, in contrast to c,l-C3H2, which has a singlet ground state).

2016ApJ...831...63X__Bergh_2009_Instance_1

The formation and evolution of S0 galaxies are very important for understanding the formation and evolution of galaxies, but they are still an open question (e.g., the recent review by D’Onofrio et al. 2015). Currently, there are two possible scenarios on the origin of S0 galaxies. One is that S0 galaxies are transformed from spiral galaxies, where spirals lose their gas and star formation is rapidly quenched. The other is that S0 galaxies are intrinsically different from spiral galaxies since their formation (Kormendy & Kennicutt 2004; Barway et al. 2009; van den Bergh 2009). The transformation origin may be associated with intra-cluster medium and neighboring galaxies, via minor mergers, slow encounters, galaxy harassments (Moore et al. 1996), or tidal effects in the dense environment (Gunn & Gott 1972; Larson et al. 1980; Dressler & Sandage 1983; Mihos & Hernquist 1994; Moore et al. 1998, 1999; Neistein et al. 1999; Shioya et al. 2002). A lot of studies have discussed the environmental dependence of galaxy evolution. Generally speaking, early-type galaxies tend to be in dense environments and have low star-formation rates (SFRs; Dressler 1980; Balogh et al. 1997, 1998, 2000; Poggianti et al. 1999; Treu et al. 2003). The fraction of S0 galaxies in the field is only about 15%, while spirals are the majority (Naim et al. 1995). Within the group environment, spirals and S0s are both about 40%–45% (Postman & Geller 1984). Furthermore, S0s become dominant in dense environments, the fraction grows up to 60% in clusters (Dressler 1980; Postman & Geller 1984). Dressler et al. (1997), Fasano et al. (2000), and Desai et al. (2007) also found that the galaxy morphological distributions change abruptly in clusters at , about 50 ∼ 70% of spirals at high redshift (z > 0.4) are transformed into S0s, while a fraction of ellipticals, about 25%, remains nearly constant between z = 0.8 and z = 0.0. However, Wilman et al. (2009) showed that the fraction of S0s in groups is the same as in clusters but it is much higher than in the field at z = 0.4, which might suggest that S0s are formed in groups or subgroups.

2016MNRAS.456..512C__Kronberg_et_al._2004_Instance_1

Extended radio emission in galaxies is associated with both radio jets and lobes and with outflows, seen often as aligned radio sources in the opposite directions with respect to the central compact radio core. Giant radio galaxies (GRG) are extreme cases of this phenomenology with jets and lobes extending on ∼ Mpc scales suggesting that they are either very powerful or very old site for electron acceleration. In this respect, GRGs have a crucial role in the acceleration of cosmic rays over large cosmic scales (e.g. Kronberg et al. 2004), in the feedback mechanism of AGNs into the intergalactic and intracluster medium (e.g. Subrahmanyan et al. 2008) and in the seeding of large-scale magnetic fields in the universe (e.g. Kronberg et al. 2004) and they are excellent sites to determine the total jet/lobe energetics in AGN-dominated structures (see e.g. Colafrancesco 2008, Colafrancesco & Marchegiani 2011). To date our knowledge of GRGs (see e.g. Ishwara-Chandra & Saikia 1999, 2002; Lara et al. 2001; Machalski, Jamrozy & Zola 2001; Schoenmakers et al. 2001; Kronberg et al. 2004; Saripalli et al. 2005; Malarecki et al. 2013; Butenko et al. 2014) is limited by their sparse numbers and by the difficulty of detecting them over large areas of the sky. Low-frequency radio observations have an enhanced capacity to detect the extended old electron population in these objects (see e.g. the recent Low Frequency Array – LOFAR – observation of the GRG UGC095551), but high-frequency radio observations are less efficient in this task due to the steep-spectra of giant radio lobes. In this context these sources will be ideal targets for the next coming deep, wide-field surveys like, e.g. the ATLAS survey of the Australia Telescope Network Facility (ATNF; see Norris et al. 2009) or the Square Kilometre Array (SKA) deep surveys that will have the potential to study their population evolution up to high redshifts and thus clarifying their role on the feedback for the evolution of non-thermal processes in large-scale structures.

2018ApJ...852..112K__Neronov_&_Aharonian_2007_Instance_1

The Virgo Cluster radio galaxy M87 (NGC 4486), located at a distance of Mpc (Mei et al. 2007) and believed to harbour a BH of mass , was the first extragalactic source detected at VHE energies (Aharonian et al. 2003). Given its proximity, M87 has been a prime target to probe scenarios for the formation of relativistic jets with high-resolution radio observations exploring scales down to some tens of rg, and much effort has recently been dedicated in this direction (e.g., Acciari et al. 2009; Doeleman et al. 2012; Hada et al. 2014, 2016; Akiyama et al. 2015, 2017; Kino et al. 2015). At VHE energies, M87 has revealed at least three active γ-ray episodes, during which day-scale flux variability (i.e., ) has been observed (Aharonian et al. 2006; Albert et al. 2008; Acciari et al. 2009; Abramowski et al. 2012; Aliu et al. 2012). The VHE spectrum is compatible with a relatively hard power law (photon index ∼2.2) extending from 300 GeV to beyond 10 TeV, while the corresponding TeV output is relatively moderate, with an isotropic equivalent luminosity of erg s−1. The inner, parsec-scale jet in M87 is considered to be misaligned by –25°, resulting in modest Doppler boosting of its jet emission and creating challenges for conventional jet models to account for the observed VHE characteristics (see, e.g., Rieger & Aharonian 2012 for review and references). Gap-type emission models offer a promising alternative and different realizations have been proposed in the literature (e.g., Neronov & Aharonian 2007; Levinson & Rieger 2011; Broderick & Tchekhovskoy 2015; Vincent 2015; Ptitsyna & Neronov 2016). M87 is overall highly underluminous with characteristic estimates for its total nuclear (disk and jet) bolometric luminosity not exceeding erg s−1 by much (e.g., Owen et al. 2000; Whysong & Antonucci 2004; Prieto et al. 2016), suggesting that accretion onto its BH indeed occurs in a non-standard, advective-dominated (ADAF) mode characterized by an intrinsically low radiative efficiency (e.g., Di Matteo et al. 2003; Nemmen et al. 2014), with inferred accretion rates possibly ranging up to (e.g., Levinson & Rieger 2011) and a BH spin parameter close to its maximum one (e.g., Feng & Wu 2017). For these values of the accretion rate, the soft photon field (see Equations (2) and (3)) is sufficiently sparse that the maximum Lorentz factor of the magnetospheric particles is essentially determined by the curvature mechanism. The observed VHE variability is in principle compatible with , so that the different dependence of the gap power on β, Equation (20), does not necessarily (in the absence of other, intrinsic considerations of gap closure) imply a strong difference in the extractable gap powers. Figure 2 shows a representative point for M87 (taking ). The observed VHE luminosity of M87 is some orders of magnitudes lower than the maximum possible gap power (given by the dotted line) and within the bound imposed by ADAF considerations (vertical line). The observed VHE flaring events thus appear consistent with a magnetospheric origin. VLBI observations of (delayed) radio core flux enhancements indeed provide support for the proposal that the variable VHE emission in M87 originates at the jet base very near to the BH (e.g., Acciari et al. 2009; Beilicke 2012; Hada et al. 2012, 2014).

2020MNRAS.494.2969T__Catelan_et_al._2001_Instance_1

In the tidal torque model used in this work, the alignment of spiral galaxies is purely due to their orientation, which in turn is related to the angular momentum correlation of neighbouring galaxies relative to the line of sight (Croft & Metzler 2000; Crittenden et al. 2001). Angular momentum correlations are mainly build up at early times during structure formation and are thus due to initial correlations (Catelan & Theuns 1996, 1997; Theuns & Catelan 1997). The correlated angular momenta result into to correlated inclination angles of neighbouring galaxies and thus ultimately into correlated ellipticities (Catelan, Kamionkowski & Blandford 2001). Assuming that the symmetry axis of the galactic disc coincides with the direction of the angular momentum $\hat{L} = \boldsymbol{L}/L$, the ellipticity can be written as the alignment of spiral galaxies is purely due to the orientation of their circular discs, which in turn is related to the angular momentum correlation of neighbouring galaxies relative to the line of sight (Croft & Metzler 2000; Crittenden et al. 2001). Angular momentum correlations are mainly build up at early times during structure formation and are thus due to initial correlations (Catelan & Theuns 1996, 1997; Theuns & Catelan 1997). The correlated angular momenta result into correlated inclination angles of neighbouring galaxies and thus ultimately into correlated ellipticities (Catelan et al. 2001). Assuming that the symmetry axis of the galactic disc coincides with the direction of the angular momentum $\hat{L} = \boldsymbol{L}/L$, the ellipticity can be written as (17)$$\begin{eqnarray*} \epsilon = \frac{\hat{L}^2_x - \hat{L}^2_y}{1+ \hat{L}^2_z} + 2\mathrm{i}\frac{\hat{L}_x\hat{L}_y}{1+\hat{L}^2_z}\,\, . \end{eqnarray*}$$Angular momentum is generated by a torque exerted by the ambient large-scale structure on to the protogalactic halo, a mechanism called tidal torquing (White 1984; Barnes & Efstathiou 1987; Schaefer 2009; Stewart et al. 2013). For Gaussian random fields, the autocorrelation of angular momenta is given by (Lee & Pen 2001) (18)$$\begin{eqnarray*} \left\langle \hat{L}_\alpha \hat{L}_\beta \right\rangle = \frac{1}{3}\left(\frac{1+ A}{3}\delta _{\alpha \beta } - A \hat{\Phi }_{\alpha \mu }\hat{\Phi }_{\mu \beta } \right)\,\, . \end{eqnarray*}$$The free parameter A determines the strength of the coupling between alignment and tidal torque. Since the correlation is determined by the traceless part of the shear tensor $\hat{\Phi }_{\alpha \beta }$ the resulting effect is clearly due to orientation effects only. For a Gaussian distribution $p(\hat{L}|\hat{\Phi }_{\alpha \beta })\mathrm{d}\hat{L}$ and the use of equation (17), one can express the ellipticity in terms of the tidal field (19)$$\begin{eqnarray*} \epsilon (\hat{\Phi }) = \frac{A}{2} \left(\hat{\Phi }_{x\alpha }\hat{\Phi }_{\alpha x} - \hat{\Phi }_{y\alpha }\hat{\Phi }_{\alpha y} -2\mathrm{i}\hat{\Phi }_{x\alpha }\hat{\Phi }_{\alpha y}\right). \end{eqnarray*}$$Correlations in the ellipticities can thus be traced back to the four-point function of the shear field, which is given in equation (11). For keeping a correct relative normalization of the shape correlations, we scale the resulting angular ellipticity spectra $C^{\mathrm{s},II}_{ij}(\ell)$ with the squared number of spiral galaxies $n_s^2$. It is remarkable that the shapes of spiral galaxies in the quadratic alignment model are in fact sensitive to tidal shear components parallel to the line of sight; in fact, those components determine the magnitude of the alignment effect, in contrast to the alignment of elliptical galaxies in the linear alignment model or to gravitational lensing, which reflect purely the tidal shear components perpendicular to the line of sight.

2020MNRAS.498.6069P__Casertano_&_Hut_1985_Instance_1

Galaxy colour is known to be sensitive to local density. Generally, sheets are denser than fields and filaments are denser than sheets. So the dependence of red and blue fractions on the geometry of large-scale environment shown in Fig. 5 may partly arise due to dependence of galaxy colour on local density. We need to decorrelate the effect of local density in order to test the role of large-scale structures on galaxy colours. We address this issue by calculating local number density of galaxies using kth nearest neighbour method (Casertano & Hut 1985). We compute the local number density using equation (2) with k = 5. We plot the local density against the local dimension of galaxies in three different volume-limited samples in Fig. 7. The top left, middle left, and bottom left panels of Fig. 7 show the relations between local dimension and local density for the three volume-limited samples when local dimensions are computed using $R_2=10 {\, h^{-1}\, {\rm Mpc}}$. The results in these panels show that the environments with larger local dimension indeed tend to have a lower local density. However, these relationships show very large scatters. The environments with local dimension up to D = 2.5 can have a wide range of local densities and it is difficult to assign a specific density range to the environments with different local dimensions. The three panels in the middle column and three panels in the right column of Fig. 7 show the relations between local density and local dimension in these samples for $R_2=40 {\, h^{-1}\, {\rm Mpc}}$ and $R_2=70 {\, h^{-1}\, {\rm Mpc}}$. They show a similar trend as seen in the three panels in the left column of the same figure. It may be noted that galaxies with smaller local dimension are progressively absent when the geometry of environments are characterized on larger length-scales. This points out to the emergence of a homogeneous network of galaxies on larger length-scales as mentioned earlier.

2020ApJ...898L..56L__Abdo_et_al._2010_Instance_1

The 3 month γ-ray light curve of 4FGL J1510.1+5702 reveals that it is at a high flux state in an epoch of several tens of days in 2018; meanwhile, optical flux densities of GB 1508+5714 in two bands rise in the same epoch. To further investigate the relationship between these two domains of emissions, a 3 day time bin γ-ray light curve is presented, together with the zoomed-in ZTF light curves; see Figure 4. In spite of the limited statistics and no Fermi-LAT observation toward the target at the exact time of the optical flares, the time bin (i.e., centered at MJD 58288.5) with the largest TS value in the 3 day γ-ray light curve is very close to the peaking time of the optical flares. Since optical variations are likely from the jet because of the large variability amplitude, based on the simultaneous γ-ray and optical brightening, we conclude that 4FGL J1510.1+5702 is the γ-ray counterpart of GB 1508+5714. There are three other time bins in the 3 month γ-ray light curve with TS values ≥10, centered at MJD 54909, 57265, and 56540, respectively. The first two time intervals do not fall into the operation time range of iPTF/ZTF. Moreover, no iPTF/ZTF data of GB 1508+5714 around MJD 56,540 are available; see Figure 3. Theoretically, in the leptonic radiation scenario, the optical and GeV γ-ray emissions of low synchrotron peaked blazars, including FSRQs, are proposed to be from the same population of emitting electrons. It is supported by correlated optical/γ-ray flares in FSRQs (e.g., Abdo et al. 2010; Bonning et al. 2012). Meanwhile, the redder-when-brighter spectral variability behavior has been detected in the optical wavelengths of γ-ray FSRQs, which is explained by the influence of the blue and slowly varying accretion disk emission (e.g., Bonning et al. 2012; Fan et al. 2018). For GB 1508+5714, a similar trend is shown. The optical spectral color, rmag–imag, is 0.66 mag in MJD 58286, while it is 0.43 mag in MJD 58272, despite the relatively large photometric uncertainties. The optical spectral color scaled by rmag corresponding to observations in different epochs are plotted, as shown in Figure 4. Its i-band variability amplitude is larger than that in the r band. All of these facts suggest that the contribution of the jet emission becomes significant at the optical wavelengths of GB 1508+5714 when the jet activity is intense with rising γ-ray emission. Moreover, the significant γ-ray emission together with the rapid optical variation in the r band provide information of the emitting jet blob. The radius of the emitting blob is constrained by the variability timescale, , where days for the current event. Meanwhile, assuming that the optical and γ-ray photons of GB 1508+5714 are from the same region, to avoid serious absorption on γ-rays from soft photons via the process, the corresponding optical depth should not be high, 1 where is the scattering Thomson cross section, is the differential comoving number density of the target photon per energy, is the energy of the target photon in dimensionless units, and is the absorption length (Dondi & Ghisellini 1995; Begelman et al. 2008). The soft photons from the jet itself could be responsible for the absorption. Since the highest energy of the detected γ-ray photons of GB 1508+5714 is ∼8 GeV, the corresponding soft photons are those detected at a few keV (3 erg s−1; Marcotulli et al. 2020), and the absorption length can be set the same as the radius of the emitting blob. A constraint of the Doppler factor of the jet blob, , is given.

