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2016ApJ...831...41W__Dai_&_Liu_2012_Instance_1

Our results have immediate stimulations for further research. First, although here we have studied the SNe Ic-BL not associated with GRBs, the main conclusion can be equally applied to GRB-SNe. It is usually believed that the central engines of GRBs are black holes (Popham et al. 1999; Narayan et al. 2001; Kohri & Mineshige 2002; Liu et al. 2007; Song et al. 2016) or magnetars (Usov 1992; Dai & Lu 1998a, 1998b; Zhang & Dai 2008, 2009, 2010; Giacomazzo & Perna 2013; Giacomazzo et al. 2015). However, since it is currently infeasible to identify the GRB central engine directly because of the cosmological distance scales of GRBs (Kumar & Zhang 2015), the researchers instead pursue indirect signatures of black holes (Geng et al. 2013; Wu et al. 2013; Yu et al. 2015) and magnetars (Dai et al. 2006; Gao et al. 2013; Wang & Dai 2013; Yu et al. 2013; Zhang 2013; Metzger & Piro 2014; Wang et al. 2015a, 2016a; Li & Yu 2016; Liu et al. 2016) that power the energetic GRBs. Growing indirect observational evidence suggests that magnetars could act as the central engines of both LGRBs and short-duration GRBs (Dai et al. 2006; Rowlinson et al. 2010, 2013; Dai & Liu 2012; Wang & Dai 2013; Wu et al. 2014; Gao et al. 2015; Greiner et al. 2015). However, because of the high mass of 56Ni needed to heat the GRB-SNe, magnetars are doubted as the candidate central engine of GRBs. With our demonstration that this high mass of 56Ni is actually not the case, such a concern is removed.8 8 We note that Cano et al. (2016a) drew the conclusion that GRB-SNe are powered by 56Ni decay under the assumption that the central engine of GRB-SNe is a magnetar. In drawing this conclusion, Cano et al. (2016a) assume that the mangetar’s rotational energy is equally divided between GRB afterglow and SNe. This assumption is somewhat ad hoc and unjustified. At the least, although the jet launching could be the result of the magnetar spin-down, it seems more likely to be the result of accretion onto the magnetar (Zhang & Dai 2008, 2009, 2010). Furthermore, Cano et al. (2016a) do not consider the origin of the kinetic energy of the GRB-SNe in their model. If we accept the assumption that a huge amount of kinetic energy of the GRB-SNe comes from the rotational energy of the magnetar, the initial rotational period of the magnetar cannot be as long as given by Cano et al. (2016a). Finally, as we mentioned above, our conclusion that the 56Ni mass for the tail modeling is usually much smaller than the peak modeling is consistent with the finding by Maeda et al. (2003).

2021AandA...655A..22M__Hopkins_et_al._2014_Instance_1

Despite the consensus on the importance of galactic winds in dwarf galaxy formation, large uncertainties persist in how the winds are driven. As the ISM physics is typically not resolved in full cosmological simulations (although some simulations are getting close, see e.g., Wheeler et al. 2019; Agertz et al. 2020), subgrid feedback models are often used to alleviate the numerical ‘overcooling’ problem, whereby energy injected into the ISM is rapidly cooled away because of unresolved ISM structures. Many studies have investigated supernova (SN) feedback, perhaps the most important process to drive galactic wind in dwarf galaxies. Different approaches of subgrid models were explored, ranging from kinetic feedback models where wind mass loading and velocities are predetermined (Springel & Hernquist 2003; Oppenheimer & Davé 2006; Dalla Vecchia & Schaye 2008), to explicit models where radiative cooling is temporarily shut off (Stinson et al. 2006; Agertz et al. 2011; Teyssier et al. 2013), to mechanical feedback where the momentum boost during the unresolved adiabatic phase is calibrated through small-scale ISM simulations and injected into the ISM (Hopkins et al. 2014; Kimm & Cen 2014; Smith et al. 2018). Simulations of dwarf galaxies in recent years have often adopted one of these approaches for SN feedback. Although many are considered successful in reproducing observations, few attempts have been made to compare these models in full cosmological simulations. It is therefore important to gauge how the evolution of simulated dwarf galaxies (especially at the low mass end) is dependent on feedback models, in order to provide a more robust model with realistic uncertainties for future observations. Moreover, most existing SN feedback models take into account individual SN explosions. However, recent studies such as Nath & Shchekinov (2013) and Sharma et al. (2014), have pointed out that stars form in clusters and, through multiple repeated SN explosions, generate the so-called superbubbles, which contain hot gas, and the sharp temperature gradients between hot and cold gas make thermal conduction an extremely important process. The evolution of superbubbles and the importance of thermal conduction have been investigated using ISM simulations with direct treatments of thermal conduction (e.g., El-Badry et al. 2019; Steinwandel et al. 2020). However, the resolution requirement for directly modelling conduction is still unattainable for cosmological galaxy formation simulations.

2019AandA...621A..27F__Delvecchio_et_al._2015_Instance_1

SMBHs and host galaxies share several properties. Both SMBHs and galaxies have exponential cut-offs at the high mass end of their co-moving space densities (e.g., Shankar et al. 2009; Ilbert et al. 2013; Kelly & Shen 2013). The population of both SMBHs and galaxies also exhibit mass downsizing whereby the oldest, in the case of galaxies, and the most massive of SMBHs grew early and rapidly (e.g., Thomas et al. 2005, 2010; Merloni & Heinz 2008). However, there is a mismatch in both the shape and co-moving number density between galaxies and dark matter halos, especially at the low and high mass ends of these functions (Benson et al. 2003). Because powerful AGN can have a mechanical and radiative energy output similar to or exceeding that of the binding energy of a massive galaxy and dark matter halo, AGN are thought to play a key role in regulating the baryonic growth of galaxies. Both observations and simulations have suggested that there may be a positive trend between the mean black hole accretion rate and star-formation rate (SFR; e.g., Delvecchio et al. 2015; McAlpine et al. 2017), while the mean SFR as a function of black hole accretion rate shows no correlation for low luminosity sources (e.g., Stanley et al. 2015; McAlpine et al. 2017). One should be cautious when interpreting both theoretical and observational results in the definition of what exactly AGN feedback is and how AGN affect their host galaxies to explain the properties of an ensemble of galaxies (Scholtz et al. 2018). The strength and nature of AGN feedback – the cycle whereby the SMBH regulates both its own growth and that of its host – depends on galaxy mass and morphology. For example, the most massive elliptical galaxies are generally metal-rich and old, while less massive lenticular galaxies, which make up the bulk of the early-type galaxy population, have star formation histories that lasts significantly longer (Thomas et al. 2005, 2010; Emsellem et al. 2011; Krajnović et al. 2011). Clearly, if AGN feedback plays a crucial role in shaping the ensemble of galaxies, its impact on massive dispersion dominated galaxies must result in somewhat different characteristics in these galaxies compared to rotationally-dominated and predominately less massive lenticular galaxies.

2016ApJ...824..142Q__Galvin_et_al._2008_Instance_1

Current observations of the interstellar neutral helium trajectories by the Interstellar Boundary EXplorer (IBEX) (McComas et al. 2009) determined the inflow longitude of the interstellar wind to be (Leonard et al. 2015), ∼757 (McComas et al. 2015), (Bzowski et al. 2015), and (Schwadron et al. 2015). Recent studies using the Ulysses/GAS instrument made observations of the interstellar helium distribution by detecting the sputtered ions from a lithium fluoride coated surface, finding the inflow direction to be (Bzowski et al. 2014) and (Wood et al. 2015). However, recent observations of the pickup helium focusing cone using the Plasma and Suprathermal Ion Composition (PLASTIC; Galvin et al. 2008) on board the Solar and Terrestrial Relations Observatory Ahead (STEREO A) spacecraft measured the peak density and determined the inflow longitude to be (Drews et al. 2012). In addition, Gershman et al. (2013) measured the peak density of the pickup helium focusing cone using the Fast Imaging Plasma Spectrometer (FIPS; Andrews et al. 2007) instrument on board the MErcury, Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft and the Solar Wind Ion Composition Spectrometer (Gloeckler et al. 1998) instrument on board the Advanced Composition Explorer spacecraft and determined inflow longitudes of and , respectively. Although these pickup ion measurements fall within the 1σ uncertainties of the IBEX observations, they appear to show consistently small deviations in the same direction. Refer to Figure 1 for a diagram of the longitudinal difference between the observations focused on in this study of Drews et al. (2012) and Schwadron et al. (2015). The difference between the pickup helium and neutral helium observations suggests that the transport of pickup ions inside 1 au may play a role—a concept that was addressed but not factored into the derived peak longitudes in the previously mentioned pickup ion studies and has recently been up for debate (Chalov 2014; Lallement & Bertaux 2014; Frisch et al. 2015).

2019ApJ...871L..22W__Alexandrova_2008_Instance_2

In analogy to the hydrodynamic case, the nonlinear coherent vortex structure also plays an important role in plasma dynamics and transport processes (Hasegawa & Mima 1978; Shukla et al. 1985; Petviashvili & Pokhotelov 1992; Horton & Hasegawa 1994). These vortices tend to have a long lifetime and are widely observed in space, laboratory, and numerical simulation of plasma (Chmyrev et al. 1988; Burlaga 1990; Volwerk et al. 1996; Stasiewicz et al. 2000; Sundkvist et al. 2005; Alexandrova et al. 2006; Alexandrova 2008; Alexandrova & Saur 2008; Vianello et al. 2010; Servidio et al. 2015). An essential subset of these plasma vortices is known as Alfvén vortices, which can be viewed as the cylindrical analog of the nonlinear Alfvén wave (Petviashvili & Pokhotelov 1992). The Alfvén vortices have an axis that is nearly parallel to the unperturbed magnetic field, along which the shape is generally invariant. Thus, these vortices are quasi-2D structures. The associated perpendicular magnetic fluctuations are linearly related with the perpendicular velocity fluctuations, but their relative amplitudes are not obligatorily equal (as is the case in an Alfvén wave): , where ξ is not necessarily equal to 1. In addition, Alfvén vortices do not propagate along in the plasma frame, and they hardly propagate in the perpendicular plane when the axis of the vortex is inclined with respect to that are in contrast with Alfvén wave (Wang et al. 2012). After first being reported in the Earth’s magnetosheath (Alexandrova et al. 2006; Alexandrova 2008), multiscale quasi-bidimensional Alfvén vortices (with ) have been identified in numerous space environments: in slow solar wind (Perrone et al. 2016; Roberts et al. 2016), in fast solar wind (Lion et al. 2016; Perrone et al. 2017), and in Saturn’s magnetosheath (Alexandrova & Saur 2008). It seems that the intermittent structures in fast solar wind are dominated by Alfvén vortices (Perrone et al. 2017), which agrees with the 2D MHD turbulence model (Zank et al. 2017).

2016ApJ...817..152X__Vreeswijk_et_al._2004_Instance_1

The connection between long-duration GRBs (LGRBs) and SNe was predicted theoretically (Colgate 1974; Woosley 1993) and has been verified observationally (e.g., Galama et al. 1998; Hjorth et al. 2003; see a review in Woosley & Bloom 2006). They usually happen in the star formation regions of the galaxies (e.g., Paczyński 1998; see the reviews in Woosley & Bloom 2006 and Kumar & Zhang 2015). The immensely bright afterglows illuminate the gas and dust within the star-forming regions of the host galaxy and intervening intergalactic medium along the GRB line of sight. Their spectra are usually featureless power-laws or broken power-laws, which can be well described by the synchrotron radiations of relativistic electrons. Therefore, GRB afterglows are good probes of burst environment and the interstellar dust and gas in distant, star-forming galaxies (Metzger et al. 1997; Jensen et al. 2001; Savaglio et al. 2003; Vreeswijk et al. 2004; Chen et al. 2005; Prochaska et al. 2007a; Schady et al. 2007, 2010; Watson et al. 2007; Fox et al. 2008; Starling et al. 2008; Jang et al. 2011; Xin et al. 2011). GRB afterglow spectra with Lyα absorption features indicate the presence of large column densities of cold neutral gas within GRB host galaxies, and their hydrogen column densities ( ) are usually larger than cm−2 (e.g., Prochaska et al. 2007b; Schady 2012). The damped Lyα systems (DLA) may represent the ISM near the GRBs in a few kiloparsecs (Kpc), but not gas directly local to the GRB (Prochaska et al. 2007b). Thus GRB optical afterglows may be used as probes of the ISM in their host galaxies, as the ISM observed is less affected by the GRB or its progenitor (Watson et al. 2007). The visual dust extinctions ( ) along the GRB lines of sight of many GRBs are low. As shown in Greiner et al. (2011), about 50% of GRBs observed with GROND after the launch of Swift mission have . In addition, the early optical light curves of about one-third of GRBs show a smooth onset bump (Li et al. 2012). It may be due to the deceleration of the GRB fireball by the ambient medium (Sari & Piran 1999; Kobayashi & Zhang 2007). In this scenario, the rising slope of the bump is determined by the medium density profile ( ) and the spectrum index of the accelerated electrons ], says, (Liang et al. 2013). Hence, The afterglow onset bumps would be also an ideal probe to study the properties of the fireball and the profile of the circumburst medium. Liang et al. (2013) found that (see also Watson et al. 2007; Jin et al. 2012).

2017ApJ...835...94O__Martin_et_al._1994_Instance_1

In this paper, we performed statistical analyses on the chirality and the magnetic configurations (inverse-polarity versus normal polarity) of the solar filaments that erupted on the solar disk from 2010 May 13 to 2015 December 31 covering both the rising phase and the beginning of the declining phases of solar cycle 24. The chirality is determined by an indirect method proposed by Chen et al. (2014), i.e., left-/right-skewed drainage corresponds to dextral/sinistral chirality. The determination of the magnetic configuration is also based on a method proposed by Chen et al. (2014), i.e., those filaments that follow Martin's Rule (Martin et al. 1994) are of the inverse-polarity type, and those that disobey Martin's Rule are of the normal-polarity type. By studying a sample of 571 filaments, we obtained the following results. (1) About 94.8% of the filaments in the northern hemisphere have negative helicity, and 87.4% of the filaments in the southern hemisphere have positive helicity, indicating a significant hemispheric preference of helicity. As a whole, 91.6% of our sample of erupting filaments follows the hemispheric rule of helicity sign. With the improved method for determining the filament chirality, the strength of the hemispheric rule is higher than that in previous studies. It should be noted that the statistical result is based on the erupting filaments. Those filaments that do not erupt during the disk passage are not included in our sample. (2) Following convention, we divided the filaments into three types, the quiescent type, the intermediate type, and the active-region type. It is shown that the strength of the hemispheric rule is 93% for the quiescent filaments, 95% for the intermediate filaments, and 83% for the active-region filaments. (3) Regarding the cyclic behavior of the hemispheric preference, it is found that the strength of the quiescent filaments decreases slightly from ∼97% in the rising phase to ∼85% in the declining phase, whereas the strength of the intermediate filaments keeps a high value around 96 ± 4%. Only the active-region filaments show significant variations. Their strength of the hemispheric rule rises from ∼63% to ∼95% in the rising phase, and keeps a high value of 82% ± 5% during the declining phase. However, during a half-year period around the solar maximum, the hemispheric preference totally vanishes. (4) It is found that in our sample of erupting filaments, 89% are inverse-polarity filaments that are magnetically supported by a flux rope, whereas 11% are normal-polarity filaments that are magnetically supported by a sheared arcade.

2021ApJ...910...86R__Zitrin_et_al._2015_Instance_1

One of the major endeavors of modern observational cosmology is to paint a coherent picture of the history of the universe. To this end, the final frontier remains the identification and characterization of the first sources that appeared in the universe, those which played a significant role in reionizing the intergalactic medium from a neutral state to a fully ionized one over the first billion years (corresponding to redshifts of 6 ≲ z ≲ 12). Extragalactic surveys (of deep fields as well as lensing clusters; Grogin et al. 2011; Koekemoer et al. 2011; Bradley et al. 2012; Ellis et al. 2013; Bradley et al. 2014; Schmidt et al. 2014; Treu et al. 2015; Lotz et al. 2017; Salmon et al. 2018; Coe et al. 2019) with the Hubble Space Telescope (HST) have yielded impressive gains in the number of galaxy candidates at redshifts z = 7–10, with samples reaching over 1000 objects, and revolutionized our understanding of galaxy evolution therein. Complementing these observations, the spectroscopic confirmation (e.g., Finkelstein et al. 2013; Oesch et al. 2015; Zitrin et al. 2015; Roberts-Borsani et al. 2016; Hoag et al. 2017; Stark et al. 2017; Hashimoto et al. 2018) and characterization (e.g., Laporte et al. 2017; Mainali et al. 2018; Endsley et al. 2021) of over a dozen sources has seen impressive advances with ground-based spectroscopy (e.g., probing the rest-frame UV and FIR with Keck/MOSFIRE, VLT/X-Shooter, and ALMA), particularly for the brightest and rarest objects. For the rest-frame optical, however, the Spitzer Space Telescope has, until now, afforded the only realistic means for statistical analyses. However, the Infrared Array Camera’s (IRAC) coarse spatial resolution and the limited depth probed by many surveys make robust and uncontaminated constraints on galaxy properties a challenging feat. Further advances with current facilities are challenging owing to the limited wavelength coverage of HST and the observed faintness of star-forming galaxies as one approaches redshifts of z > 10. The imminent arrival of the James Webb Space Telescope (JWST) has the potential to detect galaxies well beyond the current frontier of z ∼ 12 (e.g., Behroozi et al. 2020) thanks to the unprecedented resolution and sensitivity of its near-IR (NIR) imaging and spectroscopic capabilities, and revolutionize our current understanding of galaxy evolution.

2021MNRAS.506...52O__Carroll,_Press_&_Turner_1992_Instance_1

The SFG population bias factor, bSFG may be calculated from the ratio of galaxy to dark matter correlation functions, i.e: (27)$$\begin{eqnarray*} b_{\rm SFG}^2(z) &=& \frac{\xi _{\rm g}(r, z)}{\xi _{\rm DM}(r, z)} \nonumber \\ &=& \left(\frac{r_0(z)}{8} \right)^{\iota } \, \frac{J_2}{\sigma _8^2 \,\, \mathcal {G}^2(z)} \end{eqnarray*}$$(e.g. Kaiser 1984; Bardeen et al. 1986; Lindsay et al. 2014), where the matter fluctuation amplitude σ8 = 0.811 ± 0.006 (Planck Collaboration 2020), and $\mathcal {G}(z) = g(z)/g_0$, with g(z) as the growth factor at redshift z and g0 = g(z = 0) (e.g. Carroll, Press & Turner 1992).7 Additionally, J2 = 72/([3 − ι][4 − ι][6 − ι]2ι), and $r_0(z) = r^{\rm c}_0 (1+z)^{p}$ with p = 1 − (3 + w)/ι (Lindsay et al. 2014). Here, the choice of the parameter w reflects the clustering model adopted. In this demonstrative model, we consider only linear clustering (Overzier et al. 2003) where clustering growth is set by linear perturbation theory and w = ι − 1. We leave the investigation of alternative clustering growth models to future work – for example, stable clustering (where clusters have a fixed physical size and w = 0), co-moving clustering (where clusters have fixed co-moving size and w = ι − 3) and decaying clustering (which implies a rapid clustering decay) are also considered in the literature (Overzier et al. 2003; Kim et al. 2011; Elyiv et al. 2012). The remaining parameters in equation (27) are the power-law slope of the two-point correlation function of galaxies, ι, and the galaxy clustering length $r_0^{\rm c}$. Both of these may be estimated empirically for SFGs, and we adopt the best-fitting values of Hale et al. (2018): ι = 1.8 and $r_0^{\rm c} = 6.1\, \text{Mpc}\, h^{-1}$. These were computed from radio-selected SFGs in the COSMOS field using deep Karl G. Jansky Very Large Array (VLA) data at 3 GHz, reaching redshifts as high as z ∼ 5, thus covering our range of interest (z ≤ 3).8 The resulting bias factor from these parameter choices is higher than those computed for SFGs at other wavelengths (e.g. Gilli et al. 2007; Starikova et al. 2012; Magliocchetti et al. 2013), but this is attributed to the greater extent of the redshift distribution of the sources.

2016AandA...592A..74S__Sobolewska_&_Papadakis_(2009)_Instance_1

In Fig. B.1 we plot the soft X-ray light curves for our candidate highly variable AGN using available X-ray data taken by the satellite missions Einstein, ROSAT, XMM, Suzaku and Swift. The count rates were obtained from different archives including HEASARC, the XMM Science Archive, the Swift UKSSDC and from our own Swift XRT data analysis, and for upper limits the 1SXPS catalogue (Evans et al. 2014) and the XMM upper limit server2 were queried. The count rates of the different satellites were converted to fluxes between 0.2–2.0 keV using PIMMS3 assuming a power law with a photon index of 1.7 as a spectral shape taking into account Galactic extinction as given by Willingale et al. (2013). Sobolewska & Papadakis (2009) found a positive correlation between flux and spectral slope for a sample of bright RXTE AGN in the 2–10 keV band. This could affect the relative fluxes seen in our sample which are plotted in Fig. B.1. We have attempted to quantify this for the different detectors used in the creation of our light curves. The sample of Sobolewska & Papadakis (2009) showed spectral changes with observed power-law slope varying between 1.0 and 2.0 (see their Fig. 7). For a typical Galactic absorption of 3 × 1020 cm-2 the change from slope of 1.0 to 2.0 would alter our estimated fluxes by −14% (ROSAT), −13% (XMM-Newton), +7% (Swift-XRT), +76% (Suzaku), +25% (Einstein-IPC). The change is large for Suzaku observations since in this case we use the count rate between 2.0–10.0 keV and extrapolate it to the soft band. All other satellites are sensitive in the soft band and hence the fluxes are less dependent upon the assumed spectral index. Six sources within our sample (XMMSL1 J024916.6-041244, J034555.1-355959, J045740.0-503053, J051935.5-323928, J070841.3-493305, and J193439.3+490922) display variation in flux of a factor of ten or greater between at least one pair of XMM and Swift observations, on timescales of months to years. The ratio between the soft X-ray flux observed with Swift and that observed with XMM for the remaining sources is typically a factor of a few. We observed the two TDE candidates with XRT, and found that both had faded significantly, following expectations from previous and later fluxes and upper limits (Figs. 1p and h).

2016ApJ...826..117Y__Roux_&_Webb_2009_Instance_1

Traditionally, the Parker transport equation (Parker 1965) was used to model pickup ion acceleration at the SWTS when using a transport theory approach. However, interesting Voyager results, such as strongly fluctuating pitch-angle anisotropies upstream, the detection of highly anisotropic intensity spikes at the SWTS, the average upstream anisotropy peaking at a surprisingly high energy far above the upstream flow energy, and energetic particle spectra with multiple power-law slopes with breaking points in between that are highly variable upstream (Decker et al. 2005, 2008b; Cummings et al. 2006), suggest that transport modeling should be modified in at least two ways. First, the turbulent nature of the magnetic field conditions at the SWTS should be taken into account, and second, a transport theory that applies when particle distributions are highly anisotropic is needed, given that the Parker transport equation only holds for nearly isotropic particle distributions. In response, shock acceleration transport models were developed in recent years based on the numerical solutions of the focused transport equation (Kóta & Jokipii 2004; le Roux et al. 2007; Florinski et al. 2008a, 2008b; le Roux & Webb 2009) to take advantage of the fact that focused transport is not restricted to small pitch-angle anisotropies. This is especially advantageous at lower suprathermal particle energies upstream, where particle distributions can be sporadically strongly anisotropic (Decker et al. 2006), allowing one to model particle injection into diffusive shock acceleration (DSA) naturally at those energies. Furthermore, statistical variations in the observed magnetic field direction near the SWTS were included as a time series to model time variations in the injection and DSA of pickup ions to simulate the highly volatile nature of actual DSA at the SWTS (Florinski et al. 2008a, 2008b; le Roux & Webb 2009; Arthur & le Roux 2013). This focused transport approach should be seen as complementary to more sophisticated self-consistent shock acceleration models based on hybrid codes (Kucharek & Scholer 1995; Giacalone 2005) and particle-in-the-cell models (Scholer et al. 2003; Lembege et al. 2004), but it has the virtue of relative simplicity because different statistical plasma parameters can easily be studied separately and in combination at the SWTS to gain a more clear conceptional understanding of the role of such statistics on pickup acceleration at the SWTS.

2017MNRAS.470..713M__Farinelli_et_al._2012_Instance_1

Thereafter, we proceeded to fit the broad-band spectrum with the analytical model ‘COMPMAG’ and its updated version. The ‘COMPMAG’ model has many spectral parameters that were impossible to constrain simultaneously. Especially, β if left free preferred a value >0.9 in the fit, which is greater than the maximum possible terminal velocity at the neutron star surface. Therefore, we tested the two-component ‘COMPMAG’ model, assuming reasonable parameter values applicable to low-luminosity accretion-powered pulsars, i.e. free-fall velocity profile (η = 0.5), and β = 0.5 that corresponds to the maximum terminal velocity at the neutron star surface, and a pencil beam emission pattern. The radius of the accretion column (r0) was set to 0.25 corresponding to a radius of ∼1 km for a neutron star of mass 1.4 M⊙. The Albedo at the neutron star surface (A) was set to 1. This provided an acceptable fit to the data with acceptable and physically viable parameter values. Addition of a CRSF feature was not required for this model. The high β preferred by the fit indicated that bulk motion Comptonization (BMC) dominates the Comptonization process in X Persei. The fit also provided a low value of electron temperature (kT) consistent with the high value of β obtained (Farinelli et al. 2012). The dominance of BMC in low-luminosity pulsars, especially X-Persei has been predicted before and is consistent with our results (Becker & Wolff 2005, 2007). In Becker & Wolff (2007), the authors qualitatively described the observed spectrum of X-Persei with a pure BMC model. The obtained reduced χ2 value with ‘COMPMAG’ was higher than that obtained with the ‘newhcut’ model (1.84 for 569 dof), although there were no systematic pattern in the residuals, and the higher χ2 was mainly contributed by a higher variance in a few energy bins of the XIS spectra. Fit with the updated ‘COMPMAG2’ model was difficult with the given statistical quality of the data, as it required fitting many more additional parameters. Moreover as discussed in Farinelli et al. (2016), the ‘COMPMAG’ model provides an adequate description of the spectrum for low-luminosity pulsars, where the blackbody emission provides the major source of photons for Comptonization, appropriate for the case of X Persei. Considering the above, and as ‘COMPMAG’ is a more physical model to understand the continuum spectra of the source, we used this as our best-fitting model for the rest of the paper. As a CRSF feature is not required for this model, we cannot claim the presence of a CRSF in the average spectrum of X Persei. Table 1 summarizes the best-fitting broad-band spectral parameters obtained using the ‘newhcut’ (without addition of the CRSF) and ‘COMPMAG’ models. Fig. 3 shows the best-fitting unfolded spectrum for the best-fitting model, showing the model components.

2021AandA...650A..56R__Johnson_et_al._2017_Instance_1

The GRMHD model library is limited in that it has only a few discrete parameter values for the magnetization, black hole spin, and electron temperature distributions. Apart from increasing the number of discrete values, one could think about ways to interpolate between these using, for example, machine learning techniques (van der Gucht et al. 2020; Yao-Yu Lin et al. 2020) or fit to semi-analytic models (e.g., Broderick et al. 2016). The variability within the GRMHD models was found to be an important limitation for constraining black hole parameters, as attested by, for example, the small difference in recovered parameters between the EHT2021 and EHT2021+ arrays. The analysis pipeline may be extended to include a characterization of the source variability as part of the model selection process (e.g., Kim et al. 2016; Roelofs et al. 2017; Medeiros et al. 2017, 2018; Johnson et al. 2017; Bouman et al. 2018; Wielgus et al. 2020), which could improve the constraining power beyond the averaging method introduced here. EHT expansions are expected to make the large-scale jet visible in reconstructed images of the black hole shadow due to an increased dynamic range (Doeleman et al. 2019; Roelofs et al. 2020; Raymond et al. 2021). This connection between event-horizon scales and the extended jet has not been taken into account in the parameter estimation framework used here, as the GRMHD library images have a small field of view (160 μas). With the development of GRMHD simulations that have the ability to connect large (e.g., Fromm et al. 2017, 2018, 2019; Liska et al. 2018; Chatterjee et al. 2019) and small scales at different wavelengths and of an extended fitting framework, the constraining power is expected to improve especially for EHT extensions and space arrays. For a mass measurement, feature extraction techniques such as a ring fit (Event Horizon Telescope Collaboration 2019d,f) may be used, potentially in combination with fitting the more extended (variable) structure (Broderick et al. 2020b). Models and analysis techniques for Sgr A* and polarization could be considered as well. These possible avenues for further simulation and fitting framework development mean that the parameter constraints presented in this paper should not be interpreted as set limits on the constraining power of the considered arrays. Rather, they show what is achievable with the current state of the art.