2022MNRAS.510.3039K__Gunell_et_al._2018_Instance_1

Finally, our models assume the absence of planetary magnetic fields. The early paradigm considering the evolution of terrestrial planets has implied that the planetary magnetic field is necessary to protect planetary atmospheres and reduce the atmospheric mass loss (see e.g. Dehant et al. 2007, and references therein). The later studies, however, show that this point of view is ambiguous. Thus, the effect of the magnetic field on the atmospheric escape can be considered as a result of the two concurring processes: reducing the escape by capturing the ionised atmospheric species within the closed magnetic field lines, and enhancing the escape of the atmospheric ions through the regions of the open magnetic lines (polar cusps, in the case of a dipole field) and the reconnection on the night-side (see, e.g. Khodachenko et al. 2015; Sakai et al. 2018; Carolan et al. 2021). Thus, for planets in the Solar System, it was shown both in the observations (Gunell et al. 2018; Ramstad & Barabash 2021) and by modelling (Sakai et al. 2018; Egan et al. 2019) that the presence of a weak magnetic field can intensify atmospheric escape. These results, however, should be taken with caution for young planets, and in particular those in the sub-Neptune range, because of the different atmospheric structures and the non-thermal mechanisms dominating the atmospheric mass loss in the Solar System, which are contrary to the planets considered in this study (see, e.g. Scherf & Lammer 2021, for the discussion). For hot Jupiters, Khodachenko et al. (2015) predict a significant suppression of escape for intrinsic magnetic fields larger than 0.3 G. The model with the closest setup to this study by Carolan et al. (2021) predicts, however, for the 0.7Mjup planet experiencing XUV (thermally) driven atmospheric escape, a small increase in the atmospheric mass-loss rate with increasing dipole field strength (about twice between 0 and 5 G). We therefore expect that the possible effect from the planetary intrinsic magnetic field depends largely on the strength and configuration of the planetary and stellar magnetic fields, but, according to the numbers reported in the literature, might not affect our results dramatically. The lack of studies for close-in sub-Neptune-like planets, however, holds us from making final conclusions.

2018ApJ...857...98R__Ferraz-Mello_et_al._2008_Instance_1

Numerous investigations of tidal activity on extrasolar planets have been conducted, with a range of topics from the behavior of gas giants (e.g., Běhounková et al. 2010, 2011; Remus et al. 2012a, 2012b; Storch & Lai 2014), to tidal alterations of system dynamics (e.g., Lecoanet et al. 2009; Matsumura et al. 2010; Cébron et al. 2011; Bolmont et al. 2015; Turbet et al. 2017), to tidal alterations of habitability (Barnes et al. 2008, 2013; Jackson et al. 2008a, 2008b; Heller & Armstrong 2014; Kopparapu et al. 2014), issues of spin dynamics (Correia et al. 2008; Ferraz-Mello et al. 2008; Efroimsky 2012b; Cunha et al. 2015), and the role of tides on exomoons (Namouni 2010; Heller & Barnes 2013). Many such studies naturally begin with frequency-independent internal models, but an increasing number consider viscoelastic models (Henning et al. 2009; Běhounková et al. 2010, 2011; Remus et al. 2012a, 2012b; Auclair-Desrotour et al. 2014; Correia et al. 2014; Henning & Hurford 2014; Makarov & Efroimsky 2014; Shoji & Kurita 2014; Driscoll & Barnes 2015; Makarov 2015). Countless more studies rely upon reasonable selections of tidal dissipation terms in order to inform simulations of system dynamics. For solid planetary objects, a detailed study is eventually needed to constrain which rheological models are best under the stress, pressure, and compositional conditions that are applicable to exoplanets and exomoons. Indeed, studies of the Earth tell us that multiple rheological models may be needed as one goes deeper into an exoplanet’s interior. Higher pressures will surely change the microphysical mechanisms that govern the rheological response (Karato & Spetzler 1990). We currently must rely mainly on analytical and numerical modeling when exploring the interiors of extrasolar planets, particularly worlds in the super-Earth category not represented in our solar system (Valencia et al. 2007). It is not yet known how well laboratory results on the viscosity of peridotite can extend to high-pressure phases such as post-perovskite (Murakami 2004), which may play a large role in super-Earths.

2019ApJ...874L..32C__Ogle_et_al._1997_Instance_1

Cygnus A, at z = 0.0562, is 10 times closer than the next radio galaxy of similar radio luminosity.4 4 Radio luminosity >1045 erg s−1. The nuclear regions in Cygnus A have been observed extensively at radio through X-ray wavelengths (Carilli & Barthel 1996). The inner few arcseconds is a complex mix of optically obscuring dust clouds (Vestergaard & Barthel 1993; Whysong & Antonucci 2004; Lopez-Rodriguez et al. 2014; Merlo et al. 2014), atomic gas seen in narrow line emission (Stockton et al. 1994; Taylor et al. 2003), H i 21 cm absorption toward the inner radio jets, with a neutral atomic column density >1023 cm−2, depending on H i excitation temperature (Struve & Conway 2010), polarized, broad optical emission lines due to scattering by dust (Antonnuci et al. 1994; Ogle et al. 1997), and a highly absorbed hard X-ray spectrum with a total gas column density of ∼3 × 1023 cm−2 (Ueno et al. 1994; Reynolds et al. 2015). VLBI radio observations at 0.05 mas resolution reveal highly collimated jets originating on scales ∼200 times the Schwarzschild radius (Boccardi et al. 2016). Tadhunter et al. (2003), derive a black hole mass of 2.5 ± 0.7 × 109 M⊙ from HST and Keck spectroscopy of Pa-α and [O iii], and conclude that Cygnus A contains an AGN with a bolometric luminosity of order 1046 erg s−1, comparable to high redshift quasars (Runnoe et al. 2012). This AGN is highly obscured in the optical due to dust along our line of sight, with Av > 50 magnitudes, based on near-IR spectroscopy (Imanishi & Ueno 2000). Studies of the mid- to far-IR spectral and polarization properties have led to a model of a clumpy, dusty torus obscuring the AGN in Cygnus A, with a radius of at least 130 pc, although these conclusions are based on spatially integrated properties; these observations did not have the spatial resolution to resolve the torus, and hence are partially contaminated by emission from the radio core-jet (Privon et al. 2012; Lopez-Rodriguez et al. 2018).

2016ApJ...833...76B__Klimchuk_et_al._2008_Instance_1

A significant limitation of the model is that it ignores the well-established hydrodynamic evolution of the loop during the cooling process, involving the substantial transfer of mass between the chromosphere and the corona. For large downward heat fluxes, the transition region is unable to radiate the supplied energy, resulting in the deposition of thermal energy in the dense chromosphere. The resulting two to three orders-of-magnitude temperature enhancements create a large pressure gradient that drives an upward enthalpy flux of “evaporating” plasma. However, as the loop cools, the decreased heat flux becomes insufficient to sustain the radiation emitted in the now-dense transition region and hence an inverse process of downward enthalpy flux starts to occur. It has been suggested (Klimchuk et al. 2008) that the enthalpy fluxes associated with both evaporating and condensing plasma are at all times in approximate balance with the excess or deficit of the heat flux relative to the transition region radiation loss rate. This basic idea has allowed the development of global “Enthalpy-Based Thermal Evolution of Loops” (EBTEL) models that describe the evolution of the average temperature and density in the coronal part of the loops; these models are generally in good agreement with one-dimensional hydrodynamic simulations (Klimchuk et al. 2008; Cargill et al. 2012a, 2012b). It is, in principle, possible to include the effects of a turbulence-controlled heat flux in EBTEL (or 1D hydrodynamic) models. If this heat flux is reduced sufficiently relative to its collisional value, then, for the reasons explained above, there will be a significant impact on the thermal evolution of the loop. Doing so, however, would still require a numerical treatment, which is beyond the scope of the present work (but which it is our intention to carry out in a future work). Instead, we adopt a simpler approach that allows a systematic and fairly transparent quantitative analysis of the impact of turbulence on the thermodynamics of post-flare loops.

2018MNRAS.474..838D__and_2016_Instance_1

The first step in searching for dynamically correlated minor bodies, particularly those resulting from break-ups, is to get a clear characterization of what the expectations may be. The outcome of cometary disruption is well documented through two well-studied examples, those of the comets 73P/Schwassmann-Wachmann 3 and D/1993 F2 (Shoemaker-Levy 9). For reasons that still remain unclear, comet 73P started to break apart in 1995 and dozens of fragments were observed in 2006 and 2007 (see e.g. Crovisier et al. 1996; Weaver et al. 2006; Reach et al. 2009; Hadamcik & Levasseur-Regourd 2016). Some of these fragments have been recovered in 2010–2011 (Harker et al. 2011, 2017; Sitko et al. 2011) and 2016–2017 (e.g. Kadota et al. 2017;1 Williams 2017); it may consist of hundreds of pieces now (68 of them have orbit determinations). This fragmentation process can be described as gentle and progressive. In striking contrast, comet Shoemaker-Levy 9 experienced a sudden, violent fragmentation event triggered by strong tidal forces during a close encounter with Jupiter in 1992 July (see e.g. Sekanina, Chodas & Yeomans 1994, 1998; Asphaug & Benz 1996; Sekanina 1997). Most fragments collided with Jupiter over a period of a week (1994 July 16–22); 21 of them have orbit determinations. Quite different may have been the collisional event that led to the formation of the Haumea family (Brown et al. 2007; Schlichting & Sari 2009; Leinhardt, Marcus & Stewart 2010; Lykawka et al. 2012; Ortiz et al. 2012) perhaps more than 1 Gyr ago (Ragozzine & Brown 2007; Volk & Malhotra 2012). Fragments of recently disrupted minor bodies must have very similar values of their semimajor axis, a, eccentricity, e, inclination, i, longitude of the ascending node, $\mathit {\Omega }$, argument of perihelion, ω, and time of perihelion passage, τq, but $\mathit {\Omega }$, ω and τq tend to become increasingly randomized over time. In contrast, recently unbound pairs resulting from binary dissociation events might have relatively different values of a and e, but very similar values of i, $\mathit {\Omega }$ and ω, the difference in τq may initially range from weeks to centuries, but grows rapidly over time (see e.g. de León, de la Fuente Marcos & de la Fuente Marcos 2017; de la Fuente Marcos, de la Fuente Marcos & Aarseth 2017).

2021ApJ...912..163B__Brennecka_et_al._2020_Instance_2

Braukmuller et al. (2018) proposed that all elements fall into one of four categories based on their condensation temperature: refractory elements (50% condensation temperature, Tc,50 > 1400 K), which exhibit approximately uniform enrichments in their Si-normalized concentrations in CC chondrites compared to CI chondrites by a factor of ∼1–1.4; main component elements (1300 K Tc,50 1400 K), which have approximately the same Si-normalized elemental abundances in CC chondrites as CI chondrites (differ by a factor of ∼0.8–1.1); slope-volatile elements (800 K Tc,50 1300 K), which exhibit monotonically decreasing Si-normalized concentrations with decreasing Tc,50 compared to CI chondrites; and plateau volatile elements (Tc,50 800 K), which display uniform depletions in Si-normalized concentrations compared to CI chondrites by a factor of ∼0.1–0.7 that are characteristic of each CC chondrite group. Given their uniform nature with Tc,50 and comparatively well-constrained isotopic and elemental compositions, we chose to focus on the concentrations of refractory, main component, and plateau volatile elements in this study. For the refractory and main component elements in CC chondrites, we examine the elemental and isotopic compositions of Ti and Cr, respectively, because these are lithophile elements whose isotopic compositions have been measured precisely for a large number of chondrites and their components (Trinquier et al. 2007, 2009; Qin et al. 2010; Olsen et al. 2016; Van Kooten et al. 2016; Gerber et al. 2017; Davis et al. 2018; Zhu et al. 2019; Schneider et al. 2020; Williams et al. 2020). For CC iron meteorites, we examine the isotopic compositions of Mo and Ni, respectively, because these are siderophile elements (so are therefore present in appreciable concentrations in iron meteorites, unlike Ti and Cr) whose compositions have also been relatively well studied in a number of iron meteorites as well as chondrites and their components (Burkhardt et al. 2011; Budde et al. 2016; Kruijer et al. 2017; Bermingham et al. 2018; Nanne et al. 2019; Budde et al. 2019; Worsham et al. 2019; Brennecka et al. 2020; Spitzer et al. 2020). For the plateau volatile elements, we examine the elemental compositions of six elements (Bi, Ag, Pb, Zn, Te, and Sn) that exhibit a number of desirable properties: their concentrations have been relatively well constrained in CC chondrites; they show a range of lithophile, siderophile, and chalcophile behaviors; their concentrations do not appear to be strongly dependent on redox state; they show minimal variability among NC chondrite groups. Our reasoning for not considering the isotopic compositions of these elements is discussed in Section 2.3. The adopted isotopic and chemical composition of each element used in this study in CC chondrites, CC iron meteorites, CAIs, CI chondrites, and NC chondrites are included in Table 1. Uncertainties on elemental concentrations have not been routinely reported throughout the literature, although these values are typically ±5 wt% (e.g., Lodders 2003; Palme et al. 2014). CAIs can be categorized into six groups based on their compositions (Stracke et al. 2012). For the purposes of this study, we adopt the composition of type I CAIs as the representative value of refractory objects because they are seemingly the most abundant type and lack the characteristic elemental depletions of other CAI groups (e.g., Stracke et al. 2012; Brennecka et al. 2020). We also focus largely on ordinary chondrites (OC) as representative NC meteorites rather than enstatite chondrites (EC) or Rumuruti chondrites (RC). This is because EC chondrites formed under more reducing conditions than OC and RC chondrites, which introduced a compositional signature for some elements to EC chondrites that is not present in OC, RC, or CC chondrites (presumably due to their formation in more oxidizing environments) so is not representative of large-scale mixing in the disk (Alexander 2019b). Additionally, the isotopic compositions of RC chondrites are sparsely measured compared to OC and EC chondrites. NC meteorites could have experienced a number of processes (e.g., mixing, chondrule formation, volatile loss, the addition of refractory materials, etc.) that gave these meteorites their specific chemical and isotopic signatures (Alexander 2019b). We do not explore these processes in this study and simply adopt the measured elemental and isotopic compositions of NC chondrites as potential end-members for the compositions of CC meteorites.

2019AandA...627A..53H__Villar-Martín_et_al._1999_Instance_1

A spatial coincidence of the radio jet morphology and velocity dispersion of the ionised gas has already been reported for spatially-resolved spectroscopy of more luminous radio-quiet AGN (e.g. Husemann et al. 2013; Villar-Martín et al. 2017) and powerful compact radio sources (e.g. Roche et al. 2016), but it has been correctly proposed that the fast moving plasma itself can lead to radio emission that mimics jet activity (Zakamska & Greene 2014; Hwang et al. 2018). In the case of HE 1353−1917 we can rule out that the ionised plasma is creating the radio emission because the high-velocity ionised gas traced by [O III] is significantly displaced compared to the observed jet-like radio emission. Hence, we think that the radio jet is transferring its energy and momentum to the ambient medium through an extended shock front, which creates turbulence in a dense clumpy ISM. Such a great impact of the radio jet has been observationally shown in many cases (e.g. Villar-Martín et al. 1999, 2014; O’Dea et al. 2002; Nesvadba et al. 2006; Holt et al. 2008; Guillard et al. 2012; Harrison et al. 2015; Santoro et al. 2018; Tremblay et al. 2018; Jarvis et al. 2019) and theoretically supported through detailed hydrodynamic simulations (e.g. Krause & Alexander 2007; Sutherland & Bicknell 2007; Wagner & Bicknell 2011; Wagner et al. 2012; Cielo et al. 2018; Mukherjee et al. 2018). As we discussed in Sect. 3.6, the jet power alone is sufficient to energetically drive the outflow because only a small fraction of the AGN luminosity would impact the thin disc of the galaxy implying conversion efficiencies of more than 10% of Lbol. Hopkins & Elvis (2010) proposed a two-stage process for efficient radiation-driven outflows. They describe a scenario in which an initial weak wind in the hot gas phase, possibly initiated by an accretion disc wind or a radio jet, creates additional turbulence in the surrounding medium so that massive gas clouds will subsequently expand and disperse. This expansion of gas clouds would significantly increase their apparent cross-section with respect to incident radiation field of the AGN. Such a two-stage process may increase the coupling efficiency by an order of magnitude. While we cannot directly confirm this process with our observations, the close alignment of the jet axis and the ionisation cone greatly suggest that the outflow is driven jointly by both mechanical and radiative energy with an unknown ratio of the two. The open question is whether the same powerful outflow could have developed without the fast radio jet impacting the cold gas directly given its unique orientation.

2018ApJ...854...73I__Bowler_et_al._2014_Instance_1

The best-fit parameters are shown in Table 3. We find that the uncertainties in M* and are considerably large due to a degeneracy between the two parameters when all parameters are variable. Plotted in Figure 1 is the faint-end slope α as a function of redshift. Our results indicate that the best-fit values of α are about −2 at to 10, which are steeper than those at lower redshift (e.g., at in Bouwens et al. 2015). We show the fitting results at , 8, 9, and 10 in Figures 2, 3, 4, and 5, respectively. The top and bottom panels present the observed number densities and the best-fit luminosity functions in the image plane and the source plane, respectively. We also plot the results of previous blank-field surveys (Ouchi et al. 2009; Bradley et al. 2012; McLure et al. 2013; Oesch et al. 2013; Schenker et al. 2013; Bowler et al. 2014; Bouwens et al. 2015; Finkelstein et al. 2015; Calvi et al. 2016) and recent HFF results in other studies (Atek et al. 2015a; Laporte et al. 2016; McLeod et al. 2016). The best-fit parameters are consistent with those in previous studies. In the top panel of Figure 2, there may be an excess in the observed surface number density at . The reason for this excess is not clear, although using a size–luminosity relation that gives smaller sizes at faint magnitudes may reduce this excess. At , the observed number densities at the bright end are slightly larger than the number densities in the simulation. This is probably due to the existence of an overdense region of dropouts in the Abell 2744 cluster field. We discussed the properties of the overdensity in Ishigaki et al. (2016; see also Zheng et al. 2014 and Atek et al. 2015b). At , although we detect no galaxies, we can place a constraint on the luminosity function from the non-detection. Based on the best-fit parameters where only is variable, ∼1.4 galaxies are expected to be detected in the HFF fields. The middle panels of Figures 2–5 show histograms of the number of the dropouts. It is seen that our samples push the magnitude limits of the luminosity functions significantly by up to ∼3 magnitude. The correlations between M* and α at z ∼6–7 and 8 are presented in Figure 6.

2019MNRAS.484..712D__Moriarty_et_al._2014_Instance_1

The Gibbs free energy of the system, and thus the composition of the solids formed depends on the pressure and temperature at which condensation occurs. In order to consider reasonable pressures and temperatures for the inner regions of the PPD, and in order to convert these temperatures and pressures into radial locations within the disc and formation times for the solid condensates, we consider the simplest possible PPD model. We use the theoretical model derived in Chambers (2009), which models the viscous accretion of gas heated by the star. This model has been previously used for the modelling of planetesimal formation in PPDs (Moriarty et al. 2014; Harrison et al. 2018) and super-Earths (Alessi, Pudritz & Cridland 2017). This model ignores any vertical or radial mixing, and as will be discussed further later, any radial drift. All of these processes may be of critical importance in a realistic PPD. The Chambers model is a disc model with an alpha parameterization that divides the disc into three sections; an inner viscous evaporating region, an intermediate viscous region, and an outer irradiated region. For the calculations in this work, we have assumed disc parameters of $s_{0} = 33\, \mathrm{au}$, $\kappa _{0} = 0.3\, \mathrm{m^{2}\, kg}^{-1}$, α = 0.01, γ = 1.7, μ = 2.4, and $M_{*}=0.78\, \mathrm{M}_{\odot }$ following Chambers (2009) and Motalebi et al. (2015). We also assume that the mass of the PPD is directly proportional to the mass of the host star according to M0 = 0.1M* (Chambers 2009; Andrews et al. 2013). The temperature and radius of the star in the PPD phase are assumed to be functions of the stellar mass in the form derived in Siess, Dufour & Forestini (2000). The relations used in this work to calculate the PPD mass, the initial stellar radius, and the initial stellar temperature as a function of stellar mass are consistent with the values given in Stepinski (1998) and Chambers (2009) for a solar mass star. The analytical expressions for the pressure and temperature of the mid-plane of the PPD as a function of radial location (a) and time (tdisc) are presented in Appendix C. The temperature–radial location curves for the model disc around a star similar to HD 219134 are plotted as a function of time in Fig. 2. The pressure–temperature space mapped out by the model disc for the case of a star similar to HD 219134 is displayed in the Appendix in Fig. C1. The pressure–temperature space for the model disc of a solar mass star shows negligible differences compared to the HD 219134 case.

2017MNRAS.469S..39F__Johansen_et_al._2015_Instance_1

This conclusion can be quantified by the number of catastrophic collisions per comet (Rickman et al. 2015) (6) \begin{equation} N_{{\rm coll}} = N_{\rm p} A_{\rm p} u T / V, \end{equation} where Np is the number of comets in the disc, Ap and u are the collision cross-section and speed, respectively, T ≈ 0.4 Gyr is the time spent from accretion to scattering beyond Neptune and V is the disc volume. A cumulative size distribution of comets with a power index of −2.0 and u ≈ 0.6 km s−1 provides Ncoll ≈ 3, assuming that ≈5 Earth masses are distributed in comets of diameters from 1 to 100 km (Rickman et al. 2015). The size distribution is probably shallower (Johansen et al. 2015), as confirmed by the shallowing size distribution of craters of diameter 10 km observed on Pluto and Charon (Singer et al. 2016; Robbins et al. 2017). We simulate the impacts on Pluto and Charon by means of Holsapple’s model (http://keith.aa.washington.edu/craterdata/scaling/index.htm) with the following target parameters: cold ice as geological type, lunar gravity, zero atmospheric pressure; and with the following projectile parameters: bulk density of 500 kg m−3, diameter of 0.1 km and impact speed of 1 km s−1. Tests performed assuming numerical values around those just listed provide craters always a factor 2 larger than the projectiles, so that the number of projectiles of 0.1 km radius is a factor from (0.1/2.5)2.4 − 3 = 7 to (0.1/2.5)1.6 − 3 = 90 below previous estimates (Morbidelli & Rickman 2015; Jutzi & Benz 2017; Jutzi et al. 2017), according to Charon’s and Pluto’s crater size distributions, respectively (Robbins et al. 2017). The same computations performed by Rickman et al. (2015), changing only the cumulative power index from −2.0 to −1.4, i.e. Charon’s crater size distribution (Robbins et al. 2017), provide Ncoll ≈ 0.5, and Ncoll ≈ 0.05 with a cumulative power index of −0.6, i.e. Pluto’s crater size distribution (Robbins et al. 2017), which make equation (6) consistent with the observed flux of 67P fractal particles. This conclusion is confirmed by the craters observed on Nix (Robbins et al. 2017), with a cumulative power index of −0.8, close to Pluto’s one, a measured cumulative crater density of 0.01 km−2 at diameters >3 km (smaller projectiles would not destroy a parent comet, according to equation (5)) and an extrapolated cumulative crater density 0.1 km−2 at diameters >0.1 km, matching that extrapolated for Charon with a steeper cumulative index (Robbins et al. 2017). Nix and Charon are less affected than Pluto by a possible significant resurfacing and their crater density suggests a negligible number of catastrophic impacts during the Solar system lifetime on bodies of cross-section 10 km2.

2021MNRAS.503.1734I__McKinney_et_al._2019_Instance_1

We show in Fig. 6 the dependence of some Ly α characteristics on absolute FUV magnitude. Our galaxies with detected LyC emission are shown by red filled circles and those with upper limits of LyC emission are represented by red open circles. All our low-mass galaxies are characterized by moderate Ly α luminosities in a narrow range between 1042.19 and 1042.74 erg s−1 (Fig. 6a), that are slightly below the values for confirmed LyC leakers (blue filled circles) by Izotov et al. (2016a,b, 2018a,b) and high-redshift galaxies (grey open circles) by Ouchi et al. (2008), Hashimoto et al. (2017), Jiang et al. (2018), Matthee et al. (2017), Matthee et al. (2018), Sobral et al. (2018), but are ∼1 order of magnitude higher than those for GPs (black asterisks; Jaskot & Oey 2014; Henry et al. 2015; Jaskot et al. 2017; Yang et al. 2017a; McKinney et al. 2019). Our low-mass galaxies have high EW(Ly α) ∼ 65–220 Å (Table 7, red symbols in Fig. 6b), similar to those in other LyC leakers (blue symbols in Fig. 6b). They are at the high end of the EW(Ly α) values for high-z LAEs by Ouchi et al. (2008), Hashimoto et al. (2017), Jiang et al. (2018), Harikane et al. (2018), Caruana et al. (2018), Pentericci et al. (2018), Matthee et al. (2017, 2018), Sobral et al. (2018) (grey open circles) and GPs (black asterisks). However, contrary to expectations for galaxies with lower stellar masses and, likely, lower masses of the neutral gas, the separation between the Ly α peaks is on average similar to that in higher mass LyC leakers (Fig. 6c), and it is higher in galaxies with upper limits of LyC emission (>400 km s−1, red open circles). Ly α escape fractions fesc(Ly α) in low-mass galaxies are also similar to those in higher mass LyC leakers, and they are lower in galaxies with upper limits of LyC emission (red open circles in Fig. 6d). We also note that the average ratio of blue and red peak fluxes of ∼25 per cent (Table 7) is somewhat lower than the value of ∼30 per cent quoted by Hayes et al. (2021) for $z\, \sim$ 0 galaxies.

2018MNRAS.476.2421G__Gallego_et_al._2018_Instance_1

An alternative approach is to map the CGM through direct imaging of the Ly α line. Theoretical models suggest that three main mechanisms should be able to generate circumgalactic Ly α emission: cooling radiation of gravitationally heated gas (e.g. Haiman, Spaans & Quataert 2000; Yang et al. 2006; Dijkstra & Loeb 2009), ultraviolet (UV) photons produced through shock mechanisms (Taniguchi & Shioya 2000; Mori, Umemura & Ferrara 2004), and recombination radiation following photoionization (often referred as fluorescence) powered by UV sources (Cantalupo et al. 2005; Geach et al. 2009; Kollmeier et al. 2010). While the fluorescent signal powered by the diffuse metagalactic UV background (Hogan & Weymann 1987; Binette et al. 1993; Gould & Weinberg 1996; Haardt & Madau 1996), with an expected surface brightness (SB) of $\rm SB_{Ly\alpha }\sim 10^{-20} \,erg \,s^{-1} \,cm^{-2} \,arcsec^{-2}$ (Cantalupo et al. 2005; Rauch et al. 2008), is still out of reach for current optical instrumentation (but see Gallego et al. 2018), Ly α fluorescence is predicted to be boosted up into the detectable regime in the vicinity of bright ionizing sources, as luminous quasars (Rees 1988; Haiman & Rees 2001; Alam & Miralda-Escudé 2002; Cantalupo et al. 2005). This theoretical prediction has been confirmed by a number of surveys targeting the fluorescent Ly α emission around luminous and radio-quiet quasars, using narrow-band (NB) filters on 8-metre class optical telescopes (e.g. Cantalupo, Lilly & Haehnelt 2012; Cantalupo et al. 2014; Martin et al. 2014; Arrigoni Battaia et al. 2016) and spectroscopic observations (e.g. Christensen et al. 2006; North et al. 2012; Herenz et al. 2015). However, these surveys have revealed giant Ly α nebulae, spanning distances from the quasar larger than 100 physical kpc (pkpc), only in less than 10 per cent of the targets (e.g. Cantalupo et al. 2014; Hennawi et al. 2015; maximum projected linear sizes >300 pkpc), and emission on smaller scales (R ≲ 50–60 pkpc) have been detected only in about 50 per cent of the cases. This 50 per cent detection rate is likely due to a combination of limits of the observational techniques, as for instance NB filter losses, spectroscopic slit losses, point spread function (PSF) losses and, most importantly, dilution of the signal of the Ly α line into the continuum flux (both background and from the host galaxy) encompassed by the width of the filter (see also Borisova et al. 2016 for a discussion).

2022ApJ...927..149L__Cicone_et_al._2017_Instance_1

These trends make physical sense and agree with the limited previous measurements. Physically, elevated SFR/M ⋆ may trace more intense radiation fields and stronger heating of the gas, suggesting higher temperatures. The anticorrelation with M ⋆ may reflect the impact of dust shielding. Based on the existence of the mass–metallicity relation (e.g., Tremonti et al. 2004; Kewley & Ellison 2008), we expect the low-mass members of our sample to also have lower dust-to-gas ratios (e.g., Leroy et al. 2011; Rémy-Ruyer et al. 2014; Casasola et al. 2020) and more intense radiation fields. In literature studies, CO line ratios do appear enhanced in low-metallicity regions or galaxies (e.g., Lequeux et al. 1994; Bolatto et al. 2003; Druard et al. 2014; Kepley et al. 2016; Cicone et al. 2017, among many others). Higher SFR/L CO may indicate poorly shielded, low-metallicity gas in which the CO persists only in the core of a molecular cloud (e.g., see discussion in Glover & Clark 2012; Schruba et al. 2012; Bolatto et al. 2013b; Rubio et al. 2015). Alternatively, higher SFR/L CO can indicate more efficiently star-forming gas, which will often be denser gas with more nearby heating sources. These are both factors that can lead to higher line ratios, especially R 32 and R 31 (see Section 2). Given that our sample skews toward relatively massive and thus nearly solar metallicity targets, we expect that these density and heating effects likely represent the main drivers of the observed correlations. The correlations that we see agree with the results of Lamperti et al. (2020), who showed a correlation between SFR/L CO,low and R 31, and Yajima et al. (2021), who used a subset of the data we consider here and showed a correlation between R 21 and SFR/L CO,low. Qualitatively, Figure 5 echoes other results at low and high redshift that show a correlation between normalized star formation activity and excitation (e.g., Weiß et al. 2005; Bolatto et al. 2013b; Liu et al. 2021).

2022MNRAS.512.4280P__Umetsu_et_al._2016_Instance_1

The fifth force, propagated by the scalar degree of freedom, affects the Poisson equations associated to the Newtonian potential Φ, as well as the relativistic one, Ψ, according to (Kobayashi, Watanabe & Yamauchi 2015; Crisostomi & Koyama 2018; Dima & Vernizzi 2018), (1)$$\begin{eqnarray*} \frac{\text{d} \Phi (r)}{\text{d}r} = \frac{G M(r)}{r^2} \left[1+\frac{3}{4}Y_1\left(\frac{\rho (r)}{\bar{\rho }(r)}\right)\left(2+\frac{\text{d}\ln \rho }{\text{d}\ln r}\right)\right], \end{eqnarray*} $$(2)$$\begin{eqnarray*} \frac{\text{d} \Psi (r)}{\text{d}r} =\frac{G M(r)}{r^2}\left[1-\frac{15}{4}Y_2\left(\frac{\rho (r)}{\bar{\rho }(r)}\right)\right]. \end{eqnarray*} $$In the above equations, we have assumed spherical symmetry. $\bar{\rho }(r)$ is the (spatially) average density at radius r from the centre of the galaxy cluster, and Y1, Y2 correspond to the dimensionless fifth-force couplings. Finally, G is the Newton’s constant. Although the dynamics of member galaxies in the cluster is governed by the potential Φ, lensing is sourced by the combination (3)$$\begin{eqnarray*} \frac{\mathrm{ d}}{\mathrm{ d}r} \Phi _{\rm {lens}} = \frac{1}{2}\frac{\mathrm{ d}}{\mathrm{ d}r}(\Phi + \Psi). \end{eqnarray*} $$Therefore, kinematical observations allow for contraints on Y1, while lensing constrains both Y1 and Y2. The right-hand side of above equation can be expressed in terms of the density profile ρ(r) according to the relevant equations for Φ and Ψ above. The dominant source of pressureless matter density in the cluster comes from dark matter, which density we choose to model with a Navarro-Frenk-White (NFW) of Navarro, Frenk & White (1997) profile as (4)$$\begin{eqnarray*} \rho (r)=\frac{\rho _\text{s}}{r/r_\text{s}(1+r/r_\text{s})^2}, \end{eqnarray*} $$with ρs is a characteristic density and rs the radius at which the logarithmic derivative of the density profile takes the value −2. The NFW profile has been shown to provide an overall good agreement with observations and simulations over a broad range of scales in GR (e.g. Biviano et al. 2013; Umetsu et al. 2016; Peirani et al. 2017) and in MG (e.g. Lombriser et al. 2012a; Wilcox et al. 2016). Moreover, the GR analyses with lensing and internal kinematics of both clusters indicate that the total mass profile is well fitted by the NFW model (Biviano et al. 2013; Umetsu et al. 2016; Caminha et al. 2017; Sartoris et al. 2020). Under the assumption of a NFW profile, we can re-write the equation for the potential Φ in an effective way as (5)$$\begin{eqnarray*} \frac{\text{d}\Phi }{\text{d}r} \equiv \frac{G M_{\text{dyn}}}{r^2}=\frac{G}{r^2}\left[ M_{\rm {NFW}}(r)+M_1(r)\right], \end{eqnarray*} $$which serves as a definition of the dynamical mass Mdyn. Notice that, G here is still Newton’s constant as measure in the Solar system. The fifth-force contribution M1 is defined in terms of the NFW parameters as (6)$$\begin{eqnarray*} M_1(r)= M_{200}\frac{Y_1}{4}\frac{r^2(r_\text{s}-r)}{(r_\text{s}+r)^3}\times [\ln (1+c)- c/(1+c)]^{-1}. \end{eqnarray*} $$where c = r/rs is the concentration and M200 is the mass of a sphere of radius r200 enclosing an average density 200 times the critical density of the universe at that redshift. In a similar fashion, the relevant expression for the lensing mass can be found by computing (7)$$\begin{eqnarray*} M_{\text{lens}}(r) =\frac{r^2}{2G}\left[\frac{\text{d}\Psi }{\text{d}r}+\frac{\text{d}\Phi }{\text{d}r}\right]. \end{eqnarray*} $$$$\begin{eqnarray*} M_{\text{lens}}=M_{\text{NFW}}+\frac{r^2M_{200}\left[Y_1(r_\text{s}-r)-5Y_2(r_\text{s}+r)\right]}{4[\log (1+c_{200})-c_{200}/(1+c_{200})]}\frac{1}{(r_\text{s}+r)^{3}}, \end{eqnarray*} $$which can be effectively re-expressed in terms of the dynamical mass as (8)$$\begin{eqnarray*} M_{\text{lens}} \equiv M_{\text{dyn}}+M_2, \end{eqnarray*} $$with M2 the contribution from the fifth force defined through (9)$$\begin{eqnarray*} M_2=\frac{r^2M_{200}}{8(r_\text{s}+r)^{3}}\frac{Y_1(r-r_\text{s})-5Y_2(r_\text{s}+r)}{[\ln (1+c)-c/(1+c)]}. \end{eqnarray*} $$In view of the above equations, it is important to emphasize again that, although the fifth force effect enters the dynamical mass only through the coupling Y1, the lensing mass is affected by both Y1 and Y2. This is expected, since lensing is sourced by the combination of the two potentials Φ and Ψ, equation (3). Note also that, with gravitational lensing observations, one reconstructs the projected surface mass density profile Σ(R), where R is the projected radius from the cluster centre. We refer to e.g. Umetsu (2020) for an explicit discussion of the physics and mathematical framework.