2015MNRAS.451..353R__Naray_et_al._2006_Instance_1

The Λ cold dark matter(ΛCDM) paradigm (Blumenthal et al. 1984) predicted cuspy DM density profiles in the centre of galaxies (Navarro, Frenk & White 1996) and recent results with higher resolution seem to suggest a shallower DM density profile (Navarro et al. 2004, 2010). None the less, the past and newer developments are in contradiction with observational results of cored DM density profiles in dwarf galaxies (de Blok, McGaugh & Rubin 2001; de Blok & Bosma 2002; Swaters et al. 2003; Chemin, de Blok & Mamon 2011). This discrepancy is known as the cuspy-core problem. Many other authors, in an attempt to contribute to the solution of the cuspy-core problem, performed the RC decomposition considering a constant M/L (Carignan & Freeman 1985, 1988; Jobin & Carignan 1990; Persic & Salucci 1990; Martimbeau, Carignan & Roy 1994; Persic, Salucci & Stel 1996; Blais-Ouellette, Amram & Carignan 2001; de Blok, McGaugh & Rubin 2001; de Blok & Bosma 2002; Swaters et al. 2003; Kuzio de Naray et al. 2006; Fuentes-Carrera et al. 2007; Spano et al. 2008; Kuzio de Naray, McGaugh & de Blok 2008; Repetto et al. 2010; Chemin et al. 2011) and reinforce the evidence of a cored DM distribution in the central part of galaxies. Conversely, other authors pursue spectrophotometric and SPS studies to derive the M/L of the stellar component (Salucci, Yegorova & Drory 2008; de Denus-Baillargeon et al. 2013; Repetto et al. 2013) or at least to constrain the stellar component (Dutton et al. 2005) to avoid the disc–halo degeneracy. Salucci et al. (2008) accomplished RCs mass modelling and spectral energy distribution (SED) fitting with spectrophotometric models to obtain the disc masses of 18 Sa spiral galaxies (principally bulgeless systems) finding that by decomposing the RCs with the spectrophotometric disc masses the results are consistent with the corresponding maximum disc solution. Repetto et al. (2013) employed the Zibetti et al. (2009) method to optical (SDSS) and NIR (2MASS) images of NGC 5278 (KPG 390A) to obtain the stellar disc mass profile of that galaxy from SPS models to reproduce the RC of KPG 390A. The new strategy relied on fitting only the DM RC, obtained by subtracting the SPS baryonic disc from the observed RC of NGC 5278. The most important finding of Repetto et al. (2013) is that the favoured DM distribution is cored when the disc mass approximate to the maximum disc solution in agreement with the general belief. de Denus-Baillargeon et al. (2013) used a chemo-spectrophotometric galactic evolution model to determine the stellar M/L and perform the RC decomposition of 10 spiral and dwarf irregular galaxies from the SINGS survey (Kennicutt et al. 2003). The authors employed the settled baryonic disc as a weighting function to fit the model DM halo to the RCs of the studied subsample of galaxies, and concluded that the stellar discs obtained from their chemo-spectrophotometric models were compatible with the MDH. The few examples presented indicate that a growing effort to break the disc–halo degeneracy exists; however, the most significant contributions trying to address the cuspy-core problem still rely on the general assumption of considering the stellar M/L constant along the galactic disc. In general, it is still missing a significant endeavour to earn the DM distribution, through RC fitting, determining the disc stellar mass from SPS studies. For this reason, it is worth considering the cuspy-core problem with a different observational approach, focusing on the formulation of a general procedure to better constrain the baryonic disc mass in galaxies.

2016ApJ...826..168X__Ilgner_&_Nelson_2008_Instance_1

MRI is considered to be the most promising mechanism driving angular-momentum transport in protoplanetary disks (Balbus & Hawley 1991; Brandenburg et al. 1995; Hawley et al. 1995; Balbus et al. 1996; Balbus & Hawley 1998). However, protoplanetary disks are cold, dense, and, therefore, poorly ionized. The low level of ionization tends to decouple the disk gas from magnetic fields, which generates non-ideal MHD effects: Ohmic dissipation, ambipolar diffusion (AD), and the Hall effect (e.g., Armitage 2011; Turner et al. 2014). These effects quench MRI in different ways: Ohmic dissipation originates from collisions between electrons and neutrals, AD from collisions between ions and neutrals, and the Hall effect from drift between electrons and ions (Fleming et al. 2000; Sano & Stone 2002; Bai & Stone 2011). Ohmic dissipation operates in high-density regions with weak field, AD dominates in highly ionized and low-density regions, and the Hall effect lies in between (Fleming & Stone 2003; Bai & Stone 2011; Bai 2014). So far, the effect of Ohmic dissipation has been best studied. Investigations show the layered accretion in the inner disk, where the midplane region is “dead” due to low ionization while the surface layer is “active” due to sufficient ionization (Gammie 1996; Jin 1996; Fleming et al. 2000; Fleming & Stone 2003; Turner et al. 2007; Ilgner & Nelson 2008; Oishi & Mac Low 2009; Okuzumi & Hirose 2011). Recent works that take into account both Ohmic dissipation and AD show that AD may render the surface layer and portions of the outer disk inactive (Bai & Stone 2011; Landry et al. 2013; Kalyaan et al. 2015). Bai & Stone (2013) find that MRI is completely suppressed in the inner disk and a strong magnetocentrifugal wind is launched. Three-dimensional simulations that include all three non-ideal MHD effects are also performed (Bai 2014, 2015; Lesur et al. 2014; Simon et al. 2015). In the inner disk, the influence of the Hall effect on midplane angular-momentum transport depends on the orientation of the vertical magnetic field with the disk rotation axis. When the field is aligned with the axis, the enhanced Maxwell stress promotes angular-momentum transport. When the field is anti-aligned with the axis, the midplane remains quiescent. In the outer disk, the Hall effect has little influence on the disk turbulence. Although the inclusion of AD and the Hall effect substantially changes the level of turbulence in the protoplanetary disks, the feature that the viscosity is low in the inner disk and high in the outer disk is still valid. In this study, we assume that gas giant planets form in situ via the core accretion scenario, which implies that their formation locations are always in the low-viscosity region. Since in this study we focus on the relation between photoevaporation and planet formation and gap opening by planets in the disk, we adopt Ohmic dissipation to represent the non-ideal MHD effects on the MRI. We consider that this simplification has little influence on our main calculation results.

2017ApJ...846...28R__Kopparapu_et_al._2013_Instance_1

A question of relevance to life on other planets is whether the Snowball catastrophe occurs at lower radiative forcing at low or high obliquity. There is some conflict in the literature on the role of the Snowball bifurcation in planetary habitability. On the one hand, defining habitability in terms of surface liquid water suggests that a Snowball climate is uninhabitable, which has led various authors to propose metrics of fractional or seasonal habitability for planets with partial ice cover (e.g., Williams & Pollard 2003; Spiegel et al. 2008). On the other hand, not only did photosynthesis persist through Snowball events in Earth’ history, but the events may have crucially shaped the subsequent evolution of complex life (e.g., Hoffman & Schrag 2002; Hoffman et al. 2017; Laasko & Schrag 2017). The traditional habitable zone concept assumes a planet with a functioning silicate-weathering feedback and a positive CO2 greenhouse effect (Kasting et al. 1993; Kopparapu et al. 2013). Global glaciation may be triggered on such a planet through a rapid drawdown of atmospheric CO2 that reduces q below the thresholds at which the non-Snowball states disappear. In Earth history, this seems to have occurred through accidents of tectonics (Hoffman et al. 2017). These events are self-terminating through the suppression of silicate weathering and accumulation of a strong CO2 greenhouse. Such transitions can in principle occur anywhere within the habitable zone. Our simple model is unsuited to the tasks of diagnosing the inner edge of habitability (where the relevant physics are the runaway water vapor greenhouse and hydrogen loss to space) or the outer edge (where the relevant physics are CO2 condensation and Rayleigh scattering). However, we can compute the q value at which the bifurcation occurs as a function of obliquity and other model parameters, and whether the transition into the Snowball state occurs from a partially ice-covered state (cap or belt) or directly from the ice-free state.

2022MNRAS.515...22J__Newman_et_al._2013_Instance_1

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

2018AandA...616A..72W__Käpylä_et_al._2012_Instance_1

The Sun, our nearest late-type star exhibits a magnetic activity cycle with a period of around 11 yr. The cyclic magnetic field is generated by a dynamo operating below the surface, where it converts the energy of rotating convective turbulence into magnetic energy. We are still far from fully understanding the solar dynamo mechanism (e.g., Ossendrijver 2003; Charbonneau 2014). One reason is the limited information about the dynamics in the solar convection zone. Helioseismology has provided us with the profile of temperature and density stratification and the differential rotation (e.g., Schou et al. 1998) in the interior. Further information, such as the meridional circulation profiles, convective velocity strength, or even magnetic field distributions, are currently inconclusive or not even possible (e.g., Basu 2016; Hanasoge et al. 2016). One way to investigate how important differential rotation, meridional circulation, and turbulent convective velocities are for the solar dynamo is to use numerical simulations. Since the early simulations by Gilman (1983), the increase of computing resources has prompted several advances using numerical simulations. Nowadays, global simulations of convective dynamos are able to reproduce cyclic magnetic fields and dynamo solutions resembling many features of the solar magnetic field evolution (Ghizaru et al. 2010; Käpylä et al. 2012; Warnecke et al. 2014; Augustson et al. 2015), even long-time evolution (Augustson et al. 2015; Käpylä et al. 2016; Beaudoin et al. 2016). The cyclic magnetic field in these simulations can be well understood in terms of Parker–Yoshimura rule (Parker 1955; Yoshimura 1975; Warnecke et al. 2014), in which a propagating αΩ dynamo wave is excited; see also Gastine et al. (2012). The α effect (Steenbeck et al. 1966) describes the magnetic field enhancement from helical turbulence and the Ω effect the shearing of magnetic field caused by differential rotation. The propagation direction of the dynamo wave depends on the sign of α and shear: to generate an equatorward propagating wave, the product of α and the radial gradient of Ω must be negative (positive) in the northern (southern) hemisphere. Explaining the solar equatorward propagation of the sunspot appearance by the Parker–Yoshimura rule therefore requires either invoking the near-surface-shear layer (Brandenburg 2005), because the radial gradient is only negative in that layer (Barekat et al. 2014) and α is positive, or changing the sign of α in the bulk of the convection zone (Duarte et al. 2016) where the radial shear is positive. Furthermore, to understand the magnetic field evolution fully in the global numerical simulation one needs suitable analysis tools to extract the important contribution of turbulent dynamo effects. One of these tools is the test-field method (Schrinner et al. 2005, 2007; Warnecke et al. 2018). This method allows the determination of the turbulent transport coefficients directly from the simulations. This includes the measurement of tensorial coefficients such as α, turbulent pumping, and turbulent diffusion. The first application to global convection simulations of solar-like dynamo has already revealed that the turbulent effects can have a significant impact on large-scale magnetic field dynamics (Warnecke et al. 2018; Gent et al. 2017).

2021ApJ...909...18F__Hon_et_al._2020_Instance_1

The mechanisms of CL-AGNs are still debated. Early explanations mainly focus on the change in obscuration (Bianchi et al. 2005), while some recent studies favor the change of accretion rate (Stern et al. 2018; Sniegowska et al. 2020). Photoionization research shows that the CL behavior in CL quasars can be fully explained by the photoionization responses of the BELs to the extreme variability of the ionizing continuum (Guo et al. 2020). Besides, several objects can be interpreted as tidal disruption events (Merloni et al. 2015; Ricci et al. 2020). All of the models can generate significant variance in the observed intensity of continuum and emission lines. These models might be restricted by statistical studies after extending the sample of CL-AGNs. Several groups have been devoted to searching for new CL-AGNs, and tens of candidates have been discovered based on large optical and X-ray surveys, such as the Sloan Digital Sky Survey (e.g., LaMassa et al. 2015; MacLeod et al. 2016; Rumbaugh et al. 2018; Hon et al. 2020), intermediate Palomar Transient Factory (Gezari et al. 2017), Pan-STARRS1 (MacLeod et al. 2019), Catalina Real-time Transient Survey (Yang et al. 2018), and XMM-Newton slew survey (Zetzl et al. 2018; Kollatschny et al. 2020). In the future, the Large Synoptic Survey Telescope will regularly monitor millions of AGNs, and the number of CL-AGNs will further increase. The evolution of the AGN type can be well studied if we obtain continuous multiwavelength data of the complete changing process, and the development of time-domain surveys makes it possible to achieve this. The brightening of NGC 2617 (Shappee et al. 2014) and 1ES 1927+654 (Trakhtenbrot et al. 2019) triggered the alert of the All-Sky Automated Survey for Supernovae,7 7 http://www.astronomy.ohio-state.edu/asassn and follow-up observations confirmed these two CL-AGNs. However, so far, there are only small available data sets for most detected CL-AGNs, especially around the critical regime of transition between types 1 and 2. Moreover, previous studies rarely gave the change of geometry and kinematics in broad-line regions (BLRs).

2021ApJ...909...86X__Mouël_et_al._2017_Instance_1

The level of solar activity is typically represented by the number or area of sunspots. On the other hand, the “rush-to-the-pole” behavior of PCFs is believed to be one of the precursors for the next solar maximum (Altrock 2014). Figure 3 shows the maximum sunspot numbers (SILSO World Data Center 1914–2020) in comparison with the migration speed of PCFs (orange dots) in the northern and southern hemisphere for cycles 16–24. Within these nine solar cycles, the maximum sunspot number varies in two large periods, cycles 16–20 and 20–24. Note that even in longer time spans, such as from cycle 1 to 24, the sunspot number seems to vary periodically in different periods, like the often-discussed Gleissberg cycle (Le Mouël et al. 2017). The migration speeds of PCFs in the northern hemisphere can be separated into two groups, before and after cycle 20, which is similar to the trend found in the variation of sunspot numbers. However, the migration speed in the southern hemisphere is not correlated with the sunspot number and the migration speed in the northern hemisphere. As shown in Table 2, the Pearson correlation coefficients are below 0.5 in both hemispheres, in which the value for the northern hemisphere is relatively higher. To investigate the trend of temporal variation, the derivatives of migration speeds and sunspot number are calculated. The correlation between these derivatives represents the relationship between the temporal trends. It shows that the periodical variation of PCF migration in the northern hemisphere correlates better with the variation of sunspot numbers, but the absolute values of coefficients are not high (∼0.5). Based on this result, a causal connection between the temporal variations of PCF migration and the maximum number of sunspots cannot be established. In the SILSO World Data Center (1914–2020) archive of sunspot numbers, clear NS asymmetry after cycle 20 is noticed. But the overall levels of the sunspot numbers are the same in the northern and southern hemispheres. Therefore, the NS asymmetry, which is relatively small compared to the absolute sunspot number, will not affect the results shown in Figure 3.

2021ApJ...912..106Y__Minchev_et_al._2013_Instance_2

Our analysis on the LAMOST-RC stars by dissecting the MAPs shows that the chemical bimodality is observed throughout the Galactic disk, and the high- and low-[α/Fe] sequences are corresponding to the thick and thin disks of the Milky Way, respectively. How to explain the formation mechanism of the stellar thin and thick disks is beyond the scope of this paper, but our results provide some observational constraints to the model of the chemodynamical evolution of the Milky Way disk. Our flared vertical profiles for the thin and thick disks are in good agreement with the prediction of the thin+thick flaring disk model (López-Corredoira & Molgó 2014), and are consistent with the number simulations of the chemodynamical evolution in Galactic disks formed in the cosmological context (Minchev et al. 2013, 2014, 2015, 2017), as well as the cosmological zoom simulation of VINTERGATAN (Agertz et al. 2021). These model simulations suggest that the vertical flaring trends are a natural consequence of inside-out, upside down growth coupled with disk flaring (see also Bird et al. 2013; García de la Cruz et al. 2021), which allows for the low-[α/Fe] stars to exist several kpc above the disk’s midplane. As analyzed by B16, the exponential flaring profiles for the low-[α/Fe] MAPs suggests that radial migration played an important role in the formation and evolution of the thin disk. Radial migration of stars via cold torquing, also known as “churning,” by a bar and spiral waves (Minchev et al. 2013) then allows for the populations to spatially overlap in the solar neighborhood. Similar to the flared thin disk, the flaring profile for the high-[α/Fe] MAP indicates the radial migration has occurred in the formation of the thick disk as suggested by model simulations (e.g., Schönrich & Binney 2009; Minchev et al. 2015; Li et al. 2018). Of course, we cannot rule out the other formation scenarios of the thick disk, such as the accreted gas from satellites (Brook et al. 2004), accreted stars from galaxy mergers (Abadi et al. 2003), or from disk-crossing satellites heating up the thin disk (Read et al. 2008). On the other hand, the broken exponential radial profiles for the thin and thick disks cannot be explained by any model of the galactic disks. In fact, nearly all the models we mentioned above present a single-exponential profile decreasing with the increasing of R (e.g., Minchev et al. 2015; Li et al. 2018; Agertz et al. 2021). And the smooth downtrend of radial profile in the outer disk R > Rpeak, as shown in Figure 10, means that there is no cut-off of the stellar component at R = 14–15 kpc as stated by Ruphy et al. (1996), which is also discovered by B16.