2018AandA...615A..77L__XIII_2016_Instance_1

The last decade and a half has seen a revolution in the study of overdensities in the early Universe. While the study and careful characterization of large associations of galaxies in the local Universe has been possible for nearly a century, and in the intermediate redshift Universe for a significant fraction of that time (e.g., Shapley & Ames 1926; Shapley 1930; Zwicky 1937; Abell 1958; Zwicky et al. 1961), the study of their progenitors presented several practical problems which have prevented their study until relatively recently. The primary problem, inherent to the study of nearly all galaxy populations in the early Universe, is the extreme apparent faintness of galaxy populations at these distances. While some phenomena exist in the early Universe, such as quasars or radio galaxies, which are so powerful and intrinsically bright that they have been able to serve as beacons to early searches near the epoch of H I reionization (z ~ 5.5–10, Becker et al. 2001, 2015; Planck Collaboration XIII 2016), the bulk of the galaxy population residing in the early Universe does not contain such phenomena (Miley & De Breuck 2008; Ouchi et al. 2008; Lemaux et al. 2014b; Ueda et al. 2014; Talia et al. 2017). As such, the first searches for these more typical primeval galaxies were largely doomed to failure (Davis & Wilkinson 1974; Partridge 1974; Pritchet & Hartwick 1987; Parkes et al. 1994). It was not until the advent of the 10m-class ground-based telescopes largely used in conjunction with the Hubble Space Telescope (HST) that the prospect of detecting and characterizing moderate samples of such galaxies became even remotely feasible (e.g., Steidel et al. 1999; Shapley et al. 2003; Giavalisco et al. 2004; Stanway et al. 2004; Malhotra & Rhoads 2004; Malhotra et al. 2005; Vanzella et al. 2005, Le Fèvre et al. 2005). With this, the prospect of finding and characterizing analogs of the progenitors of the massive clusters and superclusters of galaxies scattered throughout the local Universe began to come within the realm of possibility.

2019MNRAS.489..855C__Husemann_et_al._2013_Instance_2

The size of ENLRs have been defined in different ways in the literature. Bennert et al. (2002) and Schmitt et al. (2003b) used the Hubble Space Telescope (HST) to obtain narrow band images of $\rm [O\, III]$, and adopted the maximum 3σ detected radius as the radius of the ENLR. This method is subject to the instrumental sensitivity limit that could be very different in different observations. Studies with long-slit spectroscopic observations define the radius based on isophote (Greene et al. 2011; Hainline et al. 2013, 2014), or the distance at which the ionization state changes from AGN to star-forming activities (Bennert et al. 2006a,b). The long-slit based observations also have drawbacks: the morphology of ENLR is sometimes irregular so that the derived size depends on the orientation of slits (Greene et al. 2011; Husemann et al. 2013). We have compared the measured size based on the IFU and the mock long-slit observation in Fig. 4 following the method discussed below. In most cases, long-slit observations tend to underestimate the true size of ENLR. IFU spectroscopic data allow us to use 2D maps to define the sizes of ENLRs. Common definitions include the radius of a specified $\rm [O\, III]$ surface brightness isophote (Liu et al. 2013, 2014), or the $\rm [O\, III]$ flux weighted radius (Husemann et al. 2013, 2014; Bae et al. 2017). We followed the same method as Liu et al. (2013) but chose a different threshold. The isophote threshold of 10−15$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$ was used for quasars related studies. This is suitable for such bright objects but are not as useful for fainter Syferts in our sample as it will leave a large number of AGN undetected. The typical 3σ depth of the MaNGA observation in $\rm [O\, III]$ surface brightness can reach 10−17$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$. For our AGN sample, the majority of AGN spaxels have surface brightnesses above 10−16$\rm erg\, s^{-1}cm^{-2}arcsec^{-2}$ which is thus adopted in this work as the threshold to define the sizes of the ENLRs (hereafter R16). If all spaxels are above this threshold, we extrapolated the fitted $\rm [O\, III]$ surface brightness profile to determine R16 (see Section 3.4 for more detail). It should be noted that the surface brightness can be affected by cosmological dimming, which has a scale factor of (1 + z)4 (Liu et al. 2013; Hainline et al. 2014). That is important for works trying to compare sample with different redshift, especially for high redshift quasars.

2019ApJ...871...58T__Charbonnel_&_Lagarde_2010_Instance_1

We derived stellar parameters, [C/M], and [N/M] using SLAM. To avoid bad fits at the edges of the parameter space, we exclude stars with spectral S/N in the g band less than 50, and metallicity less than −1.4. The derived C and N abundances are shown in Figure 8. Clearly, in the top panel, the CH-strong, CH-normal, and metal-poor field stars are separated, and their relative distribution in the N–C parameter space is similar to the case of APOGEE abundances (left panel of Figure 7): (1) metal-poor field stars form a sequence in the lower left of the top panel. As evolved stars ascend the RGB, C and N abundances may be changed by first dredge-up (Iben 1964, 1967) and extra mixing (Gratton et al. 2000; Charbonnel & Lagarde 2010). Given that for a typical halo/thick-disk star of 1 M⊙, the first dredge-up occurs around Teff = 5200 K (Boothroyd & Sackmann 1999), and most of our sample stars have K and log g 2.5, we infer that most stars have already undergone first dredge-up. On the other hand, the C and N abundances of these stars could be altered by extra mixing. Stars with brighter K-band absolute magnitudes tend to have higher [N/Fe] and lower [C/Fe] (middle and bottom panels of Figure 8), which is consistent with extra-mixing theory and observation (Gratton et al. 2000; Charbonnel & Lagarde 2010); (2) CH-normal stars show an enhanced median N abundance and slightly depleted median C abundance. Clearly, the median N abundance of CH-normal stars is enhanced compared to that of normal metal-poor field stars with similar C abundances. In other words, the enhanced N abundances in CH-normal stars cannot be explained by the extra-mixing effect alone. We notice that a few CH-normal stars may have low N abundances, probably due to large uncertainties when spectra of a particular type are scarce in the training set, i.e., high-N metal-poor stars. The statistical similarity between APOGEE C and N abundances and LAMOST-derived C and N abundances further strengthens our statement above.

2021AandA...655A..99D__Hernández_et_al._2010_Instance_1

The giant planet metallicity correlation supports the core-accretion scenario for the formation of planets (Pollack et al. 1996; Ida & Lin 2004; Mordasini et al. 2009), in which it is assumed that planetesimals are formed by the condensation of heavy elements. The discovery of this correlation has led to an increased interest on the abundances of other elements in planet hosts(e.g. Sadakane et al. 2002; Bodaghee et al. 2003; Beirão et al. 2005; Gilli et al. 2006; Ecuvillon et al. 2006; Bond et al. 2006, 2008; Robinson et al. 2006; Gonzalez & Laws 2007; Takeda et al. 2007; Delgado Mena et al. 2010; González Hernández et al. 2010, 2013; Kang et al. 2011; Brugamyer et al. 2011; Adibekyan et al. 2015; da Silva et al. 2015; Mishenina et al. 2016; Suárez-Andrés et al. 2018). Using the same sample of this study, Adibekyan et al. (2012b) found that the [X/Fe] ratios of Mg, Al, Si, Sc, and Ti both for giant and low-mass planet hosts are systematically higher than those of stars without detected planets at low metallicities ([Fe/H] ≲ from –0.2 to 0.1 dex depending on the element). Furthermore, this work confirmed the previous suggestion by Haywood (2009) that planets form preferentially in the thick disk rather than in the thin disk at lower metallicities. A plausible explanation for this behaviour is that if the amount of iron is low, it needs to be compensated with other elements that are important for planet formation, such as Mg and Si, and these elements are more abundant in the thick disk Adibekyan et al. (2012b,a). In a subsequent work, Delgado Mena et al. (2018) focused on heavier elements among the same sample of stars with and without planets, we found that planet hosts present higher abundances of Zn for [Fe/H] –0.1 dex, as a consequence of thick-disk stars having enhanced [Zn/Fe] ratios (Delgado Mena et al. 2017). Moreover, Delgado Mena et al. (2018) also found a statistically significant underabundance of Ba for low-mass planet hosts that had been previously suggested by Mishenina et al. (2016).

2022MNRAS.509.1959S__Nordlander_et_al._2019_Instance_1

However, the transition between the two extremes of modern (metal-rich) and primordial (metal-poor) star formation, and in particular the role of dust coupling and stellar radiation feedback at low metallicity, has thus far received limited exploration. Krumholz (2011) present analytical models for radiation feedback and predict a weak scaling of IMF peak mass with metallicity, while Myers et al. (2011) and Bate (2014, 2019) carry out radiation-hydrodynamic simulations of star formation over a metallicity range from $0.01{-}3\, Z_{\rm {\odot }}$ and find negligible effects on gas fragmentation. However, these studies do not explore lower metallicities, despite available evidence for the existence of a low-metallicity ISM in the past through the discovery of stars with metallicities as low as $10^{-4}\, \rm {Z_{\odot }}$ (Caffau et al. 2011; Starkenburg et al. 2018), as well as several others with $\rm {[Fe/H]} \lt -5$ (Christlieb et al. 2004; Keller et al. 2014; Frebel et al. 2015; Aguado et al. 2017, 2018; Ezzeddine et al. 2019; Nordlander et al. 2019). Coming from the opposite direction, Bromm et al. (2001), Omukai et al. (2005), and Omukai, Hosokawa & Yoshida (2010) consider the thermodynamics of gas of increasing metallicity, and find that dust and metal line cooling permits fragmentation to reach masses ≲1 M⊙ only once the metallicity exceeds ∼10−3.5 Z⊙. Dust is a more efficient coolant than metal lines, and permits fragmentation to lower masses at lower metallicity (e.g. Meece, Smith & O’Shea 2014; Chiaki & Yoshida 2020; Shima & Hosokawa 2021), but exactly by how much depends on the poorly known distribution of dust grain sizes in the early Universe (Schneider et al. 2006, 2012; Omukai et al. 2010; Schneider & Omukai 2010; Chiaki et al. 2015). However, the early Universe star formation models are fundamentally misanalogous to the modern ones that consider decreasing metallicity, in that the early Universe models consider dust solely as a coolant that enables fragmentation, whereas the modern ones assign it a more nuanced role, as both a source of cooling and later, once stellar feedback begins, a source of heating – a changeover that seems crucial to explaining why the IMF in the present-day Universe peaks at ${\sim}0.2\, \rm {M_{\odot }}$ rather than ${\sim}10^{-2}\, \rm {M_{\odot }}$ (Kroupa 2001; Chabrier 2003, 2005).

2022ApJ...939..117Z__Blandford_et_al._2019_Instance_1

Blazars are a subclass of active galactic nuclei (AGNs) with relativistic jets of high-energy particles pointing near our line of sight (e.g., Urry & Padovani 1995). Their nonthermal emission is generally detected across the entire electromagnetic spectrum from radio to γ-ray bands. Blazars are subclassified into flat-spectrum radio quasars (FSRQs) and BL Lac objects (BL Lacs), according to the equivalent width of the emission lines in their optical spectrum (Stickel et al. 1991; Stocke et al. 1991; Marcha et al. 1996). These two subclasses of blazars are thought to be intrinsically different, perhaps based on their accretion mode (Dermer & Giebels 2016). FSRQs have high luminosity and a thin and radiatively efficient black hole accretion disk (Malkan & Moore 1986), while BL Lacs are powered by an advection-dominated, low radiative efficiency accretion flow (Dermer & Giebels 2016; Blandford et al. 2019). The jet emission is relativistically beamed (Ghisellini 2019), with a Doppler boosting factor corresponding to a bulk Lorentz factor of several to greater than 10 (Pushkarev et al. 2009). In both cases, the broadband spectra consist of two broad humps, one peaking in the IR-to-X-ray regime and the other peaking in the γ-ray regime. The low-energy peak is believed to be due to synchrotron emission, while the high-energy peak is likely due to inverse Compton scattering of low-energy photons of either the same synchrotron photons (for BL Lacs) or external photons from the disk/BLR (for FSRQs) (e.g., Dutka et al. 2017). However, some blazars might not necessarily be detected in γ-rays (e.g., Paliya et al. 2017). Indeed, a recent study showed that blazars undetected in γ-rays are likely to have relatively smaller Doppler factors and more disk dominance (Paliya et al. 2017). In the case of strong Compton scattering, the beaming of γ-rays could be larger than, e.g., that seen in the radio (Dermer 1995), leading to the possible nondetection (or reduced detection efficiency) of γ-rays from sources not seen exactly pole-on.

2022AandA...659L...1L__Lellouch_et_al._2013_Instance_2

Without knowledge of nucleus shape and spin parameters (pole orientation and shape), a thermophysical model is pointless, and we instead adopted a NEATM (Near Earth Asteroid Thermal Model) model, used extensively for asteroids (Harris 1998) and TNOs (Müller et al. 2020, and references therein). NEATM is based on the asteroid standard thermal model (STM; Lebofsky et al. 1989) but accounts for phase angle effects; additionally, the temperature distribution is modified by an adjustable η−1/4 factor, which represents the combined and opposed effects of roughness (η 1) and thermal inertia (η > 1). For fixed surface (thermal inertia, roughness) and spin properties, η is also a function of the subsolar temperature, and, therefore, of the heliocentric distance (e.g., Spencer et al. 1989; Lellouch et al. 2013). Given the rh = 20 au distance of our measurements (and the expected large size of 2014 UN271), we adopted a beaming factor η = 1.175 ± 0.42, based on measurements of 85 Centaurs and TNOs (Lellouch et al. 2013, 2017). We also specified a bolometric emissivity ϵb = 0.90 ± 0.06 and a relative radio emissivity ϵr = ϵmm/ϵb = 0.70 ± 0.13, as inferred from combined Spitzer/Herschel/ALMA measurements of nine objects (Brown & Butler 2017; Lellouch et al. 2017). The lower-than-unity relative radio emissivity is interpreted as resulting from (i) the sounding of a colder dayside subsurface and (ii) the loss of outgoing thermal radiation due to volume scattering in the subsurface and/or Fresnel reflection at the surface. The few available radio observations of cometary nuclei also generally indicate radio emissivities lower than 1, for example ∼0.5 for Hale-Bopp (Fernández 2002) and 0.8 for 8P/Tuttle (Boissier et al. 2011). Comets are also found to have low thermal inertias (e.g., 10, 30, and 45 MKS for 8P/Tuttle, 22P/Kopff, and 9P/Tempel 1, respectively; Boissier et al. 2011; Groussin et al. 2009, 2013), consistent with a beaming factor, η, of order unity. Based on NEATM analysis of a large sample of comet nuclei observed with Spitzer at rh = 3.5–6 au, Fernández et al. (2013) find a mean η of 1.03 ± 0.11. The large 29P/Schwassmann-Wachmann nucleus (D = 65 km) has η = 1.1 ± 0.2 (Schambeau et al. 2021). These numbers are fully consistent with our choice of η. Given the values of rh, η, and ϵb, NEATM calculations indicate that the object’s spectral index over 224–242 GHz is 1.93, slightly lower than the Rayleigh-Jeans limit of 2.

2020MNRAS.492.4727C__Rees_1976_Instance_1

A strong property of the isothermal gas that defines the interstellar medium (ISM) is the absence of a characteristic mass scale owing to the scale-free nature of gravity. From the collapse condition of an isothermal sphere, one can derive the Jeans mass as (2)$$\begin{eqnarray*} M_{\mathrm{J}} = \frac{4 \pi}{3} \rho \left(c_{\mathrm{s}} t_{\rm ff}\right)^3 \end{eqnarray*}$$with cs being the sound speed, given by (3)$$\begin{eqnarray*} c_{\mathrm{s}} = \sqrt{\frac{k_{\mathrm{B}} T}{\mu \, m_{\mathrm{H}}}} \end{eqnarray*}$$and the free-fall time tff is defined here as (4)$$\begin{eqnarray*} t_{\mathrm{ff}} = \sqrt{\frac{3\pi }{32G \rho }}. \end{eqnarray*}$$One sees immediately that for an isothermally collapsing gas, we cannot choose a unique characteristic density that would result in a unique characteristic mass. The larger the density of the gas during collapse and fragmentation, the smaller the Jeans mass. At very large densities, though, owing to the increased dust absorption coefficient, the gas becomes opaque to its own radiation. This is sometimes referred to as the opacity limit (Low & Lynden-Bell 1976; Rees 1976). At this point, the fragmentation is halted, setting a scale below which no fragments form. It is possible to estimate the characteristic density at which this process occurs by requiring the optical depth of one Jeans radius to be unity (5)$$\begin{eqnarray*} \tau = \kappa _{\rm dust} \rho R_{\rm J} = 1\,\,\,{\rm with}\,\,\,R_{\rm J} = c_{\mathrm{s}} t_{\rm ff}. \end{eqnarray*}$$For typical molecular clouds conditions in the Milky Way with T = 10 K, μ = 2.2, and κdust = 0.1 cm2 g−1, we find the critical density that defines the opacity limit (6)$$\begin{eqnarray*} \rho _{\rm crit} = \frac{32 G}{3 \pi \kappa _{\rm dust}^2 c_\mathrm{ s}^2 } \simeq 5 \times 10^{-14} \,{\rm g}\,{\rm cm}^{-3} . \end{eqnarray*}$$At this critical density, we obtain a unique Jeans mass of the order of (7)$$\begin{eqnarray*} M_{\mathrm{J}} = 0.670 \frac{c_{\mathrm{s}}^3}{\sqrt{G^3 \rho _{\mathrm{crit}}}} \approx 6 \times 10^{-4} \, \mathrm{M_\odot }. \end{eqnarray*}$$Note that the critical density can also be derived using slightly more complicated arguments, leading to a very similar value for typical Milky Way conditions (Krumholz 2017). This mass corresponds to the smallest gas clumps that can overcome the pressure gradients and collapse. At this characteristic density, the gas evolution transitions from isothermal to adiabatic, which prevents the collapse of smaller fragments, even at higher densities. The Jeans mass at the opacity limit is obviously much smaller than the observed characteristic mass of the IMF. It does not even correspond to the minimal mass of a star, as the smallest of these fragments will not be able to collapse enough to reach stellar densities in their centres.

2016AandA...591A..13V__Giovannini_et_al._2013_Instance_1

The first direct proof of the existence of magnetic fields in large-scale extragalactic environments, i.e., galaxy clusters, dates back to the 1970s with the discovery of extended, diffuse, central synchrotron sources called radio halos (see, e.g., Feretti et al. 2012 for a review). Later, indirect evidence of the existence of intracluster magnetic fields has been given by several statistical studies on the effect of the Faraday rotation on the radio signal from background galaxies or galaxies embedded in galaxy clusters (Lawler & Dennison 1982; Vallée et al. 1986; Clarke et al. 2001; Johnston-Hollitt 2003; Clarke 2004; Johnston-Hollitt & Ekers 2004). On scales up to a few Mpc from the nearest galaxy cluster, possibly along filaments, only a few diffuse synchrotron sources have been reported (Harris et al. 1993; Bagchi et al. 2002; Kronberg et al. 2007; Giovannini et al. 2013, 2015). Magnetic fields with strengths on the order of 10-15 G in voids might be indicated by γ-ray observations (see Neronov & Vovk 2010; Tavecchio et al. 2010; Takahashi et al. 2012, 2013; but see Broderick et al. 2014a,b for alternative possibilities). Nevertheless, up to now, a robust confirmed detection of magnetic fields on scales that are much larger than clusters is not available. Stasyszyn et al. (2010) and Akahori et al. (2014a) investigated the possibility of statistically measuring Faraday rotation from intergalactic magnetic fields with present observations, showing that only the Square Kilometre Array (SKA) and its pathfinders are likely to succeed in this respect. By comparing the observations with single-scale magnetic field simulations, Pshirkov et al. (2015) infer an upper limit of 1.2 nG for extragalactic large-scale magnetic fields, while the Planck Collaboration XIX (2016) derived a more stringent upper limit for primordial large-scale magnetic fields of B 0.67 nG from the analysis of the Cosmic Microwave Background (CMB) power spectra and the effect on the ionization history (but see also Takahashi et al. 2005; Ichiki et al. 2006).

2021ApJ...915L...8D__Chen_et_al._2020_Instance_1

Magnetic field fluctuations in the solar wind are highly turbulent. The measured power spectral density (PSD) of the fluctuating magnetic field always exhibits power laws k−α, where k is the wavenumber, and α is the spectral index. A single spacecraft measures the PSD as a function of f−α in the frequency domain, which can be converted to the spatial domain under the Taylor hypothesis. According to the physical processes at different scales, the PSD in the solar wind can be divided into several segments, which can be fitted with different α. The inertial range, which is dominated by magnetohydrodynamic (MHD) turbulence, follows the cascade models with spectral indices αi from around 3/2 to 5/3 (Bruno & Carbone 2013; Chen et al. 2020). The PSDs become steepened below the ion scales (ion thermal gyroradius ρi or ion inertial length di), where kinetic mechanisms should be taken into account. Sometimes a sharp transition range is observed with αt ∼ 4 (Sahraoui et al. 2010; Bowen et al. 2020a). This transition range may be caused by imbalanced turbulence (Voitenko & Keyser 2016; Meyrand et al. 2021), energy dissipation of kinetic waves (Howes et al. 2008), ion-scale coherent structures (Lion et al. 2016), or a reconnection dominated range (Mallet et al. 2017). At smaller scales, a flatter sub-ion kinetic range forms with the spectral index αk ∼ 7/3, which can be explained as the MHD Alfvénic turbulence developing into a type of kinetic wave turbulence, e.g., kinetic Alfvén waves (KAWs; Schekochihin et al. 2009) or whistler waves (Cho & Lazarian 2004). Intermittency in the kinetic range could lead to an −8/3 spectrum (Boldyrev & Perez 2012; Zhao et al. 2016). Ion-cyclotron-wave (ICW) turbulence could lead to a steeper −11/3 spectrum (Krishan & Mahajan 2004; Galtier & Buchlin 2007; Meyrand & Galtier 2012; Schekochihin et al. 2019).The kinetic range always behaves as the KAW turbulence with the slope of −2.8 in the near-Earth space (Bale et al. 2005; Chen et al. 2013; Chen 2016). The spectral indices increase again beyond the electron kinetic scales in observations, indicating the conversion of turbulence energy to electrons (Sahraoui et al. 2009; Alexandrova et al. 2012; Chen et al. 2019) or transitions to a further cascade (Schekochihin et al. 2009; Chen & Boldyrev 2017). In simulations, Meyrand & Galtier (2013) obtained a −8/3 spectrum at electron scales under the 3D electron–MHD model.

2015ApJ...811L..32H__Liewer_et_al._2001_Instance_1

In this Letter, we directly test the relationship between proton kinetic instabilities and plasma turbulence in the solar wind using a hybrid expanding box model that allows us to study self-consistently physical processes at ion scales. In the hybrid expanding box model, a constant solar wind radial velocity vsw is assumed. The radial distance R is then , where R0 is the initial position and is the initial value of the characteristic expansion time Transverse scales (with respect to the radial direction) of a small portion of plasma, comoving with the solar wind velocity, increase ∝ R. The expanding box uses these comoving coordinates, approximating the spherical coordinates by the Cartesian ones (Liewer et al. 2001; Hellinger & Trávníček 2005). The model uses the hybrid approximation where electrons are considered as a massless, charge-neutralizing fluid and ions are described by a particle-in-cell model (Matthews 1994). Here, we use the two-dimensional (2D) version of the code, fields and moments are defined on a 2D x–y grid 2048 × 2048, and periodic boundary conditions are assumed. The spatial resolution is Δx = Δy = 0.25dp0, where is the initial proton inertial length (vA0: the initial Alfvén velocity, Ωp0: the initial proton gyrofrequency). There are 1024 macroparticles per cell for protons that are advanced with a time step , while the magnetic field is advanced with a smaller time step The initial ambient magnetic field is directed along the radial z-direction, perpendicular to the simulation plane , and we impose a continuous expansion in the x- and y-directions. Due to the expansion, the ambient density and the magnitude of the ambient magnetic field decrease as (the proton inertial length dp increases ∝ R; the ratio between the transverse sizes and dp remains constant; the proton gyrofrequency Ωp decreases as ∝R−2). A small resistivity η is used to avoid accumulation of cascading energy at grid scales; initially, we set (μ0 being the magnetic permittivity of vacuum) and η is assumed to be The simulation is initialized with an isotropic 2D spectrum of modes with random phases, linear Alfvén polarization ( ), and vanishing correlation between magnetic and velocity fluctuation. These modes are in the range 0.02 ≤ kdp ≤ 0.2 and have a flat one-dimensional (1D) power spectrum with rms fluctuations = 0.24 B0. For noninteracting zero-frequency Alfvén waves, the linear approximation predicts (Dong et al. 2014). Protons initially have the parallel proton beta and the parallel temperature anisotropy as typical proton parameters in the solar wind in the vicinity of 1 AU (Hellinger et al. 2006; Marsch et al. 2006). Electrons are assumed to be isotropic and isothermal with βe = 0.5 at t = 0.

2021AandA...654A.132B__Davies_et_al._2014b_Instance_1

We can use the equivalent width of Hα (EWHα, see Table 4) to put additional constraints on the recent star formation history of the AGNs. To do so, we first need to estimate the largest fraction of the Hα luminosity that could arise from star formation, and for this we use the group of AGNs with the highest EWHα. There are a number of reasons why AGNs could have lower EWHα, but the maximum values will only be found when both AGN and star formation contribution are maximal. The group of six AGNs with the highest EWHα consists of ESO 137-G034, NGC 3081, NGC 2110, NGC 7582, NGC 2992, and NGC 5728, and their median EWHα is 70 Å. These also tend to have the highest log [OIII]/Hβ, with a median ratio of 1.07. Similarly, their median log [NII]/Hα is 0.01. To assess the star formation contribution to the Hα flux, we consider lines from the most extreme AGN photoionisation models of Groves et al. (2004), to the location of solar metallicity star-forming galaxies (see also Davies et al. 2014b). Since the AGNs are very close to the highest [OIII]/Hβ ratios that the models can produce, we find that at most 10% of their Hα flux could be due to star formation. Applying this correction reduces the EWHα that is associated with star formation to 7 Å. We also need to make a correction for the old stellar population, since EWHα in models compares the line flux to the continuum due to stars associated with the line emission. We find that 5% of the continuum is associated with young stars. We therefore estimate that the maximum EWHα associated with the most recent star-forming episode is 7 Å/5%, which is 140 Å. Comparing this to Starburst99 models (specifically Figs. 83 and 84 in Leitherer et al. 1999) rules out continuous star formation since it would imply a timescale exceeding several Gyr, inconsistent with the stellar population synthesis results. Instead, it means that the recent star formation must have ceased. Based on the rate at which the EWHα falls after star formation stops, we estimate that the end of star formation must have typically happened at least 6 Myr prior.

2022AandA...662A...8M__Shu_et_al._1987_Instance_1

Even before studying the relationship between the IMF and the CMF, it is important to realize that how the IMF originates from the observed CMF depends directly on the definition of the cores, assumed to be the gas mass reservoir used for the formation of each star or binary system. As shown by Louvet et al. (2021), defining this mass reservoir may seem obvious in the observed map of a cloud, but core characteristics (size, mass) depend heavily on the spatial scales probed by the observations. In addition, the theoretical definition of cores also depends on whether the star-formation scenario is quasi-static or dynamic. In the former scenario, cores are gas condensations sufficiently dense to be on the verge of gravitational collapse, and they convert the core gas into stars (Shu et al. 1987; Chabrier 2003; McKee & Ostriker 2007; André et al. 2014). After a quasi-static phase of concentration of the cloud gas into cores, cores become distinct from their surrounding cloud and start to collapse, and their future stellar content becomes independent of the properties of the parental cloud. In the latter scenario, dynamics play a major role during all phases of the star-formation process (e.g., Ballesteros-Paredes et al. 2007; Hennebelle & Falgarone 2012; Padoan et al. 2014). In particular, global infall of filament networks and gas inflow toward cores are expected to be important drivers of star formation (e.g., Smith et al. 2009; Vázquez-Semadeni et al. 2019; Padoan et al. 2020). In this framework, filaments, cores, and stellar embryos simultaneously accrete gas, and the gas reservoir associated with star formation largely exceeds the extent of the observed cores. This so-called clump-fed scenario was proposed in various recent papers and described in detail in the review by Motte et al. (2018a, see references therein). One of the main objectives of the ALMA-IMF Large Program is to discriminate between the quasi-static and dynamic scenarios by quantifying the role of cloud kinematics in defining core mass and in possibly changing it over time.

2021AandA...654A.126B__Hotta_(2017)_Instance_1

Analytical and semianalytical approaches have been developed to describe this process and estimate the width of the overshooting layer (e.g., Schmitt et al. 1984; Zahn 1991; Rempel 2004). With the improvement of computational methods and resources, an increasing number of studies have been devoted to numerical simulations of convection and overshooting using realistic stellar conditions (geometry, luminosity, thermal diffusivity, equation of state, opacities, etc.). A commonly used tactic to increase the efficiency and improve the stability of these simulations is to artificially increase the luminosity (or nuclear energy for convective cores or burning shells) and to modify the thermal diffusivity of the reference stellar model. This tactic is common and has been used, for example, in Rogers et al. (2006, 2013), Meakin & Arnett (2007), Tian et al. (2009), Brun et al. (2011, 2017), Hotta (2017), Cristini et al. (2017), Edelmann et al. (2019), Horst et al. (2020). This approach is used to increase the Mach number of the convective flow, reducing the disparity between advective and acoustic timescales, improving the efficiency of time-explicit codes limited by the Courant–Friedrich–Levy constraint. It is also used to provide numerical stability or to accelerate the thermal relaxation. But no examination of its potentially far-reaching impact has been conducted. Rempel (2004) pointed out that enhanced energy flux in numerical simulations could lead to unrealistically vigourous convection, which could impact the properties of the overshooting layer and could explain some of the discrepancies between analytical models and numerical simulations. Numerical simulations also suggest an increase in the overshooting depth with increasing flux (Hotta 2017; Käpylä 2019). Determining scaling laws of the overshooting depth as a function of the energy input could thus allow for an extrapolation of the results to more realistic stellar conditions and help to estimate the overshooting depth in real stars, as suggested by Hotta (2017), for example, for the Sun. But Käpylä (2019) also shows that an artificial modification of the heat conductivity in the radiative and overshooting regions could impact the overshooting process. In some computational studies, both the luminosity and the thermal diffusivity are enhanced by the same factor to ensure that the thermal structure is unchanged compared to the reference stellar structure and with the expectation that the larger thermal diffusivity counterbalances the larger energy flux. This procedure has been proposed as a way to provide a good representation of the true dynamics of the system (e.g., Rogers et al. 2006, 2013; Tian et al. 2009). But this expectation has never been demonstrated. Another expectation concerns internal waves, excited by convective motions and by flows penetrating the convective boundary. Simulations with artificially modified luminosity and thermal diffusivity are also used to perform the analysis of internal waves, either for convective envelopes (e.g., Rogers et al. 2006; Brun et al. 2011; Alvan et al. 2014) or for convective cores (e.g., Rogers & McElwaine 2017; Edelmann et al. 2019; Horst et al. 2020). None of these works have examined whether the wave spectrum of a realistic star is accurately predicted by such simulations.