2021AandA...653A..32D__Kriek_et_al._2006_Instance_1

The choice of SFH to infer evolutionary parameters intrinsically carries a degeneracy with the adopted functional form. A more direct approach is to quantify the light-weighted contribution of recent star formation by measuring the relative contribution to the integrated stellar spectrum of short-lived massive stars with respect to long-lived lower-mass stars. Balmer absorption lines reach their maximum strength in A-type stars with a spectral break at 3646 Å. Stars of lower mass and lower effective temperature produce metal absorption lines (CaII H & K, Fe, and Mg) which result in a sharp spectral break at 4000 Å. Moreover, the underlying continuum changes shape with time, progressively losing emission in the NUV-blue spectral range while flattening in the NIR. The different evolutionary rates of the stars producing the lines and their fractional contribution to the optical light at fixed mass enable tracing the evolutionary stage of a galaxy. In Fig. 11 (upper panels) we show the evolution of the spectral break measured through the DB definition (Kriek et al. 2006) and the Dn4000 definition (Balogh et al. 1999), as well as the relative strength (the ratio) between the two (lower left panel). Lighter shaded curves show the variation with increasing duration of star formation. The ratio is shown as a function of age of composite templates built with a short truncated SFH. The ratio is only mildly dependent on dust reddening because the two indices share a similar wavelength range. Moreover, the two indices are fairly robust against low resolution. The ratio varies strongly during the first 1 Gyr or so, reaching its maximum around 0.3–0.5 Gyr. Eventually, it drops below 1 when the light-weighted contribution from A-type stars fades away. Constant star formation instead results in a ratio of ∼1.1 that is rather constant with time. Varying the metallicity of the input templates has the effect of anticipating the transition to DB/Dn4000 > 1. This effect is strongest when supersolar metallicity (2.5Z⊙) is adopted in which case the transition is reached at 0.9 Gyr. We suggest that this ratio could be used to spot PSB galaxies with high dust attenuation along and across the UVJ diagram when high-resolution spectra are unavailable.

2016AandA...588A...2L__Mätzler_(1998)_Instance_2

H2O ice on Pluto has long escaped spectroscopic detection, and based on initial New Horizons data appears to be exposed only in a number of specific locations, usually associated with red color, suggestive of water ice/tholin mix (Grundy et al. 2015; Cook et al. 2015). Nonetheless, water ice is likely to be ubiquitous in Pluto’s near subsurface, given its cosmogonical abundance, Pluto’s density, and its presence on Charon’s surface6. Absorption coefficients for pure water ice (kH2O) at sub-mm-to-cm wavelengths are discussed extensively by Mätzler (1998), who also provides several analytic formulations to estimate them as a function of frequency and temperature along with illustrative plots. We use the Mishima et al. (1983) formulation (see Appendix of Mätzler 1998). Its applicability is normally restricted to temperatures above 100 K, but Fig. 2 of Mätzler (1998) indicates the trend with temperature. Absorption coefficients extrapolated to 50 K (estimated as half the values at 100 K) are shown in Fig. 5. At 500 μm, our best estimate is kH2O = 0.25 cm-1, comparable to the above values for CH4 and N2 ices. The corresponding penetration length is therefore comparable to the diurnal skin depth but remains negligible compared to the seasonal skin depth, even for seasonal Γ = 25 MKS. According to these calculations, the seasonal layer would be probed only at a wavelength of ~4 mm and beyond. We also remark that the expression from Mishima et al. (1983) would give a penetration depth of 56 m at 2.2 cm, which is an order of magnitude larger than indicated by the laboratory measurements of Paillou et al. (2008). In addition, small concentrations of impurities can dramatically reduce the microwave transparency of water ice (e.g., Chyba et al. 1998 and references therein). Therefore, the above calculations likely indicate upper limits to the actual penetration depth of radiation in a H2O ice layer, from which we conclude that the seasonal layer is not reached at the Herschel wavelengths.

2018MNRAS.477..957D__Slee_et_al._2001_Instance_1

The role of cluster mergers in producing shocks underlying radio relics at cluster peripheries is well supported by observational evidence (Giovannini, Tordi & Feretti 1999; Bagchi et al. 2006; van Weeren et al. 2009; Venturi et al. 2013). A different class of relics, proposed to be fading radio galaxy lobes or such lobes revived due to adiabatic compression (Enßlin & Gopal-Krishna 2001), are also well known to occur in clusters. Examples of relics in this category are those in Abell 4038 (Slee & Roy 1998; Kale & Dwarakanath 2012) and Abell 85 (Slee et al. 2001). In A168 we find an arc-like relic at the periphery (B) and a smaller steep-spectrum relic (A) in its wake, as seen projected in the plane of the sky. The intracluster medium (ICM) in the cluster is elongated along the north–south direction and the orientation of B is perpendicular to this direction. Merger-shock-related relics have been found to be oriented preferentially perpendicular to the elongation axis of the ICM (van Weeren et al. 2011). The flat spectral index of B, arc-like morphology and orientation thus support the scenario that a cluster merger along the north–south direction led to an outgoing merger shock that accelerated electrons, which are detected as relic B. Relic A has a steep and curved spectrum (Fig. 3) indicative of an ageing population of relativistic electrons. We propose that relic A is a candidate adiabatically compressed lobe of a radio galaxy, the compression having been caused by the outgoing shock at B. Simulations of adiabatically compressed cocoons of radio galaxies have shown that, as compression proceeds, the cocoon is torn into filamentary structures, which can appear like a single torus or multiple tori at late stages (Enßlin & Brüggen 2002). The morphology of relic A is complex and filamentary, which compares well with the predicted structures of compressed cocoons. The morphology of B is not smooth at the outer boundary, but shows kink-like features connected to A, implying a possible distortion due to the presence of a radio cocoon in the path of the outgoing shock that led to the formation of A.

2016ApJ...830...15J__Mathieu_et_al._1997_Instance_1

If PTFO 8-8695 is accreting material onto the star from a gas disk devoid of small grains, the excess Hα emission may result entirely from the accreting material whether or not there is a planetary companion present. This accretion-related emission would presumably be similar to Hα emission seen in other CTTSs, many of which also have close companions. If there is a low-mass companion to PTFO 8-8695, accretion from a disk may be through accretion streams such as those proposed by Artymowicz & Lubow (1996) (see also Günther & Kley 2002). At this time, it is not known if a planetary mass companion can excite accretion streams such as those modeled by Artymowicz & Lubow (1996) and Günther & Kley (2002). A few CTTSs binaries are thought to potentially be accreting through accretion streams. These include DQ Tau (Basri et al. 1997; Mathieu et al. 1997), UZ Tau E (Jensen et al. 2007), AK Sco (Alencar et al. 2003), KH 15D (Hamilton et al. 2012), and the eclipsing binary system CoRoT 223992193 in NGC 2264 (Gillen et al. 2014). None of these stars shows the type of Hα variations seen in PTFO 8-8695 where the accretion-related emission appears to move from one side of the line profile to the other as it spirals onto one or both of the stars. This type of line profile behavior is also not seen in the Hα profile variations of single CTTSs in extensive studies of their line profile variability (e.g., Giampapa et al. 1993; Johns & Basri 1995a, 1995b; Johns-Krull & Basri 1997; Oliveira et al. 1998; Alencar et al. 2001), nor is it predicted from theoretical models of magnetospheric accretion such as those shown in Kurosawa & Romanova (2013). While we cannot completely rule out accretion from a tenuous disk as the source of the excess Hα emission observed in PTFO 8-8695, we argue that this is not the most likely explanation of the observed emission. Deep mid-IR or millimeter continuum observations, or a deep search for close circumstellar disk gas emission (e.g., H2 emission, see France et al. 2012), could shed light on whether there is a tenuous disk around this star feeding accretion onto it.

2018AandA...617A..86L__Tian_et_al._2016_Instance_1

Using AIA intensity images in six EUV bandpasses, a differential emission measure (DEM) analysis (Cheng et al. 2012; Shen et al. 2015) is performed for the solar flare at 17:03:37 UT, when the oscillations are pronounced. Figure 8 panels b and c plot the DEM profiles in the flaring loop and the background corona, respectively. They contain the same region with an FOV of 3″ × 3″, as enclosed by the red boxes in Fig. 1e. The black profile in each panel is the best-fit DEM solution to the observed fluxes. The colored rectangles represent the errors of the DEM curve, which are calculated from 100 Monte Carlo (MC) realizations of the observational data (Cheng et al. 2012; Tian et al. 2016; Li et al. 2017b). The average temperature (T) and emission measure (EM) inside and outside (background corona) of the flaring loop are also estimated according to their errors, respectively. For example, the confident temperature (log T) range inside the flaring loop is 6.0−7.5, while that outside of the flaring loop is 5.8−7.1, since the temperatures in solar flare are much higher than that in the background corona. Therefore, the number density inside the flaring loop can be estimated with n e = E M / w $ n_e\,{=}\,\sqrt{EM/w} $ by assuming a filling factor of 1.0 (Tian et al. 2016; Li et al. 2017b), and we can obtain a lower limited density inside the flaring loop of ∼4.7 × 1010 cm−3. On the other hand, the effective LOS depth ( l ≈ H π r ∼ 4 × 10 10 $ l\,{\approx}\sqrt{H\pi r}\,{\sim}\,4\,{\times}\, 10^{10} $ cm), instead of the loop width, is applied to calculate the number density outside of the flaring loop (Zhang & Ji 2014; Zucca et al. 2014; Su et al. 2016; Li et al. 2017b), and we get 9.1 × 108 cm−3. Finally, a number density ratio (rd = n0/ne) of ∼0.02 between outside and inside of the flaring loop is determined, which is very close to the density contrast from recent observations (Tian et al. 2016; Li et al. 2017b).

2022AandA...666A.141M__Hopkins_et_al._2006_Instance_1

Many mechanisms that probably lead to quenching have been proposed, and surely we need some parameters to discriminate between these mechanisms. One of such critical parameters we are looking for is the quenching timescale, which varies from one mechanism to another. Most of these timescales are obtained from simulations (Wright et al. 2019; Wetzel et al. 2013; Walters et al. 2022). Among mass-dependent quenching mechanisms, the supernova feedback is a strong physical process that quickly quenches star formation in ∼0.1 Gyr (Ceverino & Klypin 2009). On the other hand, the AGN feedback timescale is still under debate. Quasar mode AGN feedback is a strong process. Quasars’ lifetimes are not long ( 0.1 Gyr, Hopkins et al. 2006), and the gas outflow driven by quasars can quench star formation at million-year-level timescales (Smethurst et al. 2021). On the other hand, the radio mode of AGN feedback is a slow process (Best et al. 2005); it takes up to and beyond 1 Gyr to establish a balance between cooling and heating to reach a low star formation rate phase (Fabian 2012). In Schawinski et al. (2014) the authors maintain that the timescale of AGN feedback leading to a quenching can be related to the host galaxy type. Furthermore, Hirschmann et al. (2017) simulated the star formation history (SFH) of galaxies with AGN and found that the quenching timescale can have a wide range, from a few hundred Myr to a few Gyr. For environmental quenching mechanisms, strangulation is a long-term process that lasts a few billion years (Peng et al. 2015). Merger-driven quenching does not happen directly after galaxy merger events; a median delay time of 1.5 Gyr is expected, and the timescale varies over a wide range (Rodríguez Montero et al. 2019). Ram pressure stripping is a rapid type of quenching, with a timescale of ∼0.2 Gyr (Steinhauser et al. 2016). Thus, we can use the quenching timescale to determine some of the physical mechanisms involved.

2015ApJ...808...56M__Beaulieu_et_al._2011_Instance_2

The field of extrasolar planetary transits is one of the most productive and innovative subject in astrophysics in the last decade. Transit observations can be used to measure the size of planets, their orbital parameters (Seager and Mallén-Ornelas 2003), and stellar properties (Mandel & Agol 2002; Howarth 2011), to study the atmospheres of planets (Brown 2001; Charbonneau et al. 2002; Tinetti et al. 2007), and to detect small planets (Miralda-Escudé 2002; Agol et al. 2005) and exomoons (Kipping 2009a, 2009b). In particular, the study of planetary atmospheres requires a high level of photometric precision, i.e., one part in ∼104 in stellar flux (Brown 2001), which is comparable to the effects of current instrumental systematics and stellar activity (Berta et al. 2011; Ballerini et al. 2012), hence the necessity of testable methods for data detrending. In some cases, different assumptions, e.g., using different instrumental information or functional forms to describe them, leed to controversial results even from the same data sets; examples in the literature are Tinetti et al. (2007), Ehrenreich et al. (2007), Beaulieu et al. (2008) and Désert et al. (2009, 2011) for the hot-Jupiter HD 189733b, and Stevenson et al. (2010), Beaulieu et al. (2011) and Knutson et al. (2011, 2014) for the warm-Neptune GJ436b. Some of these controversies are based on Spitzer/IRAC data sets at 3.6 and 4.5 μm. The main systematic effect for these two channels is an almost regular undulation with period ∼3000 s, so called pixel-phase effect, as it is correlated with the relative position of the source centroid with respect to a pixel center (Fazio et al. 2004; Morales-Caldéron et al. 2006). Conventional parametric techniques correct for this effect by dividing the measured flux by a polynomial function of the coordinates of the photometric centroid; some variants may include time-dependence (e.g., Stevenson et al. 2010; Beaulieu et al. 2011). Newer techniques attempt to map the intra-pixel variability at a fine-scale level, e.g., adopting spatial weighting functions (Ballard et al. 2010; Cowan et al. 2012; Lewis et al. 2013) or interpolating grids (Stevenson et al. 2012a, 2012b). The results obtained with these methods appear to be strongly dependent on a few assumptions, e.g., the degree of the polynomial adopted, the photometric technique, the centroid determination, calibrating instrument systematics over the out-of-transit only or the whole observation (e.g., Beaulieu et al. 2011; Diamond-Lowe et al. 2014; Zellem et al. 2014). Also, the very same method, applied to different observations of the same system, often leads to significantly different results. Non-parametric methods have been proposed to guarantee a higher degree of objectivity (Carter & Winn 2009; Thatte et al. 2010; Gibson et al. 2012; Waldmann 2012, 2014; Waldmann et al. 2013). Morello et al. (2014, 2015) reanalyzed the 3.6 and 4.5 μm Spitzer/IRAC primary transits of HD 189733b and GJ436b obtained during the cryogenic regime, so called “cold Spitzer” era, adopting a blind source separation technique, based on an Independent Component Analysis (ICA) of individual pixel timeseries, in this paper called “pixel-ICA”. The results obtained with this method are repeatable over different epochs, and a photometric precision of one part in ∼104 in stellar flux is achieved, with no signs of significant stellar variability as suggested in the previous literature (Désert et al. 2011; Knutson et al. 2011). The use of ICA to decorrelate the transit signals from astrophysical and instrumental noise, in spectrophotometric observations, has been proposed by Waldmann (2012, 2014) and Waldmann et al. (2013). The reason to prefer such blind detrending methods is twofold: they require very little, if any, prior knowledge of the instrument systematics and astrophysical signals, therefore they also ensure a higher degree of objectivity compared to methods based on approximate instrument systematics models. As an added value, they give stable results over several data sets, also in those cases where more conventional methods have been unsuccessful. Recently, Deming et al. (2015) proposed a different pixel-level decorrelation method (PLD) that uses pixel timeseries to correct for the pixel-phase effect, while simultaneously modeling the astrophysical signals and possible detector sensitivity variability in a parametric way. PLD has been applied to some Spitzer/IRAC eclipses and synthetic Spitzer data, showing better performances compared to previously published detrending methods.