2019ApJ...882...97P__Warmuth_&_Mann_2016_Instance_1

The RADYN code (Carlsson & Stein 1992, 1995, 1997; Allred et al. 2015) is a one-dimensional radiative hydrodynamic code that can be used to study the interaction of particle beams with the solar atmosphere. It uses the Fokker–Planck formalism (McTiernan & Petrosian 1990), which takes into account the beam energy losses due to Coulomb collisions and pitch-angle diffusion when incorporating relativistic effects. RADYN includes a six-level hydrogen atom, a nine-level helium atom, and a six-level calcium atom. A return current has also been included in the simulations. We generated a set of models that simulates the conditions in the solar atmosphere during weak to intense WLFs. The beam fluxes used had values of 3 × 109, 1 × 1010, and 3 × 1010 erg cm−2 s−1, while the low-energy cutoff EC covered the parameter space where flare values are usually found (20–120 keV; Warmuth & Mann 2016). The spectral index δ was equal to 3 for all models. The beams were applied continuously and the outputs were analyzed at t = 20 s. This value is consistent with the X-ray analysis of the best observed type II WLF to date (Procházka et al. 2018). The initial atmosphere used in this work has the transition region placed at a height of 1200 km above the photospheric floor and has a coronal temperature of 3 MK at 10 Mm (QS.SL.HT loop described in Allred et al. 2015). The beams were injected at the top of a half-loop with a Gaussian distribution with an HWHM of 235. Line synthesis was carried out using the RH code (Uitenbroek 2001) incorporating partial redistribution that is particularly important for resonance line profiles. We used the 20-level hydrogen atom and the 6-level calcium atom to produce synthetic spectra for the Lyman and Balmer line and continuum diagnostics. A VOIGT profile was used for Ca ii K line, Lyman γ the higher-order Lyman lines. The Ca ii H and Lyα and β profiles were modeled in PRD. The Balmer lines had profiles of type VOIGT_VCS_STARK, which incorporates the unified Stark effect theory (Kowalski et al. 2017). The spectra were synthesized by setting a minimal spectral resolution of 0.05 nm.

2017ApJ...835..101H__Vanderbeke_et_al._2014_Instance_1

In the present survey of GCSs in BCGs, we use the color index (from here on we drop the accents on the SDSS indices). In the following discussion it will be useful to have a calibration of this index versus cluster metallicity [Fe/H]. To do this, we would ideally need to have GC photometry of the same clusters in both the Kron-Cousins and SDSS systems, in addition to spectroscopically based metallicity measurements. At present, there are no ideal solutions to that problem. Galaxies satisfying all three of these criteria are rare; in principle the Milky Way GC databases could be used, but cluster-to-cluster foreground reddenings differ strongly, the published SDSS indices (Vanderbeke et al. 2014) show considerable scatter versus metallicity, and the variety of studies from which the UBVRI indices were derived are completely different from the SDSS survey, so that aperture-size mismatches are significant. Similar problems affect the M31 GC sample. The best option at the present time for developing a transformation is likely to be from the nearby early-type giant galaxy NGC 5128: here, UBVRI photometry is available from Peng et al. (2004), griz photometry from Sinnott et al. (2010), and [Fe/H] values derived through from Woodley et al. (2010); these [Fe/H] values are in turn well correlated with the Sloan-system spectroscopic index [MgFe]’ (see Woodley et al.). We have extracted the GCs in common from these three catalogs, with the results shown in Figure 1. The great majority of these GCs lie well outside the central few kiloparsecs of NGC 5128 and thus are unaffected by the well-known dust lane. We have therefore applied only the foreground reddening of the Galaxy, for which we adopt (Cardelli et al. 1989) to obtain the intrinsic colors. We note, however, that the UBVRI measurements were done on aperture diameters corrected to through median curves of growth (Peng et al. 2004), while the griz measures were done through apertures (Sinnott et al. 2010), which means that a small aperture mismatch may exist here as well that affects the zero-point of .

2020ApJ...904...81G__Nariyuki_&_Hada_2007_Instance_1

Alfvén waves of arbitrary amplitude with constant total pressure are known to provide an exact solution to the compressible magnetohydrodynamic (MHD) system in a homogeneous plasma, in that nonlinearities are turned off and there no couplings with compressible modes. However, such a dynamical system is linearly unstable to parametric instabilities and large-amplitude Alfvén waves are known to decay into compressible and secondary Alfvénic modes through three- or four-wave resonances that lead to a variety of parametric instabilities, depending on the plasma beta and dispersive effects, such is the case of parametric decay (Galeev & Oraevskii 1973; Derby 1978), modulational, and beat instabilities (Sakai & Sonnerup 1983; Wong & Goldstein 1986; Jayanti & Hollweg 1993; Nariyuki & Hada 2007). Parametric instabilities of Alfvén waves (or of a spectrum of Alfvén waves) have been widely studied over the years through theoretical approaches (Goldstein 1978; Jayanti & Hollweg 1993; Malara & Velli 1996), and numerical simulations adopting both MHD (Ghosh et al. 1994; Malara et al. 2000; Del Zanna et al. 2001; Tenerani et al. 2017) and kinetic models (Terasawa et al. 1986; Matteini et al. 2010; Nariyuki et al. 2012; Verscharen et al. 2012), although most often in one-dimensional setups. In particular, the traditional parametric decay instability has attracted much attention over the years in the context of both turbulence and plasma heating. This type of decay is most efficient at low values of the plasma beta and it essentially involves the decay of a pump Alfvén wave into a lower-frequency reflected Alfvén wave and a forward sound wave. For this reason, parametric decay remains an appealing process because it provides a natural mechanism for the production of reflected modes, which is essential for the triggering of a turbulent cascade. Indeed, recently it has been proposed as a viable mechanism to initiate the turbulent cascade in the solar wind acceleration region (Chandran 2018; Réville et al. 2018), while global MHD simulations of the solar wind have also shown that the parametric decay instability can contribute substantially to solar wind heating and acceleration, thanks to the generation of compressible modes that, in the absence of kinetic effects, naturally steepen into shocks (see, e.g., Shoda et al. 2019). The traditional parametric decay has been also invoked as a possible source for the generation of inward modes and solar wind turbulence in the inner heliosphere, where an increasing content of reflected waves (cross-helicity) and an evolving turbulent spectrum are observed with increasing heliocentric distance (Bavassano et al. 2000). However, expansion effects are known to inhibit its development, essentially because the parametric decay process is strongly suppressed as the plasma beta increases at larger heliocentric distances (Tenerani & Velli 2013, 2020; Del Zanna et al. 2015). Temperature anisotropies can destabilize the parametric decay at values of the plasma beta approaching unity and above, but the anisotropy in the solar wind is not large enough to affect the instability significantly (Tenerani et al. 2017).

2020MNRAS.498.1801K__Gundlach_et_al._2011_Instance_1

Water ice is ubiquitous in the cold regions of the Universe, owing to the fact that hydrogen and oxygen are the two most abundant elements to form a solid such as icy dust particles and comets. It is, therefore, commonly accepted that the essential component of dust particles and planetesimals in protoplanetary discs is water ice beyond the so-called snow line, at which the temperature of gas is low enough for water vapour to condense into ices (e.g. Cyr, Sears & Lunine 1998). Reactive accretion of water ice from hydrogen and oxygen atoms on the surface of dust particles takes place in the dense core of molecular clouds where the growth of dust particles has been observed by scattering of stellar radiation (Steinacker et al. 2010). It is worthwhile noting that laboratory experiments on the coagulation growth of water-ice particles have a long history outside astronomy and planetary science, since coagulation is observed in daily life and is a plausible route to the formation of snowflakes (e.g. Faraday 1860; Hosler, Jensen & Goldshlak 1957). Recent works on laboratory measurements of cohesion between crystalline water-ice particles at vacuum conditions provided encouraging results that dust particles composed of water ice might be much more cohesive than previously believed (Gundlach et al. 2011; Gundlach & Blum 2015; Jongmanns et al. 2017). Form a theoretical point of view, Chokshi, Tielens & Hollenbach (1993) demonstrated that the JKR theory of elastic contact formulated by Johnson, Kendall & Roberts (1971) is a powerful tool for better understanding of dust coagulation. Numerical simulations incorporating the JKR theory have shown that dust aggregates consisting of submicrometre-sized water-ice particles proceed with coagulation growth even at a collision velocity of 50 m s−1 (Wada et al. 2009, 2013). As a result, the majority of recent studies on dust coagulation and planetesimal formation assume that silicate aggregates are disrupted by mutual collision at a velocity of vdisrupt ∼ 1 m s−1, but icy aggregates at vdisrupt ∼ 10 m s−1 (e.g. Birnstiel, Dullemond & Brauer 2010; Vericel & Gonzalez 2019). Such a trendy assumption led Drążkowska & Alibert (2017) to propose planetesimal formation by the ‘traffic jam’ effect at the snow line, provided that sticky water-ice particles grow faster and thus drift toward the central star faster than less-sticky bare silicate particles, implying that aggregates of the former catch up the latter at the snow line, which results in a traffic jam. However, we argue that the importance of water ice to dust coagulation is still open to debate, since water ice is not necessarily stickier than other materials such as silicates and complex organic matter (Kimura et al. 2015, 2020a; Musiolik & Wurm 2019).

2016MNRAS.463.3204R__Trautman_1967_Instance_1

Since the perturbation in equation (22) is not conservative, we shall focus on the extension of Noether's theorem to non-conservative systems by Djukic & Vujanovic (1975). It must be $F_i-q^\prime _if\ne 0$ for the conservation law to hold (Vujanovic, Strauss & Jones 1986). For the case of non-conservative systems the generators Fi, f, and the gauge Ψ need to satisfy the following relation: (29) \begin{eqnarray} &&{\sum _i\left\lbrace \left( \frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {q_i}} \right) F_i + \left(\frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {q^\prime _i}} \right)( {F}^\prime _i - q^\prime _i{f}^\prime ) + Q_i(F_i-q^\prime _if)\right\rbrace} \nonumber\\ &&{\quad+ f^\prime \scr {L} + f\frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {\tau }} = {\Psi }^\prime .} \end{eqnarray} This equation and the condition $F_i-q^\prime _if\ne 0$ furnish the generalized NBH equations (Trautman 1967; Djukic & Vujanovic 1975; Vujanovic et al. 1986). The NBH equations involve the full derivative of the gauge function and the generators with respect to τ, meaning that equation (29) depends on the partial derivatives of Ψ, Fi, and f with respect to time, the coordinates, and the velocities. By expanding the convective terms the NBH equations decompose in the system of Killing equations: (30) \begin{eqnarray} &&{ \scr {L} \frac{\mathrm{\partial} {f}}{\mathrm{\partial} {q_j^\prime }} +\sum _i \frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {q^\prime _i}}\left( \frac{\mathrm{\partial} {F_i}}{\mathrm{\partial} {q_j^\prime }} - q^\prime _i\frac{\mathrm{\partial} {f}}{\mathrm{\partial} {q_j^\prime }} \right) = \frac{\mathrm{\partial} {\Psi }}{\mathrm{\partial} {q_j^\prime }},} \nonumber \\ &&{ \frac{\mathrm{\partial} {}}{\mathrm{\partial} {\tau }}(f\scr {L} - \Psi ) + \sum _i \Bigg\lbrace \frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {q_i}}F_i + \scr {L}\frac{\mathrm{\partial} {f}}{\mathrm{\partial} {q_i}}q_i^\prime + Q_i(F_i-q_i^\prime f)+ \frac{\mathrm{\partial} {\scr {L}}}{\mathrm{\partial} {q_i^\prime }}} \nonumber \\ &&{\times\, \left[ \frac{\mathrm{\partial} {F_i}}{\mathrm{\partial} {\tau }} - q_i^\prime \frac{\mathrm{\partial} {f}}{\mathrm{\partial} {\tau }} + \sum _j\left( \frac{\mathrm{\partial} {F_i}}{\mathrm{\partial} {q_j}}q_j^\prime - q_i^\prime q_j^\prime \frac{\mathrm{\partial} {f}}{\mathrm{\partial} {q_j}} \right) \right] - \frac{\mathrm{\partial} {\Psi }}{\mathrm{\partial} {q_i}}q_i^\prime \Bigg \rbrace = 0.}\nonumber\\ \end{eqnarray} The system (30) decomposes in three equations that can be solved for the generators Fρ, Fθ, and f given a certain gauge. If the transformation defined in equation (26) satisfies the NBH equations, then the system admits the integral of motion (28).

2017MNRAS.469.2662D__Morales_et_al._2012_Instance_1

A well-studied way to look at antenna spectral requirements is from the perspective of foreground avoidance in power spectrum space. In the avoidance scheme, smooth-spectrum foregrounds should, in the ideal case, occupy a wedge–shaped region of the two–dimensional power spectrum space (where the wavenumber k can be decomposed into k⊥ and $k_\Vert$ that are the transverse and line-of-sight wave numbers, respectively) whereas the remaining area – the so-called EoR window – is dominated by the 21 cm emission (Datta, Bowman & Carilli 2010; Morales et al. 2012; Trott, Wayth & Tingay 2012; Vedantham, Udaya Shankar & Subrahmanyan 2012; Thyagarajan et al. 2013; Liu, Parsons & Trott 2014a,b). Sources have most of their emission at low k∥ values although, due to the inherent chromatic interferometric response, this area increases with baseline length to resemble a characteristic wedge-like shape (Parsons et al. 2012; Trott et al. 2012; Vedantham et al. 2012; Liu et al. 2014a,b; Thyagarajan et al. 2015). In the most optimistic scenario, the EoR power spectrum can be directly measured in the EoR window, whose boundaries are set by the so-called horizon limit, i.e. the maximum delay that an astrophysical signal can experience, given by the separation of the two receiving elements. In practice, the boundaries of the EoR window can be narrowed by a number of mechanisms that spread power from the foreground dominated region into the EoR window, in particular calibration errors (Barry et al. 2016; Patil et al. 2016), leakage of foreground polarization (Bernardi et al. 2010; Jelić et al. 2010; Moore et al. 2013; Asad et al. 2015, 2016) and intrinsic chromaticity of the instrumental response. Recent attention has indeed been given to simulate and characterize the element response, particularly for the HERA (DeBoer et al. 2017), realizing that it may be one of the critical items responsible for spilling power from the wedge into the EoR window.

2019ApJ...875...90L__Velli_et_al._2015_Instance_3

When energy flows from the interior of the Sun outward into the solar atmosphere, why is the Sun’s outer atmosphere, the corona, much hotter than the inner atmosphere, the underlying chromosphere and photosphere? This is the long-standing problem of the coronal heating, which is one of the eight key mysteries in modern astronomy (Kerr 2012). For about 80 yr since the discovery of the extremely hot corona around the late 1930s (Grotian 1939; Edlen 1945), people have worked hard on addressing this issue, and great advances have been made in observation and theoretical studies (Parnell & De Moortel 2012; Amari et al. 2015; Arregui 2015; Cargill et al. 2015; De Moortel & Browning 2015; Jess et al. 2015; Klimchuk 2015; Longcope & Tarr 2015; Peter 2015; Schmelz & Winebarger 2015; Velli et al. 2015; Wilmot-Smith 2015). Especially during recent decades, high-resolution observations of solar super-fine structures indicate that small spicules, minor hot jets along small-scale magnetic channels from the low atmosphere upwards to the corona, petty tornados and cyclones, and small explosive phenomena such as mini-filament eruptions and micro- and nano-flares—all of these small-scale magnetic activities contribute greatly to coronal heating (De Pontieu et al. 2011; 2018; Zhang & Liu 2011; Parnell & De Moortel 2012; Klimchuk 2015; Peter 2015; Schmelz & Winebarger 2015; Henriques et al. 2016; Li et al. 2018a). Additionally, contributions of MHD waves to heating the corona have been observationally illustrated (van Ballegooijen et al. 2011; Jess et al. 2015; Kubo et al. 2016; Morton et al. 2016; Soler et al. 2017; Morgan & Hutton 2018). Meanwhile, with the progress of observational studies, two groups of theoretical models, magnetic reconnection models and magnetohydrodynamic wave models, have traditionally attempted to explain coronal heating, but so far no models can address the key mystery perfectly (van Ballegooijen et al. 2011; Arregui 2015; Cargill et al. 2015; Peter 2015; Velli et al. 2015; Wilmot-Smith 2015). Maybe we do not need to intentionally take to heart such the classical dichotomy, because waves and reconnections may interact with each other (De Moortel & Browning 2015; Velli et al. 2015). Additionally, statistical studies may look at coronal heating from a comprehensive perspective. Li et al. (2018b) found that the long-term variation of the heated corona, which is represented by coronal spectral irradiances, and that of small-scale magnetic activity are in lockstep, indicating that the corona should statistically be effectively heated by small-scale magnetic activity. Observational and theoretical model studies through heating channels and modes, and statistical studies by means of heating effect (performance of the heated corona), both suggest that coronal heating originates from small-scale magnetic activity.

2015MNRAS.452.2731S__Stroe_et_al._2013_Instance_1

The H α studies of Umeda et al. (2004) and Stroe et al. (2014a, 2015) are tracing instantaneous (averaged over 10 Myr) SF and little is known about SF on longer time-scales and the reservoir of gas that would enable future SF. An excellent test case for studying the gas content of galaxies within merging clusters with shocks is CIZA J2242.8+5301 (Kocevski et al. 2007). For this particular cluster unfortunately, its location in the Galactic plane, prohibits studies of the rest-frame UV or FIR tracing SF on longer time-scales, as the emission is dominated by Milky Way dust. However, the rich multiwavelength data available for the cluster give us an unprecedented detailed view on the interaction of their shock systems with the member galaxies. CIZA J2242.8+5301 is an extremely massive (M200 ∼ 2 × 1015 M⊙; Dawson et al. 2015; Jee et al. 2015) and X-ray disturbed cluster (Akamatsu & Kawahara 2013; Ogrean et al. 2013, 2014) which most likely resulted from a head-on collision of two, equal-mass systems (van Weeren et al. 2011; Dawson et al. 2015). The cluster merger induced relatively strong shocks, which travelled through the ICM, accelerated particles to produce relics towards the north and south of the cluster (van Weeren et al. 2010; Stroe et al. 2013). There is evidence for a few additional smaller shock fronts throughout the cluster volume (Stroe et al. 2013; Ogrean et al. 2014). Of particular interest is the northern relic, which earned the cluster the nickname ‘Sausage’. The relic, tracing a shock of Mach number M ∼ 3 (Stroe et al. 2014c), is detected over a spatial extent of ∼1.5 Mpc in length and up to ∼150 kpc in width and over a wide radio frequency range (150 MHz–16 GHz; Stroe et al. 2013, 2014b). There is evidence that the merger and the shocks shape the evolution of cluster galaxies. The radio jets are bent into a head–tail morphology aligned with the merger axis of the cluster. This is probably ram pressure caused by the relative motion of galaxies with respect to the ICM (Stroe et al. 2013). The cluster was also found to host a high fraction of H α emitting galaxies (Stroe et al. 2014a, 2015). The cluster galaxies not only exhibit increased SF and AGN activity compared to their field counterparts, but are also more massive, more metal rich and show evidence for outflows likely driven by SNe (Sobral et al. 2015). Stroe et al. (2015) and Sobral et al. (2015) suggest that these relative massive galaxies (stellar masses of up to ∼1010.0–10.7 M⊙) retained the metal-rich gas, which was triggered to collapse into dense star-forming clouds by the passage of the shocks, travelling at speeds up to ∼2500 km s−1 (Stroe et al. 2014c), in line with simulations by Roediger et al. (2014).

2020AandA...644A..97C__Leroy_et_al._2013_Instance_2

Major nearby galaxy cold gas mapping surveys (Regan et al. 2001; Wilson et al. 2009; Rahman et al. 2011; Leroy et al. 2009; Donovan Meyer et al. 2013; Bolatto et al. 2017; Sorai et al. 2019; Sun et al. 2018) have focused on observations of the molecular gas (through CO lines). Despite a few notable exceptions (e.g. Alatalo et al. 2013; Saintonge et al. 2017), these surveys observed mainly spiral or infrared-bright galaxies (i.e. galaxies with significant star formation) and have furthered our understanding of how star formation happens, rather than how it stops. This boils down to quantifying the relation between molecular gas and star formation rate (SFR), which appears nearly linear in nearby discs (Kennicutt 1998; Bigiel et al. 2008; Leroy et al. 2013; Lin et al. 2019). This relationship is often parametrised via the ratio between the SFR and the molecular gas mass (Mmol), which is called the molecular star formation efficiency (SFE = SFR/Mmol = 1∕τdep), where the inverse of the SFE is the depletion time, τdep. The depletion time indicates how much time is necessary to convert all the available molecular gas into stars at the current star formation rate. On kpc scales and in the discs of nearby star-forming galaxies, τdep is approximately constant around 1–2 Gyr (Bigiel et al. 2011; Rahman et al. 2012; Leroy et al. 2013; Utomo et al. 2017), and it appears to weakly correlate with many galactic properties such as stellar mass surface density or environmental hydrostatic pressure (Leroy et al. 2008; Rahman et al. 2012). Nevertheless, small but important deviations for a constant SFE have been noticed, which can be the first hints of star formation quenching. In some galaxies, the depletion time in the centres appear shorter (Leroy et al. 2013; Utomo et al. 2017) or longer (Utomo et al. 2017) with respectto their discs. These differences may correlate with the presence of a bar or with galaxy mergers (Utomo et al. 2017; see also Muraoka et al. 2019) and do not seem to be related to unaccounted variation in the CO-to-H2 conversion factor (Leroy et al. 2013; Utomo et al. 2017). Spiral arm streaming motions have also been observed to lengthen depletion times (Meidt et al. 2013; Leroy et al. 2015).

2022ApJ...930...70H__Vogl_et_al._2020_Instance_1

There are some existing studies applying machine learning to transient studies. For example, the spectral types of the SNe can be classified based on their light-curve data (Möller et al. 2016; Muthukrishna et al. 2019a; Takahashi et al. 2020; Villar et al. 2020), and transients can be identified from the astronomical survey images (Goldstein et al. 2015; Mahabal et al. 2019; Gómez et al. 2020). The light curves of SNe Ia can be well modeled by functional principal component analysis (FPCA; He et al. 2018), where it was shown remarkably that a set of FPCA eigenvectors that are independent of the photometric filters can be derived from the observed light curves of SNe Ia. There are a few studies of the application of deep learning neural networks to the spectral data of SNe. For example, Muthukrishna et al. (2019b) used a convolutional neural network (CNN) for automated SN type classification based on SN spectra. Several other works (Chen et al. 2020; Vogl et al. 2020; Kerzendorf et al. 2021) applied a Gaussian process, principal component analysis (PCA), and deep learning neural networks to radiative transfer models of SNe. Sasdelli et al. (2016) used unsupervised learning algorithms to investigate the subtypes of SNe Ia. Stahl et al. (2020) developed neural networks to predict the photometric properties of SNe Ia (phase and Δm 15) based on spectroscopic data. Saunders et al. (2018) used PCA to find low dimensional representations of the spectral sequences of 140 well-observed SNe Ia. Chen et al. (2020), in particular, built an artificial intelligence assisted inversion (AIAI) of radiative transfer models and used that to link the observed SN spectra with theoretical models. The AIAI is able to retrieve the elemental abundances and density and temperature profiles from observed SN spectra. The AIAI approach has the potential for quantitatively coupling complex theoretical models with the ever-increasing amount of high-quality observational data.

2021AandA...650A.203G__Chiosi_1980_Instance_1

In the past, as well as in the more recent literature, there have been many attempts to explain the different chemical evolutionary paths of different MW components, particular those of the thin and thick discs. The outcome of these studies is that the observed different chemical evolutionary paths are related to differences in the main physical processes that drive galaxy evolution, the most significant of which are the gas accretion time-scale and the star formation efficiency and, possibly, radial migration (Larson 1972; Lynden-Bell 1975; Pagel & Edmunds 1981; Matteucci & Greggio 1986; Matteucci & Brocato 1990; Ferrini et al. 1994; Prantzos & Aubert 1995; Chiappini et al. 1997, 2001; Portinari & Chiosi 1999; Bekki & Tsujimoto 2011; Micali et al. 2013; Sahijpal 2014; Snaith et al. 2014; Grisoni et al. 2017; Grand et al. 2018; Spitoni et al. 2021). A good agreement between observations and theoretical predictions for the Galaxy is obtained by models that are based on the assumption that the disc formed via the infalling of gas (Chiosi 1980; Matteucci & Francois 1989; Chiappini et al. 1997). The formation of the different components is associated with distinct sequential main episodes of gas accretion (infall phases) that, at first, rapidly accumulates in the central regions and then, more slowly, in the more external ones, according to the so-called ‘inside-out scenario’ (Chiappini et al. 2001). In particular, the three-infall model, devised by Micali et al. (2013), is capable of reproducing the abundance patterns of the MW halo, thick and thin disc at once. In this model, the halo forms in a first gas infall episode of short timescale (0.2 Gyr) and mild star formation efficiency, ν = 2 Gyr−1, lasting for about 0.4 Gyr. It is immediately followed by the thick disc formation, characterised by a somewhat longer infall timescale (1.2 Gyr), a longer duration (about 2 Gyr) and a higher star formation efficiency (ν = 10 Gyr−1). Finally, star formation continues in the thin disc with a longer infall timescale (6 Gyr in the solar vicinity) and is still continuing to this day, with a star-formation efficiency of ν = 1 Gyr−1. The [O/Fe] vs. [Fe/H] path is thus continuous across the regions populated by halo, thick, and thin disc stars. While Micali et al. (2013) described the chemical enrichment as continuous across the three different infall stages, Grisoni et al. (2017) used also an alternative scheme where the thin and thick disc components evolve separately, in a parallel approach (see also Chiappini 2009). In such a parallel approach, the disc populations are assumed to form in parallel but to proceed at different rates. The gas infall exponentially decreases with a timescale that is 0.1 Gyr and 7 Gyr, for the thick and thin disc, respectively. This alternative approach better reproduces the presence of the metal-rich α-enhanced stars in the [Mg/Fe] vs. [Fe/H] diagram obtained with the recent AMBRE data (Mikolaitis et al. 2017).

2022AandA...659A..54E__Kendall_et_al._1992_Instance_1

Exploration of the stationary points of the [H, P, S, O] molecular system was initially carried out using Møller–Plesset second order Perturbation Theory (MP2) (Møller & Plesset 1934; Frisch et al. 1990a,b; Head-Gordon & Head-Gordon 1994; Head-Gordon et al. 1988; Sæbø & Almlöf 1989) with the 6-311++G(d, p) basis set (McLean & Chandler 1980; Krishnan et al. 1980). Following the initial survey, transition state structures connecting various isomers of [H, P, S, O] were located using MP2/6-311++G(d, p) and confirmed via an intrinsic reaction coordinate (IRC) calculation. To achieve a quantitative picture of the ground state potential energy surface, coupled cluster theory with single, double, and perturbative triple excitations [CCSD(T)] (Knowles et al. 1993, 2000) single point calculations employing the aug-cc-pV(Q+d)Z basis set were performed at the MP2 equilibrium geometries. Entrance channel pathways were explored via relaxed scans and individual searches for transition states. Following this, higher level calculations on the electronic structure, rotational constants, and harmonic vibrational frequencies of each isomer were performed using CCSD(T) together with the Dunning basis sets aug-cc-pV(X+d)Z (X = T, Q, 5) (Dunning 1989; Woon & Dunning 1993; Kendall et al. 1992), including additional tight d functions on the sulfur and phosphorous atoms (Dunning et al. 2001). CCSD(T) including all electrons was then performed using the second order Douglas-Kroll–Hess Hamiltonian in conjunction with the contracted relativistic Douglas–Kroll aug-cc-pwCVTZ-DK basis set to correct for scalar relativistic and core-correlation effects (Jorge et al. 2009). The aforementioned combinationof level of theory and basis set will be referred to as CCSD(T)-AE/TZ-DK. Finally, explicit correlation of the electrons was included using the CCSD(T)-F12b method (Werner et al. 2011) with the Dunning basis sets aug-cc-pVXZ (X = T, Q, 5). Single-reference character of the wavefunction was confirmed via single-state complete active spaceself-consistent field theory in addition to the coupled cluster T1 diagnostic. Energies and geometry parameters were then extrapolated to the complete basis set limit using the two-point (Q, 5) extrapolation scheme E(x)= ECBS + AX−3, where E(x) is the value calculated using the basis set of cardinal number X, ECBS is the extrapolated energy, and A is a parameter fit in the least-squares fitting procedure. Mulliken population analysis was performed on cis-HOPS using MOLPRO. Corrections to the rotational constants, spectroscopic data, and anharmonic vibrational data were calculated for the four lowest energy isomers at the CCSD(T)/aug-cc-pV(T+d)Z level of theory using CFOUR (Matthews et al. 2020; Stanton et al. 2019). Permanent dipole moments for each isomer were calculated using the finite field method (field strengths of 0, 0.005, and −0.005 au) as implemented in MOLPRO.

2019MNRAS.484.1359Y__Melrose_&_Yuen_2014_Instance_1

The discrete change in spin-down rate between the on and off states suggests a switching behaviour in the pulsar magnetosphere. While explanation for the phenomenon remains inconclusive, conventional treatments typically involve referring each emission state to different condition in the magnetosphere in such a way that a plasma-filled magnetosphere is related to the emission-on state and a sudden depletion of charge particles is responsible for the decrease in the spin-down rate during the emission-off state (Contopoulos 2005; Kramer et al. 2006; Beskin & Nokhrina 2007; Li et al. 2012). Kramer et al. (2006) and Beskin & Nokhrina (2007) suggest that energy loss of PSR B1931 + 24 is due only to the rotating dipole during the emission-off state where there is no current flowing, whereas current loss is responsible for the energy loss during the emission-on state. In this scenario, pulses are undetectable due to decrease in the plasma density in the emitting region to a magnetospheric state so that the pulse intensity of the pulsar decreases when it jumps to that state and resumes to its normal intensity when it returns to its initial state. While the approach has revealed unprecedented information about the pulsars, it implicitly treats the two emission states as independent entities with presumed vacuum condition for the emission-off state. Our investigation is based on a magnetospheric model that synthesizes the corotating magnetosphere model and the vacuum model (Melrose & Yuen 2014, 2016), in which multiple quasi-stable magnetospheric states are described by the parameter y such that the charge filling fraction of a state corresponds to a y value and a change in the charge filling fraction corresponds to a change of state which is signified by a change in y. The presence of plasma in the corotating magnetosphere model implies a global current flow that closes at the stellar surface within the polar cap region. By considering a simple framework for the spin-down torque as induced by the component of the global current that crosses the magnetic fields at the stellar surface, we show that discrete changes in the spin-down rates may be attributed to changes in the pulsar torque caused by variations in the global current flow when jumping takes place between different magnetospheric states in the pulsar magnetosphere. Using this idealized model, characteristics of intermittent pulsars are studied by jointly considering the two emission states based on the parameters y and α, the obliquity angle between the magnetic and rotation axes, through the ratio of the respective spin-down rate whose changes are described by the ratio of the corresponding spin-down torque in the two states. The yet unidentified links between intermittent and ordinary pulsars imply that, in addition to the parameters already under detailed examination in the literature, there may exist unknown factors that are distinctly related to intermittency and likely to be pulsar-specific. An obvious example is the large differences in the emission-on and -off cycles which range from days (Kramer et al. 2006) to years (Camilo et al. 2012). Since the correlation between these parameters and intermittency is still unclear, before including such factors, it is useful to explore the implications of the idealized model.