2022MNRAS.513.2194I___2017_Instance_1

There are several assumptions related to the FB origin. One of the first intriguing assumptions of the FB origin was the scenario of the evolution of the relativistic jet remnant. Presumably, relativistic jets existed during the recent activities of Sgr A* about 107 yr ago. These assumptions lead to many interesting discussions about FB’s inheritance from relativistic jets (Guo et al. 2012; Yang et al. 2012; Zhang & Guo 2020). The FBs are presumably filled with matter from jets originating from the supermassive black hole (SMBH) vicinity. The expansion process could occur at the front of a shock wave that has collided with the external environment and formed the boundaries of the currently observed FBs. On the other hand, Su & Finkbeiner (2012) provided the evidence of the possibility of a gamma jet existence, which could also lead to the filling of such a structure as FBs by hot particles. There is another possibility of the FB formation due to the tidal disruption of stars (Cheng et al. 2011; Chernyshov et al. 2014, 2017) and the acceleration of individual particles by the arising shock waves. The FB primary structure originating from supernova explosions in the central molecular zone (CMZ) is also possible (Lacki 2014). The young stars’ formation and the stellar winds may also have a role in the FB origin, including the CMZ life cycle (Armillotta et al. 2019). Cheng et al. (2011) also described a scenario of FBs’ periodic feeding by supernova explosions. Various interesting scenarios for the FB formation were also discussed by Mertsch & Petrosian (2019). Comparative analysis of the possible scenarios of FB origin, in general, has been of great interest for explaining its nature since discovery in 2010. It is also interesting to note that all scenarios that are mentioned above may complement each other. FBs may have really formed from relativistic jets and energized by intensive periodic (on average, once every 104 yr) processes within. Stellar plasma injected by supernova shock waves may be one of the important additional channels for the supply of energy to a stationary bubble formed from a jet.

2019ApJ...885..168O__Thomas_et_al._2004_Instance_1

Tidal heating of Io has been shown to be responsible for its widespread volcanism. The tidal heating rate of Jupiter’s tidally locked moon, , driven by forced eccentricities, e, locked by Europa and Ganymede’s Laplace resonance with Io, is the dominant interior heating source. Similarly, the tidal heating of an exomoon will likely dominate the interior energy budget due to the additional stellar tide. Consequently, the tidal heating rate is orders of magnitude higher than at Io, which for an exo-Io of similar rheological properties ( , Rs = RIo, ρs = ρIo) can be written as (Cassidy et al. 2009; Equations (19) and (20)) 3 where υ = 3 × 10−7 cm3 erg−1, and τs = τp/5 based on the tidal stability criterion discussed in Section 2. For utility, we describe the exo-Io’s tidal efficiency as , which can readily be computed for any three-body system as tabulated in Table 4. The enhanced tidal heating described in Equation (3) will also contribute to the surface temperature T0 = Teq + ΔT0, which is very roughly approximated as 4 where σsb is the Stefan–Boltzmann constant and Teq. At Io, the total neutral volcanic content (SO2, SO, NaCl, KCl, Cl, and dissociation products) ejected to space (Section 4.2.1) by the incident plasma is estimated to be, on average, ∼1000 kg s−1 (e.g., Thomas et al. 2004), varying within an order of magnitude over decades of observations (Burger et al. 2001; Wilson et al. 2002; Thomas et al. 2004). While the source of the dominant gas SO2 is ultimately tidally driven volcanism, the near-surface atmosphere is mostly dominated by the sublimation of SO2 frost (Tsang et al. 2016). By observing the atmospheric evolution of the SO2 column density with heliocentric distance, Tsang et al. (2013) estimated the direct volcanic component to be Nvolc ∼ 6.5 × 1016 cm−2, typically of the total observed SO2 column density. Ingersoll (1989) demonstrated the relative contributions due to both sublimation and volcanic sources in maintaining Io’s atmosphere and established a relationship relating the volcanic source rate to the volcanically supplied atmospheric pressure: 5 This expression also gives the volcanic column density , where g is the acceleration due to gravity. Adopting an observed atmospheric temperature of Tatm = 170 K by Lellouch et al. (2015) corresponding to an atmospheric scale height of H = 12 km, a thermal velocity equal to 150 m s−1, and a sticking coefficient α = 0.5 for the SO2 mass of 64 amu yields a volcanic source rate of ∼ 6.9 × 106 kg s−1 of SO2 integrated over Io’s mass MIo. The average volumetric mixing ratio for NaCl to SO2 at Io is observed to be XNaCl ∼ 3 × 10−3 (Lellouch et al. 2003). This leads to a source rate of ∼ 7.4 × 103 kg s−1 of NaCl, somewhat larger than but reasonably consistent with the direct measurement of the NaCl volcanic source rate of (0.8–3.1) × 103 kg s−1 (Lellouch et al. 2003). From these estimates, we will adopt ∼3 × 103 kg s−1 of Na i as the volcanic source rate for Io.

2020ApJ...901...41S__Laursen_et_al._2013_Instance_1

Observations have shown that the shape of the Lyα line is diverse. It includes broad damped absorption profiles, P-Cygni profiles, double-peak profiles, pure symmetric emission profiles, and combinations thereof (Kunth et al. 1998; Mas-Hesse et al. 2003; Shapley et al. 2003; Møller et al. 2004; Noll et al. 2004; Tapken et al. 2004; Venemans et al. 2005; Wilman et al. 2005). This variety can be understood through a detailed radiative transfer calculation, which is analytically solvable only for simple cases (e.g., a static, plane-parallel slab by Harrington 1973 and Neufeld 1990, and a static uniform sphere by Dijkstra et al. 2006). Later, numerical algorithms based on Monte Carlo techniques were developed to solve radiative transfer for more general cases. Now theoretical studies mostly rely on them (e.g., Spaans 1996; Loeb & Rybicki 1999; Ahn et al. 2000, 2002; Zheng & Miralda-Escudé 2002; Richling 2003; Cantalupo et al. 2005; Dijkstra et al. 2006; Hansen & Oh 2006; Tasitsiomi 2006; Verhamme et al. 2006, 2015; Laursen et al. 2013; Behrens et al. 2014; Duval et al. 2014; Gronke et al. 2015; Smith et al. 2019; Lao & Smith 2020; Michel-Dansac et al. 2020). Meanwhile, a galaxy model needs to be constructed to perform such a radiative transfer calculation. One can adopt a realistic galaxy model from hydrodynamical simulations. Galaxies from such simulations can be useful for performing a statistical study of Lyα properties, but they cannot be directly used to model individual galaxies in observations. Therefore it would be better to adopt a simple but manageable toy model for the purpose of reproducing observations. One example for such models is a shell model, in which a central Lyα source is surrounded by a constantly expanding, homogeneous, spherical shell of H i medium with dust. Although this shell model has surprisingly well reproduced many observed Lyα line profiles (e.g., Ahn 2004; Schaerer & Verhamme 2008; Verhamme et al. 2008; Schaerer et al. 2011; Gronke et al. 2015; Yang et al. 2016; Gronke 2017; Karman et al. 2017), because of its extreme simplicity and contrivance, there is still room for improvement (e.g., see Section 7.2 in Yang et al. 2016; Orlitová et al. 2018).

2022MNRAS.514.1961R__Prochaska_&_Zheng_2019_Instance_2

Along with the time-domain detections, we identified J173438.35-504550.4 as a potential host galaxy for FRB 20201123A using robust statistical treatment given the relatively small localization error region. At face value, the low redshift of J173438.35-504550.4 appears at odds with the large dispersion measure for FRB 20201123A (${\rm DM}_{\rm FRB}\approx 434 \, {\rm pc \, cm^{-3}}$). Our Galaxy, however, contributes ${\rm DM}_{\rm ISM}\approx 200 \, {\rm pc \, cm^{-3}}$ (NE2001 gives 229 ${\rm pc \, cm^{-3}}$ and YMW16 gives 162 ${\rm pc \, cm^{-3}}$) from its interstellar medium and a presumed ${\rm DM}_{\rm Halo}\sim 50 \, {\rm pc \, cm^{-3}}$ from its halo (Prochaska & Zheng 2019). This leaves ${\approx}180 \, {\rm pc \, cm^{-3}}$ for the cosmos (DMcosmic) and the host (DMhost). At z = 0.05, the average cosmic contribution is $\langle {\rm DM}_{\rm cosmic}\rangle \sim 42\, {\rm pc \, cm^{-3}}$ (Macquart et al. 2020) but the intrinsic scatter in this quantity is predicted to be large. Adopting the best-fitting model to the Macquart relation by Macquart et al. (2020), the 95 per cent confidence interval is ${\rm DM}_{\rm cosmic}= [15,125] \, {\rm pc \, cm^{-3}}$. Allowing for the maximum value of this interval (which would imply a significant foreground galaxy halo), we recover a minimum host contribution of ${\rm DM}_{\rm host, min} \approx 60~\rm pc~cm^{-3}$. This is consistent with estimates for host galaxy contributions from theoretical and empirical treatments (Prochaska & Zheng 2019; James et al. 2022). For a true DMcosmic value of this sightline closer to (or below) the mean, the host contribution would exceed $100 \, {\rm pc \, cm^{-3}}$. Such values are inferred for other FRB hosts (e.g. FRB 20121102A; Tendulkar et al. 2017). In conclusion, we find no strong evidence to rule out the association with J173438.35-504550.4 based on its redshift and DMFRB. The significant host contribution to the DM, combined with the scattering in FRB 20201123A possibly originating in the host, shows that it shares similarities with other highly active, repeating FRBs like FRB 20121102A and FRB 20190520A and potentially resides in a turbulent and dense environment within the host.

2022ApJ...927..145S__Cui_et_al._2012_Instance_1

It is generally thought that the stellar halo of the Milky Way (MW) contains the fossil record of the MW’s formation history imprinted in its kinematical and chemical properties. Since Eggen et al. (1962) showed a model of the MW’s formation process from the kinematic analysis of halo stars in the solar neighborhood, many studies of this Galactic fossil component have been carried out using a large number of newly available halo samples, with their assembly requiring considerable observational efforts over the past decades. These include, for example, the Hipparcos Catalog, obtained from the first astrometry satellite (Perryman et al. 1997), and spectroscopic catalogs such as RAVE (Steinmetz et al. 2006), SEGUE (Yanny et al. 2009), LAMOST (Cui et al. 2012; Zhao et al. 2012), GALAH (De Silva et al. 2015), APOGEE (Majewski et al. 2017), H3 (Conroy et al. 2019), and more. Perhaps the most significant impacts on this field of research have been brought about by the second astrometry satellite, Gaia. The Gaia catalog (Gaia Collaboration et al. 2016, 2018, 2021) provides trigonometric parallaxes and proper motions for billions of Galactic stars with unprecedented high accuracy. Based on the astrometry data of the stars in the Gaia catalog combined with that of the spectroscopic catalogs, the MW’s new dynamical maps have been drawn (e.g., Belokurov et al. 2018; Helmi et al. 2018; Myeong et al. 2018a, 2018b; Beane et al. 2019; Hagen et al. 2019; Iorio & Belokurov 2019; Anguiano et al. 2020; Cordoni et al. 2021; Koppelman et al. 2021), and new aspects of the MW’s formation and evolution history have been revealed (e.g., Antoja et al. 2018; Sestito et al. 2019; Wyse 2019). In particular, the Gaia catalog has enabled the discovery of new substructures in the MW’s stellar halo (e.g., Koppelman et al. 2019; Myeong et al. 2019; Li et al. 2020) that are remnants of past merging/accretion events associated with the MW’s formation history (e.g., Fernández-Trincado et al. 2020; Naidu et al. 2020, 2021).

2020MNRAS.498..385J__Roman-Duval_et_al._2010_Instance_1

In the upper panel of Fig. 17, we demonstrate that the mass distribution of GMCs in each galaxy reproduces the upper limit of ∼3 to 8 × 106 M⊙ observed by Rosolowsky et al. (2003) in M33, by Freeman et al. (2017) in M83 and by Miville-Deschênes et al. (2017) and Colombo et al. (2019) in the Milky Way. This upper limit has been predicted to arise due to a combination of centrifugal forces and stellar feedback (Reina-Campos & Kruijssen 2017). We also find a turnover in the mass spectrum between 104.8 and 105 M⊙, consistent with the behaviour of the GMC mass distribution in the Milky Way (Miville-Deschênes et al. 2017), although we cannot rule out the possibility that the turnover we see in the simulations is influenced by their limited mass resolution. Above the turnover, the GMC mass function has a power-law form with β ∼ 1.9, close to the observed range of β ∈ [1.6, 1.8] for clouds in the Milky Way (Solomon et al. 1987; Williams & McKee 1997; Heyer et al. 2009; Roman-Duval et al. 2010; Miville-Deschênes et al. 2017; Colombo et al. 2019) over the same mass range (log M ∈ [4.8, 6.5]). In the lower panel of Fig. 17, we display the spectrum of GMC sizes for each simulated galactic disc, given by the effective cloud radius ℓeff, such that (42)$$\begin{eqnarray*} \ell _{\rm eff} = 1.91 \sqrt{\Delta \ell _{\rm maj}^2 + \Delta \ell _{\rm min}^2}, \end{eqnarray*}$$where Δℓmaj and Δℓmin are the second moments of an ellipse fitted to the footprint of each cloud in the galactic mid-plane, using astrodendro. We adopt this definition of the cloud size in order to make a direct comparison to works in the existing observational literature (e.g. Solomon et al. 1987; Bertoldi & McKee 1992; Rosolowsky & Leroy 2006; Colombo et al. 2019). The factor of 1.91 is the correction first defined by Solomon et al. (1987) for converting the RMS cloud extent to an estimate of the spherical cloud size. The smallest resolved cloud has a diameter of 18 pc, so we do not capture the observed turnover of the distribution at ∼30 pc (Miville-Deschênes et al. 2017). Likewise, our largest clouds slightly exceed the truncation size of 70 pc observed by Colombo et al. (2019), with a maximum diameter of ∼200 pc. Importantly, we do approximately reproduce the observed power-law slope of $\mathrm{d}N/\mathrm{d}R \sim R^{-\beta _\ell }$ with βℓ ∼ 2.8 (Colombo et al. 2019). This is given by the black line in Fig. 17, while our best fit to the simulation data over the observed range of cloud sizes ℓeff ∈ [18, 70] pc is given by the purple line, with a slightly shallower slope of βℓ = 2.43 ± 0.06.