2018MNRAS.474.2277D__Oliveira,_Dottori_&_Bica_1998_Instance_2

There are three possible explanations for the origin of these systems: (1) they formed from the fragmentation of the same molecular cloud (Elmegreen & Elmegreen 1983), (2) they were generated in distinct molecular clouds and then became bound systems after a close encounter leading to a tidal capture (Vallenari, Bettoni & Chiosi 1998; Leon, Bergond & Vallenari 1999), or (3) they are the result of division of a single star-forming region (Goodwin & Whitworth 2004; Arnold et al. 2017). Their subsequent evolution may also have different outcomes. Dynamical models and N-body simulations (see, e.g., Barnes & Hut 1986; de Oliveira, Dottori & Bica 1998, and references therein) have shown that, depending on the initial conditions, a bound pair of clusters may either become unbound, because of significant mass-loss in the early phases of stellar evolution, or merge into a single and more massive cluster on a short time-scale (≈60 Myr) due to loss of angular momentum from escaping stars (see Portegies Zwart & Rusli 2007). The final product of a merger may be characterized by a variable degree of kinematic and morphologic complexity, mostly depending on the values of the impact parameter of the pre-merger binary system (de Oliveira, Bica & Dottori 2000; Priyatikanto et al. 2016). In some cases, the stellar system resulting from the merger event may show significant internal rotation (in fact, for many years this has been the preferred dynamical route to form rotating star clusters; see Sugimoto & Makino 1989; Makino, Akiyama & Sugimoto 1991; Okumura, Ebisuzaki & Makino 1991; de Oliveira, Dottori & Bica 1998). Merger of cluster pairs has been sometimes invoked to interpret the properties of particularly massive and dynamically complex clusters (e.g. see the study of ω Centauri by Lee et al. 1999, G1 by Baumgardt et al. 2003 and NGC  2419 by Brüns & Kroupa 2011), and, more in general, as an avenue to form clusters with multiple populations with different chemical abundances both in terms of iron and light elements (e.g. van den Bergh 1996; Catelan 1997; Amaro-Seoane et al. 2013; Gavagnin, Mapelli & Lake 2016; Hong et al. 2017).

2016ApJ...817...12P__Chamandy_et_al._2014_Instance_1

Large-scale magnetic fields with strength of the order of 1–10 μG have been observed in disk galaxies (e.g., Beck et al. 1996; Fletcher 2010; Beck 2012; Beck & Wielebinski 2013; Van Eck et al. 2015). The origin of these fields can be explained through mean-field dynamo theory (Ruzmaikin et al. 1988; Beck et al. 1996; Brandenburg & Subramanian 2005a; Kulsrud & Zweibel 2008). The conservation of magnetic helicity is one of the key constraints in these models, and also leads to the suppression of the α-effect. The operation of the mean-field dynamo automatically leads to the growth of magnetic helicity of opposite signs between the large-scale and small-scale magnetic fields (Pouquet et al. 1976; Gruzinov & Diamond 1994; Blackman & Field 2002). To avoid catastrophic suppression of the dynamo action (α-quenching), the magnetic helicity due to the small-scale magnetic field should be removed from the system (Blackman & Field 2000, 2001; Kleeorin et al. 2000). Mechanisms suggested to produce these small-scale magnetic helicity fluxes are: advection of magnetic fields by an outflow from the disk through the galactic fountain or wind (Shukurov et al. 2006; Sur et al. 2007; Chamandy et al. 2014), magnetic helicity flux from anisotropy of the turbulence produced by differential rotation (Vishniac & Cho 2001; Subramanian & Brandenburg 2004, 2006; Sur et al. 2007; Vishniac & Shapovalov 2014), and through diffusive flux (Kleeorin et al. 2000, 2002; Brandenburg et al. 2009; Mitra et al. 2010; Chamandy et al. 2014). The outflow of magnetic helicity from the disk through dynamo operation leads to the formation of a corona (Blackman & Field 2000). According to Taylor's hypothesis, an infinitely conducting corona would resistively relax to force-free field configurations under the constraint of global magnetic helicity conservation (Woltjer 1960; Taylor 1974; Finn & Antonsen 1983; Berger & Field 1984; Mangalam & Krishan 2000). In this paper, we include advective and diffusive fluxes in a simple semi-analytic model of a galactic dynamo that transfers magnetic helicity outside the disk and consequently builds up a force-free corona in course of time. We first solve the time-dependent dynamo equations by expressing them as separable in variables r and z. The radial part of the dynamo equation is solved using an eigenvector expansion constructed using the steady-state solutions of the dynamo equation. The eigenvalues of the z part of the solution are obtained by solving a fourth-order algebraic equation, which primarily depends upon the turbulence parameters and the magnetic helicity fluxes. Once the dynamo solutions are written out as parametric functions of these parameters, the evolution of the mean magnetic field is computed numerically by simultaneously solving the dynamical equations for α-quenching and the growth of large-scale coronal magnetic helicity. Since the large-scale magnetic field lines cross the boundary between the galactic disk and the corona, the magnetic helicity of the large-scale magnetic field in the disk volume is not well defined. Hence we use the concept of gauge-invariant relative helicity (Finn & Antonsen 1983; Berger & Field 1984; Berger 1985) to estimate the large-scale magnetic helicity in the disk and the corona. Here the gauge-invariant relative helicity for the cylindrical geometry is calculated using the prescription given in Low (2006, 2011). We then investigate the dependence of the saturated mean magnetic field strength and its geometry on the magnetic helicity fluxes within the disk and the corresponding evolution of the force-free field in the corona.

2021ApJ...921...18K__Kushwaha_et_al._2018a_Instance_3

The most unique and characteristic observational feature of blazars’ highly variable broadband emission is the broad bimodal SED extending from the lowest accessible EM band, i.e., the radio, to the highest accessible, i.e., GeV-TeV γ-rays. The broadband SED of all blazars can be categorized into three different spectral subclasses: low-energy-peaked (LBL/LSP), intermediate-energy-peaked (IBL/ISP), and high-energy-peaked (HBL/HSP; Fossati et al. 1998; Abdo et al. 2010), based on the location of the low-energy hump. A remarkable property of each spectral subclass is the stability of the location of the two peaks despite huge variations in flux and often spectral shape. Only in a few rare instances has an appreciable shift in the location of the peaks been observed, e.g., the 1997 outburst of Mrk 501 (Pian et al. 1998; Ahnen et al. 2018) and the activity of OJ 287 from the end of 2015 to the middle of 2017 (Kushwaha et al. 2018a, 2018b). Even these two cases are remarkably different. In the case of Mrk 501, the locations of both the peaks shifted to higher energies. On the contrary, in OJ 287, a shift in the location of only the high-energy peak was observed during the 2015–2016 activity (Kushwaha et al. 2018a, 2019), while in 2016–2017 a new broadband emission component overwhelmed the overall emission, appearing as an overall shift in both the peaks as revealed in the detailed study by Kushwaha et al. (2018b). With the SED being the prime observable for exploration of the yet-debated high-energy emission mechanisms, such changes offer invaluable insights about the emission processes. For example, in Mrk 501 the shift in both peaks strongly implies the same particle distribution for the overall emission, while for OJ 287 the shift of only the high-energy peak can be reproduced by either inverse Compton scattering of the broad-line region photon field (Kushwaha et al. 2018a) or emission of hadronic origin (Oikonomou et al. 2019; Rodríguez-Ramírez et al. 2020).

2018MNRAS.478.2541F__Smith_&_Tombleson_2015_Instance_2

Utilizing the full range of peak absolute magnitudes observed in LBV stars [M ≃  (−13)–(−9) mag; e.g. Smith et al. 2011b] provides a range of peak apparent magnitudes of m ≃  16.5–20.5 mag, for a distance of D ≃ 8 Mpc (Table 1). Hence, if the transient source (m ≈ 21.0 mag; Section 2.1.2) is an LBV star, it must have been observed a short time after its peak (Fig. 2; left-hand column; rows 4–5); quiescent LBV stars can have absolute magnitudes as low as M ≃ −6 mag (e.g. Smith et al. 2011b), or m ≃ 23.5 mag (for a distance of D ≃ 8 Mpc; Table 1). An LBV star provides an adequate explanation for the transient time-scale, the isolation (e.g. Smith & Tombleson 2015; Smith 2016), the lack of a host H ii region (Fig. 2 and 3; see below, however), and the transient/main source offset (d ≈ 0.3 kpc, for D ≃ 8 Mpc; Table 1; see below, however). In addition, (net) fading of the LBV peak event by Δm ≲ 3 mag (over a period of approximately 40 yr) may possibly produce an apparent brightness centroid shift/morphology variation in the main source (Sections 2.1.2 and 2.1.3). However, this scenario has its caveats. First, it is difficult to interpret the flux variability of the main source (Sections 2.1.4 and 2.3.1) within such a context. Secondly, although a fraction of LBV stars are isolated (e.g. Smith & Tombleson 2015; Smith 2016), in the only XMP with a documented LBV star, the LBV star appears embedded within an H ii region (DDO 68; Pustilnik et al. 2017); no clear H ii region at the location of the transient source is discernible in the HST images (Fig. 3; top), although it should be detectable given the typical lifetime of an H ii region (few Myr; e.g. Alvarez, Bromm & Shapiro 2006). Thirdly, a (net) magnitude variation of Δm ≲3 mag of the transient over a period of approximately 60 yr would result in a quiescent LBV source (m ≲ 23.5 mag) that should have been detectable in the HST images (Fig. 3; top). Lastly, as LBV stars brighten, they become redder (e.g. Sterken 2003), which appears to contradict the POSS data (Table 2; Fig. 2; rows 2–5). Consequently, as the LBV scenario explains some of the observables challenged by other scenarios (e.g. transient timeline), it remains a contender for the observed phenomenon.

2018AandA...619A..13V__Saviane_et_al._2012_Instance_4

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.

2020ApJ...895...82V__Fryer_et_al._2018_Instance_1

The shock is then revived by adding an energy injection following the parameterized method of Fryer et al. (2018). In this model, roughly was deposited into the inner in the first . Some of this energy is lost through neutrino emission and the total explosion energy at late times for this model is . This explosion is then mapped into our three-dimensional calculations, using one million SPH particles. The mapping took place when the supernova shock had moved out of the iron core and propagated into the Si–S rich shell at . We note that our 1D methods employed for modeling the collapse, core bounce, and initial explosion do not capture the full physics of the central engine (for a discussion, see Fryer et al. 2018), and this is a source of uncertainty in our yield calculations. The details of the engine change the shock trajectories, and neutrino chemistry can change Ye values (Saez et al. 2018; Fujimoto & Nagakura 2019). The nature of the shock affects mostly the yields after the shock falls below NSE (before it falls out of NSE, the yields are set by the equilibrium values, not the time-dependent evolution). Our model captures one instance of the range of asymmetric trajectories, and it should be noted that no model at this time is sufficiently accurate to dictate exactly the properties of the asymmetries (Janka et al. 2016). In addition, any model that does not include convection-driven asymmetries from the progenitor star cannot properly capture the asymmetries (Arnett et al. 2015). The 3D explosion model used here also displays stochastic asymmetries, implying that any manner of convective asymmetry could generate similar results. If this behavior is universal, it could have important implications. These points taken together indicate that nucleosynthetic patterns arising from convection-like behavior are robust, regardless of the driver. As discussed below, this increases the utility of NSE nucleosynthesis, particularly of and , as diagnostics of the conditions in the progenitor star.

2017ApJ...844...14L__Martell_et_al._2008_Instance_1

Figure 2 shows the measured spectral indices of stars as functions of K magnitude, obtained from the 2MASS catalog. The CN, HK′, and CH indices increase with decreasing magnitude because the brighter RGB stars have lower temperatures and the strengths of these molecular bands generally increase with decreasing temperature. Therefore, the chemical abundances of stars are compared on the δ-index versus magnitude diagrams. It is important to note that the observed stars show a large spread in δ-index that is at least several times larger than the measurement error. The standard deviations for all sample stars are 0.23 for CN, 0.07 for HK′, and 0.07 for CH. In particular, the CN index distribution shows the largest spread. Note that a bimodality or a large spread in CN distribution is generally observed in most GCs (Norris et al. 1981; Norris 1987; Briley et al. 1992; Harbeck et al. 2003; Kayser et al. 2008; Martell et al. 2008).2 2 Although the evolutionary mixing effect can also contribute to the large spread in CN index distribution among bright RGB stars (Sweigart & Mengel 1979), this effect alone cannot explain a discrete distribution and a wide spread in the unevolved stars (see, e.g., Kayser et al. 2008). Therefore, we have divided subpopulations of RGB stars in NGC 5286 on the histogram of the δCN index (see Figure 3). It is clear from this histogram that RGB stars are divided into three subpopulations: CN-weak (δCN −0.2; blue circles), CN-intermediate (−0.2 ≤ δCN 0.1; green circles), and CN-strong (0.1 ≤ δCN; red circles). The distribution of CN index into three or more subpopulations is similar to that reported in NGC 1851 (Campbell et al. 2012; Lim et al. 2015; Simpson et al. 2017). This is also consistent with the recent results from population models and spectroscopic observations that show that most GCs host three or more subpopulations (see, e.g., Jang et al. 2014; Carretta 2015). The presence of multiple populations is also observed from recent photometry using UV filters, which are mainly sensitive to N abundance (Milone et al. 2015; Piotto et al. 2015). In this regard, further observations are required to check that the trimodal CN distribution, observed in NGC 1851 and NGC 5286, is a ubiquitous feature in other GCs as well.

2019MNRAS.487..475C__Ward-Thompson_et_al._2009_Instance_1

We attempted to find a correlation between the mean magnetic field and the outflow and minor axis of the cloud CB 17. Relative orientations between various quantities of CB 17 are presented in the first row of Table 6, along with a comparative study of the same for some dark clouds. The first column gives the cloud ID and columns 2–6 give the position angles of the mean magnetic field at the envelope ($\lt \theta ^{\rm env}_B\gt $), mean magnetic field at the core ($\lt \theta ^{\rm core}_B\gt $), outflow axis (θout), minor axis (θmin) of the core of the cloud and Galactic plane (θGP), respectively. $\lt \theta ^{\rm env}_B\gt $ of CB 17 is found to be almost aligned along the Galactic plane over that region of the sky (column 7), which indicates the dominance of the Galactic magnetic field over the envelope magnetic field of the cloud and thus we cannot infer much about the magnetic field structure from the optical study. A similar feature has also been observed in the cases of CB 34 (Das et al. 2016), L328, L673-7 (Soam et al. 2015), CB 26 (Halder et al. 2019), CB 3 and CB 246 (Ward-Thompson et al. 2009). However, $\lt \theta ^{\rm core}_B\gt $ of CB 17 (obtained by submm polarimetry) turned out to be perpendicular to $\lt \theta ^{\rm env}_B\gt $ (column 8); a similar phenomenon has been observed in the case of CB 34-C1 (Das et al. 2016), IRAM 04191 (Soam et al. 2015) and CB 54 (Wolf et al. 2003). Since, in the case of CB 17, $\lt \theta ^{\rm env}_B\gt $ is along the Galactic plane orientation, this implies that only $\lt \theta ^{\rm core}_B\gt $ (denser region) is linked with the ongoing physical phenomena in the cloud. $\lt \theta ^{\rm core}_B\gt $ is oriented perpendicular to θGP as well (column 9) and a similar orientation has been observed in the case of CB 34-C1 (Das et al. 2016), IRAM 04191 (Soam et al. 2015), CB 230 and CB 244 (Wolf et al. 2003) as well. Moreover, $\lt \theta ^{\rm core}_B\gt $ is found to be almost aligned along the minor axis of the core of the cloud; the angular offset is nearly 5.9° (column 10). The alignment of $\lt \theta ^{\rm core}_B\gt $ with the minor axis of the cloud fits the magnetically regulated star formation model, in which the magnetic field should lie along the minor axis of the cloud (Mouschovias & Morton 1991; Li 1998), and the same feature has also been observed for the clouds CB 34-C1 (Das et al. 2016) and IRAM 04191 (Soam et al. 2015). The angular offset between $\lt \theta ^{\rm core}_B\gt $ and the outflow axis is found to be 80.9° (column 11), that is, the core-scale magnetic field is oriented almost perpendicular to the outflow direction and a similar phenomenon has also been observed in the case of CB 34 (Das et al. 2016), CB 68 (Bertrang et al. 2014), B335, CB 230, CB 244 (Wolf et al. 2003) and CB 3 (Ward-Thompson et al. 2009). The angular offset between θout and θmin is found to be 75° and the same feature has been observed for CB 34-C1 (Das et al. 2016).