2016MNRAS.459.3585G__Tiengo_&_Mereghetti_2007_Instance_1

In the following, we consider an NS with mass MNS = 1.5 M⊙ and radius RNS = 12 km, which is compatible with expectations from modern equations of state such as APR or BSk21 models (Akmal, Pandharipande & Ravenhall 1998; Goriely, Chamel & Pearson 2010). The value of the radius is also in agreement with the estimates derived by Sartore et al. (2012) and Ho et al. (2007), assuming a source distance of 120 pc (Walter et al. 2010). This choice translates into a gravitational redshift factor at the star surface 1 + z = 1.26. The rotational period of RX J1856 is P = 7 s and the X-ray pulsed fraction is the lowest among the XDINSs, ∼1.3 per cent (Tiengo & Mereghetti 2007). The polar strength of the dipole field is taken to be Bp = 1013 G, a value which is somehow intermediate between the spin-down measure and the estimates from spectral fitting (Ho et al. 2007; van Kerkwijk & Kaplan 2008). We assume that the magnetic field is dipolar (see Section 2) and that the surface temperature distribution is that induced by the core-centred dipole. Since for fields higher than ∼1011 G, electron conduction across the field lines is strongly suppressed, the meridional temperature variation is Tdip ≃ Tp|cos θB|1/2, where Tp is the polar value of the temperature (e.g. Greenstein & Hartke 1983). We checked that this simple expression for Tdip differs only slightly ( ≲ 6  per  cent) from the more accurate formula by Potekhin, Pons & Page (2015) for θ ≲ 80°. However, taken face value, the previous expression for Tdip yields vanishingly small values near the magnetic equator. The analysis of Sartore et al. (2012) has shown that the X-ray spectrum of RX J1856 is best modelled in terms of two blackbody components with $kT^\infty _\mathrm{h}\sim 60$ eV and $kT^\infty _\mathrm{c}\sim 40$ eV. To account for this in a simple way, we actually adopt a temperature profile given by Ts = max (Tdip, Tc) with Tp = Th, where $T_\mathrm{h,c}=T^\infty _\mathrm{h,c}/(1+z)$.

2020MNRAS.491.5406T__Chisholm_et_al._2017_Instance_1

We show the mass-loading factors required to simultaneously reproduce the stellar metallicity and SFR of passive galaxies in the bottom panel of Fig. 9. We find that the mass-loading factor strongly decreases with increasing stellar mass. This anticorrelation between stellar mass and λeff is qualitatively consistent with the mass dependence in theoretical models, which predict that $\lambda \propto M_*^{-1/3}$ (Murray, Quataert & Thompson 2005) for momentum-driven winds and $\lambda \propto M_*^{-2/3}$ for energy-driven winds (e.g. Dekel & Silk 1986), as well as other observational evidence (e.g. Heckman et al. 2015; Chisholm et al. 2017; Fluetsch et al. 2019). Our results indicate that ‘effective’ outflows (which are capable of permanently removing gas from the galaxy) are, together with starvation, of increasing importance in low-mass galaxies. In particular, since the rate at which gas is locked up into long-lived stars is given by (1 − R)Ψ = 0.575Ψ, and the rate at which gas is ejected from the galaxy is given by λeffΨ, then, for galaxies with log (M*/M⊙) 10.2, the rate at which gas is lost through galactic winds is roughly 1–3 times larger than the rate at which gas is locked up into long-lived stars. Clearly outflows play an essential role in depleting the gas reservoir of low-mass galaxies during the quenching phase. Outflows are relatively weaker (λeff ≤ 0.6) in more massive galaxies (log (M*/M⊙) > 10.2), with starvation becoming the dominant quenching mechanism, as illustrated in Fig. 9. However, outflows still play an important role in quenching star formation, as comparable amounts of gas are removed through galactic winds and through the formation of long-lived stars. Although these massive galaxies may be ejecting large amounts of gas in the form of outflows (i.e. a large λ), our results suggest that these ejection events are short lived and/or most of the outflowing gas does not escape the galaxy and is instead recycled (i.e. a relatively small λeff).

2022MNRAS.512.4280P__Umetsu_et_al._2016_Instance_2

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.

2020MNRAS.493.5413K__Dubey_et_al._2009_Instance_1

As we describe in Section 2 the case of TNDWs propagating in a plasma with equal mass fraction of 12C and 16O (CO) and density of ρ0,7 ≈ 1,1 which is typical for Type Ia supernovae, is particularly challenging for full-star simulations. In addition to the problem that the burning length-scale is much smaller than the typical cell size, near detailed balance is obtained for many isotopes while NSE is not reached. We test in Section 2 two available one-dimensional (1D) codes: a modified version of the 1D, Lagrangian version of the vulcan code (hereafter V1D; for details, see Livne 1993) and a modified version of the Eulerian, 1D hydrodynamic flash4.0 code with thermonuclear burning (Fryxell et al. 2000; Dubey et al. 2009), against the ρ0,7 = 1 case. We show that with resolutions that are typical for multidimensional full-star simulations, the V1D and the flash results are not satisfactory (up to $50{{\ \rm per\ cent}}$ error in V1D and up to $20{{\ \rm per\ cent}}$ error in flash). We demonstrate in Section 3 the operation of a new numerical scheme for thermonuclear burning that can be implemented in multidimensional full-star simulations. The new scheme allows an accurate calculation of TNDWs in a consistent way (i.e. without pre-describing the position and/or the conditions behind the TNDW) with all thermonuclear burning taking place in situ (without post-processing) for an arbitrary reaction network with hundreds of isotopes. The new scheme contains two important ingredients: (1) a burning limiter (a variant of Kushnir et al. 2013), which guarantees that the thermodynamic variables and the composition are accurate for the resolved scales, while keeping the numerical thermodynamic trajectory for unresolved scales within some controlled error from the true thermodynamic trajectory, and (2) adaptive statistical equilibrium (ASE) burning, which groups isotopes that are in detailed balance into one effective isotope, where the ratio between the isotope abundances inside the group is given from equilibrium conditions (this is an extension of the earlier attempts of Hix et al. 2007; Parete-Koon & Hix 2008; Parete-Koon, Hix & Thielemann 2008, 2010).

2016MNRAS.462.1415C__Lu_et_al._2014_Instance_1

Over the last 15 yr, our understanding of how galaxies form and evolve has improved substantially. The combination of technological and theoretical progress has brought this field into a new era: advances in observational techniques (e.g. multi-object spectroscopy, efficient near-infrared CCDs) have enabled multiwavelength observations of large samples of galaxies out to the highest redshifts, while the steady rise of computational power and refinement of numerical techniques have fostered new approaches (e.g. semi-analytic models, hydro-dynamic simulations) to model the formation and evolution of galaxies. This progress has led to a general consensus about the main physical ingredients required to describe the evolution of the galaxy population (e.g. Gonzalez-Perez et al. 2014; Lu et al. 2014; Vogelsberger et al. 2014; Henriques et al. 2015; Schaye et al. 2015): collapse and hierarchical growth of dark matter haloes; accretion of baryons on to these haloes; conversion of baryons into stars; feedback of massive stars and active galactic nuclei (AGN) on star formation; supernova- and AGN-driven outflows of metal-enriched gas; infall of both pristine and metal-enriched gas on to galaxies. The large-scale environment can also affect galaxy properties, in particular, by providing quenching mechanisms (e.g. tidal or ram-pressure stripping, strangulation; e.g. Lagos et al. 2014; Rafieferantsoa et al. 2015), and through its influence on the merger rate (e.g. Lackner et al. 2012; Rafieferantsoa et al. 2015) and galactic spins (e.g. Hahn, Teyssier & Carollo 2010; Codis et al. 2012). Although these different ingredients are present in many galaxy formation models, we still lack a detailed quantification of their respective roles in shaping the properties of galaxies. This is because of the complexity inherent in galaxy physics, which combines gravity, radiation hydro-dynamics, magnetic fields and high-energy physics, acting on scales from less than a pc (e.g. for the formation of proto-stellar cores) to over a Mpc (e.g. for environmental effects). For this reason, ‘first-principles’ simulations of galaxy formation remain far beyond the reach of current computational capabilities. Instead, small-scale baryonic physics is generally subsumed into sub-grid prescriptions, which vary from model to model (e.g. Scannapieco et al. 2012; Haas et al. 2013a,b; Vogelsberger et al. 2013; Torrey et al. 2014; Crain et al. 2015). The appropriateness of such prescriptions, and hence, our ability to understand galaxy formation, must be assessed by comparing simulated and observed galaxy properties.

2017ApJ...834L..13W__Chang_et_al._2012_Instance_1

Thanks to their short spectral lags, cosmological distances, and very high-energy photons, GRBs have been viewed as the most promising sources for studying LIV effects (Amelino-Camelia et al. 1998; Ellis et al. 2006; Jacob & Piran 2008). In the past, various limits on LIV have been obtained from the spectral time lags of individual GRBs or a large sample of GRBs (e.g., Amelino-Camelia et al. 1998; Coleman & Glashow 1999; Schaefer 1999; Ellis et al. 2003, 2006; Boggs et al. 2004; Kahniashvili et al. 2006; Jacob & Piran 2008; Abdo et al. 2009a, 2009b; Biesiada & Piórkowska 2009; Xiao & Ma 2009; Shao et al. 2010; Chang et al. 2012, 2016; Nemiroff et al. 2012; Ellis & Mavromatos 2013; Kostelecký & Mewes 2013; Vasileiou et al. 2013, 2015; Pan et al. 2015; Zhang & Ma 2015; Wei et al. 2016). In particular, Abdo et al. (2009a) used the time lag of the highest energy (13.2 GeV) photon from GRB 080916C to constrain the linear LIV energy scale ( E QG , 1 ) and presented a stringent limit of 1.3 × 10 18 GeV, improving the previous limits by at least one order of magnitude. Abdo et al. (2009b) set the current strictest limits on both the linear and quadratic LIV energy scales by analyzing the arrival time delay between a 31 GeV photon and the low-energy (trigger) photons from GRB 090510. The limits set are E QG , 1 > ( 1 − 10 ) E Pl and E QG , 2 > 1.3 × 10 11 GeV. However, these limits were based on the rough time lag of a single GeV-scale photon. It is necessary to consider using the true spectral time lags of bunches of high-energy photons (i.e., the lags of high-quality, high-energy light curves) to constrain the LIV. Furthermore, since the emission mechanism of GRBs is still poorly understood, it is difficult to distinguish an intrinsic time delay at the source from a delay induced by propagation in a vacuum to the observer. That is, the method of the flight-time difference used for testing LIV is hindered by our ignorance concerning the intrinsic time delay in different energy bands (see, e.g., Ellis et al. 2006; Biesiada & Piórkowska 2009).

2022MNRAS.512.1499R__Holmbeck_et_al._2019_Instance_1

The differences in composition are reflected in the final abundances after r-process nucleosynthesis, shown in Fig. 15. The abundances are obtained using a grid of pre-computed trajectories with SkyNet (Lippuner & Roberts 2017), as discussed in detail in Radice et al. (2018b). We normalize the relative abundances by fixing the height of the third r-process peak (A ≃ 190). We also report Solar r-process abundances from Arlandini et al. (1999) in the same figure. However, we emphasize that even if NS mergers were the sole contributor of r-process elements, there is no reason to expect that every merger should produce ejecta with relative abundances close to Solar. Indeed, variability between the yields of different mergers is required to explain observed abundances in metal-poor stars (Holmbeck et al. 2019). Overall, the simulations span a factor ∼2 in the ratio of A ≃ 100 to third r-process peak. However, the difference between the M0 and M1 at the SR resolution, which is the resolution we use for production simulation, are modest compared to the systematic uncertainties from the unknown NS EOS and to the variability due to the binary mass ratio (Radice et al. 2018b; Nedora et al. 2021b). Clearly, strong conclusions cannot be drawn from this limited study alone, but our simulations suggest that the uncertainties in the yields from mergers arising from neutrino radiation treatment are modest. This is also supported by the results of Foucart et al. (2020). They compared M1 and Monte Carlo neutrino transport in the context of NS mergers and reported only a modest ${\sim }10{{\ \rm per\ cent}}$ difference in the Ye of the ejecta between the two schemes. Interestingly, they reported that M1 systematically overestimates the Ye of the ejecta, so we cannot exclude that the M0+Leakage results are actually more accurate than the results obtained with THC_M1. That said, it is important to emphasize that this comparisons has only been made for the dynamical ejecta and not for the secular ejecta, which we discuss in Section 6.5.

2021AandA...656A..79K__Matsumoto_et_al._(1990)_Instance_1

Theoretical single-ionization cross-sections for the Ar2+ ion are compared to the experimental data in Fig. 2. The cross-sections for other two levels, 3P1 and 3P0, are in close agreement with the values from 3P2 and are therefore not presented. The cross-sections of the direct process are evaluated in the potential of the ionized ion. Experimental data obtained by Diserens et al. (1988) and Man et al. (1993) are only presented in Fig. 2. These experimental data showed the lowest contribution from the metastable fraction in the ion beam. Measurements from Muller et al. (1980), Danjo et al. (1984), Mueller et al. (1985), and Matsumoto et al. (1990) demonstrated onsets below the ionization threshold. In addition, the CADW calculations (Loch et al. 2007) are presented for comparison in Fig. 2. The DW cross-sections for the ground level are in good agreement with the experimental results at low energies (Diserens et al. 1988; Man et al. 1993). However, the calculations are below the measurements at the high energies. The theoretical cross-sections are above the experimental values for the two highest levels of the ground configuration from the ionization threshold up to 200–300 eV, which is well beyond the peak region. On the other hand, good agreement with the measurements for these two levels is obtained at the higher energies. It should be noted that the CADW cross-sections (Loch et al. 2007) underestimate the measurements at the low electron energies. Excitations from the 2p subshell are investigated in the CADW calculations of these latter authors, but it is not clear whether the EA channels corresponding to the excitations from the 3s and 3p subshells are included in their study. On the other hand, decays of the excited Ar2+ 2p 53s 23p4 nl (n ≥ 4, l n) configurations lead to states of the Ar4+ ion. The total excitation cross-sections from the 2p subshell amount to ~1 Mb at the peakenergy of 280 eV in our study. Therefore, the excitations from the 2p subshell are not investigated in this work.

2015MNRAS.447.3936M__Grigorieva_et_al._2007_Instance_1

We now analyse whether release of this entrapped CO is possible, and quantify it using simple assumptions. In the Fomalhaut ring, the rate at which large planetesimals in the belt are being ground down, which is the same as the rate at which small dust grains are being replenished, has been estimated as 6.0 × 1017 kg yr−1 (Wyatt & Dent 2002). Assuming the planetesimal composition to be similar to that observed in Solar system comets (ice/rock ratio of about 1, CO/H2O ice ratios between 0.4 and 30 per cent), we can use it to estimate the rate of CO release, which corresponds to between 1.9 × 1015 and 8.0 × 1016 kg yr−1. The mechanisms that can be responsible for this release are collisions and photodesorption. Collisions can contribute through dust vaporization (Czechowski & Mann 2007), planetesimal breakup (Zuckerman & Song 2012) and giant impacts (Jackson et al. 2014). Photodesorption, on the other hand, will affect the H2O ice on the surface of solids, in turn exposing CO and allowing it to escape on very short time-scales. The rate at which water vapour will be released is da/dt ∼ 1.5 × 10−3 μm yr−1 (scaled to the distance of the ring, from the result of Grigorieva et al. 2007), where a is the vertical thickness of the layer. The total water mass released in this manner will then be (19) \begin{equation} \frac{\mathrm{d}M_{\rm H_2O}}{\mathrm{d}t} = 4\sigma _{\rm tot}\rho _{\rm gr} \frac{\mathrm{d}a}{\mathrm{d}t}, \end{equation} where ρgr is the grain density, which we take as that of water ice (∼1 × 10−15 kg μm−3) and σtot is the total cross-section of icy grains in the Fomalhaut ring (in μm2). Under the assumption that all the grains are fully icy, we can use the total cross-sectional area of the Fomalhaut ring (33.7 au2; Wyatt & Dent 2002) to obtain an H2O production rate of 4.6 × 1018 kg yr−1. This is higher than the rate at which mass is being passed down the collisional cascade (again, 6.0 × 1017 kg yr−1), pointing towards a more realistic scenario where grains are not fully icy, but made up of a mixture of ice and rock. We therefore conclude that photodesorption of H2O might contribute significantly to the release of trapped CO gas from planetesimals in the ring, though the extent of this contribution depends on how much of the cross-sectional area of the Fomalhaut disc is icy. In any case, the exact mechanism for CO gas production is unimportant as long as there is one that can feasibly explain its release.

2021MNRAS.503...13Z__Asplund_et_al._2000_Instance_1

Although the method developed here is not identical to the means by which SONG determines radial velocity from the observed spectra, it simulates the SONG observations sufficiently well. First, the set of fictitious Fe i lines carefully chosen in this work is able to represent the properties of most Fe i lines seen between 4400 and 6900 Å, which constitute a large part of all lines in this wavelength interval. Secondly, the procedure to extract radial velocity from theoretical spectral lines is similar to how radial velocities are typically obtained from observed spectra. Thirdly, the evaluation of our final radial velocity amplitude includes the information of many spectral lines that span the whole range in observation. The major uncertainty in our method is associated with the linear relationship between radial velocity amplitude and equivalent width. Due to the complicated physical processes involved in spectral line formation in a 3D atmosphere (e.g. Asplund et al. 2000), it is difficult to quantify higher order effects beyond the linear relation between $\mathfrak {v}$ and Wλ; that is, the systematic uncertainty of the linear fitting. Nevertheless, it is still illuminating to provide the statistical uncertainty. The statistical uncertainty is quantified using the bootstrap method. The data set considered here is the radial velocity amplitude and equivalent width of 49 fictitious Fe i lines. We conduct 10 000 bootstrap samplings, that is, generating 10 000 data sets each containing 49 randomly sampled $\mathfrak {v}$ and Wλ pairs. A linear regression between equivalent width and radial velocity is then performed for each re-sampled data set. For each fitting, we compute the equivalent width weighted mean radial velocity amplitude for all selected Fe i lines. The bootstrap method therefore results in 10 000 weighted mean radial velocity amplitudes, their mean and variance is the desired final radial velocity amplitude and its statistical uncertainty, which is 72.2 ± 0.5 m s−1 for the 3D solar model and 93.2 ± 0.3 m s−1 for the ϵ Tau model.

2022MNRAS.510.6085L__Tafalla_&_Hacar_2015_Instance_1

Filamentary structures have been found at almost all size scales in the Galaxy. Massive, long filamentary dark clouds are commonly found inside giant molecular clouds (GMCs; e.g. Bergin & Tafalla 2007; André et al. 2014, and references therein), such as the dark clouds L1495 in the Taurus cloud complex (e.g. Chapman et al. 2011) and the Serpens South cloud in the Serpens region (e.g. Dhabal et al. 2018). Filamentary clouds of 4–6 pc length are common, and possibly longer than 10 pc. Some of these clouds are dark at infrared wavelengths. The line–width size relation observed for molecular gas indicates that the thermal Mach number would exceed 10 at such size scales. The long-term survival of these filamentary structures requires a reinforcing mechanism. As shown in the ideal magnetohydrodynamical (MHD) simulations of Li & Klein (2019), a moderately strong, large-scale magnetic field (Alfv$\acute{\rm e}$n Mach number, ${{\cal M}_{\rm A}}\sim 1$) can provide such a mechanism. In the weak-field model with ${{\cal M}_{\rm A}}=10$, the appearance of molecular clouds is clumpy, rather than the long and slender filamentary clouds seen in moderately strong field models. High-resolution images of massive molecular clouds from the Herschel space telescope reveal complex filamentary substructures (e.g. André et al. 2014). The characteristic inner width of molecular filaments found with Herschel is about ∼0.1 pc (Arzoumanian 2011; Arzoumanian et al. 2019). Dense cores, where stars form, are located along or at the intersections of some of these fine substructures (e.g. Könyves et al. 2015; Tafalla & Hacar 2015). From these observations of molecular cloud structures at different size scales, one can visualize an evolutionary sequence of star formation starting from highly supersonic, magnetized GMCs, continuing on to filamentary dark clouds that form within them, and then on to finer filamentary substructures. Fragmentation of these filamentary structures and substructures leads to the clumps and dense cores that form protostellar clusters and protostars. Knowing the physical conditions inside filamentary clouds would provide crucial information on the formation of filamentary substructures and dense cores, and on the origin of the initial mass function (IMF) and the star formation rate. Particularly important is the characterization of the physical properties of transcritical filamentary structures whose mass per unit length is within a factor of ∼2 of the critical line mass ${M_{\rm crit,\, th,\, \ell }}=2\, c_{\rm s}^2/G$ of nearly isothermal cylindrical filaments (e.g. Ostriker 1964; Inutsuka & Miyama 1997), where cs is the isothermal sound speed. Indeed, Herschel observations suggest that transcritical filamentary structures dominate the mass function of star-forming filaments and that their fragmentation may set the peak of the prestellar core mass function and perhaps ultimately the peak of the IMF (André et al. 2019). In this paper, we report the results of polarimetric observations of the pristine section B211 of one such transcritical filament, the Taurus B211/B213 filament, using the High-resolution Airborne Wideband Campera plus (HAWC+) onboard Stratospheric Observatory For Infrared Astronomy (SOFIA). We determine the magnetic field structure inside a filamentary cloud with filamentary substructures.

2022MNRAS.517.1313M__Krumholz_&_McKee_2005_Instance_1

Star formation is an inefficient process, as evidenced by observed gas depletion times,1 which are two orders of magnitude above the dynamical time, both in galaxies (e.g. Leroy et al. 2017; Utomo et al. 2018), and in individual giant molecular clouds (GMCs) (e.g. Krumholz & Tan 2007; Evans, Heiderman & Vutisalchavakul 2014; Heyer et al. 2016; Pokhrel et al. 2020; Hu et al. 2022). Theoretical models explain this inefficiency through a combination of mechanisms that provide support against gravitational collapse, including turbulence, magnetic fields, stellar feedback, and dynamical stabilization (Krumholz & McKee 2005; Ostriker, McKee & Leroy 2010; Federrath & Klessen 2012; Krumholz, Klein & McKee 2012b; Federrath 2013b; Padoan et al. 2014; Federrath 2015; Burkhart 2018; Meidt et al. 2018; Krumholz & Federrath 2019; Evans, Kim & Ostriker 2022). Recent progress in both theory and observations have highlighted the pivotal role that feedback, especially due to massive (main-sequence) stars, plays in star/star-cluster formation (Krumholz et al. 2014; Krumholz, McKee & Bland-Hawthorn 2019), and the lifecycle of GMCs (see Chevance et al. 2020, 2022a for reviews). This massive-star feedback has been suggested to be largely responsible for limiting the integrated star formation efficiency (ϵ*) to low values in typical environments, where ϵ* is given by (1)$$\begin{eqnarray} \epsilon _* = \frac{M_{*}}{M_{\mathrm{gas}}}, \end{eqnarray}$$which quantifies the net efficiency of star formation over the lifetime of a GMC, i.e. the ratio of the final stellar mass M* and the available gas mass in the parent molecular cloud Mgas. Feedback achieves this by (i) disrupting GMCs in order ∼ unity dynamical time-scales, through the momentum and energy carried by feedback processes (e.g. Grudić et al. 2018), and (ii) driving turbulent motions that could further provide support against collapse (e.g. Mac Low & Klessen 2004; Krumholz, Matzner & McKee 2006; Elmegreen 2009; Gritschneder et al. 2009; Federrath et al. 2010; Wibking, Thompson & Krumholz 2018; Gallegos-Garcia et al. 2020; Menon, Federrath & Kuiper 2020; Menon et al. 2021).

2022MNRAS.515.5495M__Gallazzi_et_al._2008_Instance_1

The stellar metallicity in the Universe evolves with redshift (Mannucci et al. 2010; Sommariva et al. 2012; Krumholz & Dekel 2012; Dayal, Ferrara & Dunlop 2013; Madau & Dickinson 2014). The metallicity at a high redshift (z > 2) is much smaller in comparison to the low redshift Universe z 2. The first-generation stars contaminate the interstellar medium and cause a chemical evolution of the Universe. We can treat the metallicity evolution with redshift by a relation (2)$$\begin{eqnarray*} \log _{10}(Z(z))= \gamma z +\zeta , \end{eqnarray*}$$where γ captures the redshift dependence and ζ captures the metallicity value at z = 0 (Mannucci et al. 2010; Madau & Dickinson 2014). This relation captures the metallicity of the parent star or the gas cloud from which a star has formed. It is written to express only a mean evolution of the metallicity. Along with the mean metallicity evolution of the Universe, there is going to be a scatter in the metallicity depending on the galaxy properties. Such a source of uncertainty brings additional stochasticity to the metallicity relation. Currently, a limited number of observations (Gallazzi et al. 2008; Mannucci et al. 2010; Krumholz & Dekel 2012) are available to explore the environment dependence of the metallicity, and most of our current understandings are based on simulations(Genel 2016; Torrey et al. 2019). These studies show that the overall median metallicity dependence of the galaxies at different redshifts can be explained by power form (Pei, Fall & Hauser 1999; Young & Fryer 2007; Torrey et al. 2019). Several studies of GW merger rates and mass distribution are performed (Belczynski et al. 2002; Dominik et al. 2012, 2015; Mapelli et al. 2017; Giacobbo, Mapelli & Spera 2018; Toffano et al. 2019; van Son et al. 2022) which are motivated by these studies and show that the black hole mass distribution can exhibit a redshift dependence. The existence of any stochasticity in the galaxy metallicity distribution will also influence the mass distribution but is currently not well known. However, as the relation given in equation (1) is in terms of the logarithm of metallicity, so the impact of fluctuation around the median value depending on the individual galaxy properties is going to be a small (logarithmic) change. As we are unable to measure the host of the BBH due to a large sky localization error of the BBH, we cannot directly associate the properties of galaxies with BBH source properties. So, we can only infer an ensemble average mass distribution from the GW data and the additional stochasticity (which will depend on the host properties) will appear as an additional uncertainty in the measurement of MPISN. As a result, we consider a median distribution of galaxy metallicity and the dependence of MPISN on it.

2019AandA...625A.114J__Tacconi_et_al._2018_Instance_1

Although most galaxies have an implied SFR that scatters within a factor two around the MS, some do show a significantly higher SFR. Those objects also exhibit a higher gas content, shorter gas depletion times (e.g., Genzel et al. 2015; Schinnerer et al. 2016; Tacconi et al. 2013, 2018), and higher dust temperatures (e.g., Magnelli et al. 2014). Likewise, the stellar-light radial distribution is different in these two galaxy populations; while MS galaxies are closely approximated by exponential disks (e.g., Bremer et al. 2018), those above (and below) it exhibit a higher central mass concentration (e.g., Wuyts et al. 2011). Based on this dichotomy and the parametrization of the MS over cosmic time, a scenario has been proposed to explain the evolutionary path of galaxies along the MS. Since the normalization of the MS, the gas fraction of galaxies, and cosmic molecular gas density decrease from z ∼ 2.5 to 0 at a similar pace (e.g., Speagle et al. 2014; Decarli et al. 2016; Tacconi et al. 2018), it is thought that MS galaxies evolved through a steady mode of star formation, possibly regulated by the accretion of cool gas from the intergalactic medium (e.g., Dekel et al. 2009; Kereš et al. 2009; Davé et al. 2010; Hodge et al. 2012; Romano-Díaz et al. 2014, 2017; Feng et al. 2015; Anglés-Alcázar et al. 2017). From theoretical predictions, the scatter of the MS could thus be explained as the result of a fluctuating gas inflow rate that is different in each galaxy (e.g., Tacchella et al. 2016; Mitra et al. 2017). In this context, a galaxy enhances its SFR and moves towards the upper envelope of the MS due to gas compaction. As the gas is depleted, the SFR decreases and the galaxy falls below the MS. As long as a SFG is replenished with fresh gas within a timescale shorter than its depletion time, it will be confined within the MS (Tacchella et al. 2016). On the other hand, the enhanced star formation efficiency of galaxies above the MS has been linked to mergers (e.g., Walter et al. 2009; Narayanan et al. 2010; Hayward et al. 2011; Alaghband-Zadeh et al. 2012; Riechers et al. 2013, 2014) and instability episodes in gas-rich disks (particularly at high redshift; e.g., Davé et al. 2010; Hodge et al. 2012; Wang et al. 2019).

2015AandA...576A...5C__Christen_&_Müller_(2003)_Instance_1

Using the CASSIS2 software, we detected 8 lines of glycolaldehyde, 31 lines of the aGg′ conformer of ethylene glycol, and 26 lines of methyl formate (see Table 1). The glycolaldehyde and methyl formate transitions are taken from the JPL spectroscopic database (Pickett et al. 1998), while the ethylene glycol transitions are from the CDMS catalog (Müller et al. 2001, 2005). The predictions are based on experimental data from Butler et al. (2001), Widicus Weaver et al. (2005) and Carroll et al. (2010) for glycolaldehyde, Christen et al. (1995) and Christen & Müller (2003) for ethylene glycol, and Ilyushin et al. (2009) for methyl formate. The frequencies of five of the detected glycolaldehyde lines were directly measured in the laboratory (Butler et al. 2001). Some of the lines result from a blending of several transitions of the same species. The lines that are strongly blended with other species are not listed in Table 1. All three species are emitted very compactly at the position of the continuum peak (\hbox{$\alpha_{2000}=03^{\rm h}28^{\rm m}55\fs57$}α2000=03h28m55.s57, \hbox{$\delta_{2000}=31\degr14\arcmin37\farcs1$}δ2000 = 31°14′37 .̋ 1). The angular sizes obtained with a circular Gaussian fit in the (u, ν) plane vary from a point source to a maximum of 1″ depending on the transition. The line fluxes listed in Table 1 were measured at the continuum peak position with the CASSIS software using a Gaussian fitting method (Levenberg-Marquardt algorithm). The lines that are contaminated in the wings by other transitions are consequently fitted with a sum of Gaussians. We carefully checked that the derived full widths at half maximum (FWHM) are consistent with the other line measurements. The average FWHM is about 4.5 km s-1 at 317 GHz, and 5.0 km s-1 at 225 and 242 GHz. The widths of the methyl formate lines at 87 GHz are quite broad (~12 km s-1). It is consequently difficult to completely exclude an additional flux contribution from other species. The variation of FWHM with the frequency can be explained by the spectral resolution of the observations that decreases toward the lower frequencies.

2017ApJ...837..109L__parsec,_Cisternas_et_al._2013_Instance_1

It has been generally believed (see Kormendy & Ho 2013; Kormendy 2016, for recent reviews) that, unlike massive galaxies at high redshifts (e.g., ) whose evolution is driven by a major merger, low-redshift galaxies largely evolve through secular evolution (i.e., in a slow and gentle manner) driven by internal processes within galactic disks and/or by environmental effects such as harassment or nurturing (see Kormendy & Kennicutt 2004 for details; see also Cowie et al. 1996; Conselice et al. 2014 for the cosmic evolution). It has also been generally believed accordingly that most activity (namely active galactic nuclei—AGNs) of supermassive black holes (BHs) at the centers of galaxies at low redshifts (e.g., , Cisternas et al. 2011; and even up to , Kocevski et al. 2012) appear to be fueled by the random accretion of gas via internal, secular processes working close to the BH (say, within a few hundred parsec, Cisternas et al. 2013; also see Hopkins & Hernquist 2006). In these cases, there is no connection between AGN activity and major mergers of their host galaxies. This non-connection appears to be particularly true for low-z AGNs hosting intermediate-mass black holes (IMBHs):12 12 Following Greene & Ho (2007) and Dong et al. (2012), hereinafter we refer to BHs with at the centers of galaxies as “low-mass” or “intermediate-mass” BHs; accordingly, for the ease of narration wherever it is not ambiguous, hereinafter we refer to AGNs hosting low-mass BHs as low-mass AGNs or IMBH AGNs. Normally, we prefer “intermediate-mass BHs” to “low-mass BHs” because of the possible confusion of the latter with the stellar-mass BHs in low-mass X-ray binaries (LMXBs). according to the analysis of their images by the Hubble Space Telescope (HST), the majority of low-mass AGNs live in late-type disk galaxies without a classical bulge (Greene et al. 2008; Jiang et al. 2011). Indeed, the accretion rate for an IMBH is so tiny (0.05 yr−1 even if at the maximum Eddington accretion) that a steady supply of fuel, in the form of stellar mass loss from evolved stars or Bondi accretion of hot gas in the innermost regions, is available readily much more than required (Ho 2008). “In fact, the paradox for local BHs is not whether there is enough fuel to light them up. Rather, the puzzle is how to keep them so dim despite the ready abundance of in situ gas.” (Kormendy & Ho 2013; see also Ho 2008). That is, the real problem seems to be this (see Ho 2009): there must be some mechanism (yet to know) to hinder the innermost fueling process.13 13 According to W.-M. Gu (2016, private communication), AGN outflows, which can be launched even at very low accretion rates (e.g., Wang et al. 2013; Gu 2015), provide such a mechanism.

2021AandA...656A.148R__in_2012_Instance_1

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

2021ApJ...909...65K__Liu_et_al._2014_Instance_1

Various groups around the world have proposed different models to explain the formation of these two peculiar classes of SNe Ia. Sub-Chandrasekhar limiting-mass WDs were believed to be formed by merging two sub-Chandrasekhar mass WDs (double-degenerate scenario), leading to another sub-Chandrasekhar mass WD, exploding due to accretion of a helium layer (Hillebrandt & Niemeyer 2000; Pakmor et al. 2010). On the other hand, the super-Chandrasekhar WDs were often explained by incorporating different physics, such as a double-degenerate scenario (Hicken et al. 2007), presence of magnetic fields (Das & Mukhopadhyay 2013, 2014), presence of a differential rotation (Hachisu et al. 2012), presence of charge in the WDs (Liu et al. 2014), ungravity effect (Bertolami & Mariji 2016), lepton number violation in magnetized WD (Belyaev et al. 2015), generalized Heisenberg uncertainty principle (Ong 2018), and many more. However, none of these theories can self-consistently explain both of the peculiar classes of WDs. Moreover, each of these has some caveats or incompleteness, mostly based on the stability (Komatsu et al. 1989; Braithwaite 2009). Furthermore, numerical simulations showed that a merger of two massive WDs could never lead to a mass as high as 2.8M⊙ owing to the off-center ignition and formation of a neutron star rather than an (overluminous) SN Ia (Saio & Nomoto 2004; Martin et al. 2006). Hence, all the conventional pictures failed to explain the inferred masses of both the sub- and super-Chandrasekhar progenitor WDs and also both classes of progenitor WDs simultaneously by invoking the same physics. Moreover, each of the theories can explain only one regime of SN Ia, but it seems more likely that the nature would prefer only one scenario/physics to exhibit the same class of SNe. Whether it be an under- or overluminous SN Ia, other physics such as the presence of Si, etc., remains the same. Therefore, we seem to require just one theory to explain all the SNe Ia.

2015MNRAS.451.1528P__Brun_et_al._2014_Instance_1

Currently, there is an extensive data base of observations of magnetic activity on the main-sequence stars (see e.g. reviews by Donati & Landstreet 2009; Reiners 2012). Cool stars with outer convective envelope are of particular interests because they are Sun-like. It is believed that the magnetic activity on the solar-like stars results from large-scale dynamo processes driven by turbulent convection and rotation (Brandenburg & Subramanian 2005). Observations (e.g. Böhm-Vitense 2007; Donati & Landstreet 2009; Katsova et al. 2010; Saar 2011; Katsova, Livshits & Mishenina 2013; Marsden et al. 2014; Vidotto et al. 2014), as well as the 2D mean-field models of the angular momentum balance (Ruediger 1989; Kitchatinov & Rüdiger 1999; Kitchatinov 2013) and the 3D numerical simulations (Miesch & Toomre 2009; Hotta & Yokoyama 2011; Guerrero et al. 2013b; Brun et al. 2014; Käpylä, Käpylä & Brandenburg 2014) show that parameters of the differential rotation and convection, e.g. the typical size and turnover time of convective flows, depend on the general stellar parameters, such as mass, age, the spectral class and the rotation rate. The mass of a star and its Rossby number, which is the ratio of the period of rotation and a typical turnover time of convection, are likely the most important parameters governing the stellar dynamo (Donati & Landstreet 2009; Morin et al. 2013). The diagram 3 in the paper by Donati & Landstreet (2009) shows an increase of the magnetic activity with decrease of the Rossby number and the mass of a star. These parameters determine the topology of the large-scale magnetic field, as well. It is found that the axisymmetric solar-type dynamo can operate in stars with mass about 1 M⊙, and with periods of rotation longer than 10 d. Observations, also show pieces of evidence that solar analogues with period of rotation smaller than 10 d, may have the substantial non-axisymmetric components of the large-scale magnetic field (Donati & Landstreet 2009; Folsom et al. 2014).

2015AandA...579A..51B__Egan_et_al._1998_Instance_1

Even though the understanding of high-mass star formation has made tremendous progress over the past decade (Beuther et al. 2007; Zinnecker & Yorke 2007; Klessen 2011; Tan et al. 2014), the initial conditions are still poorly constrained. It is known, that stars predominantly form in clusters (Lada & Lada 2003), which is especially true for high-mass stars (e.g., de Wit et al. 2005; Gvaramadze et al. 2012). On observational grounds, the first evolutionary stage of such clusters spawning future high-mass stars might in general be termed pre-protocluster cores (Evans et al. 2002). Their appearance and morphology can be different depending on the environment. Objects of this sort have been found in several (sub-)millimeter surveys (e.g., Klein et al. 2005; Beuther & Sridharan 2007). Also the ISO satellite mission has resulted in a list of such objects revealed by far-infrared observations at 170 μm within the ISO Serendipity Survey (ISOSS, Bogun et al. 1996). For these clumps, cold dust and gas temperatures have been established in follow-up investigations (Krause et al. 2003, 2004). The most prominent variety of young massive clumps are the infrared dark clouds (IRDCs). They were discovered as dark silhouettes against the galactic background at 8 and 15 μm with the Midcourse Space Experiment (MSX, Egan et al. 1998) and ISO (Perault et al. 1996). ISO, MSX, the Spitzer Space telescope, and further (sub-)millimeter observations have helped for studying these objects in detail (e.g., Simon et al. 2006; Hennemann et al. 2008; Vasyunina et al. 2009; Ragan et al. 2009; Peretto & Fuller 2009). Because IRDCs can only be seen in absorption against a strong infrared background, their location is mainly within the disk toward the inner quadrants of our Milky Way, whereas ISOSS sources are more widely distributed. In fact, the Milky Way midplane had to be avoided for ISOSS because of saturation. IRDCs can have masses up to several thousand solar masses, and the more massive ones are explicitly thought to be progenitors of star clusters (e.g., Wyrowski 2008; Rathborne et al. 2010; Henning et al. 2010; Ragan et al. 2012a). On average the ISOSS sources have masses less than 500 M⊙ (Hennemann et al. 2008). While their masses often are somewhat lower than for large high-contrast IRDCs, the general characteristics such as low temperature and low turbulent linewidth are similar to IRDCs. Therefore, ISOSS sources are also considered to be early evolutionary stages of intermediate- to high-mass star formation in more isolated regions. Consequently, the better characterization of such clumps (ISOSS and IRDCs) is an important step toward understanding the initial conditions of high-mass star formation.

2019MNRAS.488.5029H__Malhotra_et_al._2001_Instance_2

For the first time, we detected [C ii] 158-μm emission from a GRB host galaxy at z > 2. This is the second detection of [C ii] 158-μm emission among known GRB host galaxies, following GRB 980425 (Michałowski et al. 2016). The [C ii] 158-μm fine structure line is the dominant cooling line of the cool interstellar medium, arising from photodissociation regions (PDR) on molecular cloud surfaces. It is one of the brightest emission lines from star-forming galaxies from FIR to metre wavelengths, almost unaffected by dust extinction. [C ii] 158-μm luminosity, L[C II], has been discussed as an indicator of SFR (e.g. Stacey et al. 2010). If L[C II] scales linearly with SFR, the ratio to FIR luminosity, L[C II]/LFIR, is expected to be constant, since LFIR is a linear function of SFR (e.g. Kennicutt 1998a). However, LC II/LFIR is not constant, but declines with increasing LFIR, known as the ‘[C ii] deficit’ (e.g. Luhman et al. 1998, 2003; Malhotra et al. 2001; Sargsyan et al. 2012; Díaz-Santos et al. 2013, 2017; Spilker et al. 2016). The [C ii] deficit persists when including high-z galaxies (e.g. Stacey et al. 2010; Wang et al. 2013; Rawle et al. 2014). In Fig. 5, we compare the [C ii] deficit in the GRB 080207 host and other star-forming galaxies. Two GRB hosts are shown by stars: GRB 080207 (orange star) and 980425 (blue star). The comparison sample is compiled from the literature up to z ∼ 3 (Malhotra et al. 2001; Cormier et al. 2010, 2014; Ivison et al. 2010; Stacey et al. 2010; Sargsyan et al. 2012; Farrah et al. 2013; Magdis et al. 2014; Brisbin et al. 2015; Gullberg et al. 2015; Schaerer et al. 2015). Active galactic nuclei are separated from star-forming galaxies based on either (i) the explicit description in the literature or (ii) EWPAH 6.2μm 0.1 (Sargsyan et al. 2012). As reported by previous studies (e.g. Maiolino et al. 2009; Stacey et al. 2010), high-z galaxies are located at a different place from local galaxies in the L[C II]/LFIR–LFIR plane.

2019AandA...630A.131M__Molina_et_al._2009_Instance_1

X-rays emerging from active galactic nuclei (AGNs) are the result of an inverse-Compton process occurring in the proximity of the central black hole (BH), where optical-UV photons arising from the accretion disc are inverse-Compton scattered by hot electrons in an optically thin, compact corona (e.g. Haardt & Maraschi 1991, 1993; Haardt et al. 1994, for details on the two-phase model). Such a Comptonisation mechanism accounts for the power-law-like shape of the X-ray primary continuum emission and the high-energy roll-over observed in various nearby AGNs (e.g. Nicastro et al. 2000; Perola et al. 2002; De Rosa et al. 2002; Molina et al. 2009, 2013; Malizia et al. 2014; Ricci et al. 2018). Broadband X-ray spectral investigations are of primary importance in studying AGN Comptonisation properties. Indeed, as extensively discussed in the literature (e.g. Ghisellini 2013) both the photon index (Γ) and high-energy cut-off (Ec) of the X-ray primary emission depend on the intrinsic properties of the Comptonising medium, namely its temperature, optical depth, and geometry. Therefore, the interplay between coronal parameters and the AGN X-ray spectral shape has been the object of several investigations, especially with observatories capable of detecting hard X-rays. Dadina (2007), using BeppoSAX data, collected and studied the photon index and Ec of a sample of AGNs (see also Perola et al. 2002, for previous results), while similar works were performed on INTEGRAL data (e.g. Bassani et al. 2006; Molina et al. 2009; Malizia et al. 2014), and, in the context of the BAT AGN Spectroscopic Survey, by Ricci et al. (2018). Subsequently, NuSTAR (Harrison et al. 2013), thanks to its unprecedented effective area above 10 keV, greatly helped in studying the exponential cut-offs of the nuclear continuum in several AGNs (see e.g. Fabian et al. 2015, 2017; Tortosa et al. 2018a). These space missions gave rise to a substantial corpus of high-energy cut-off and photon index measurements.

2021ApJ...906..105C__Huang_et_al._2019_Instance_1

Even though Ω is only a function of Ψ, the physical connection between the two at the foot-point is not very obvious.9 9 They may be constrained by proper boundary conditions (e.g., Contopoulos et al. 2013). Likely most researchers, here we assume that they generally follow the ansatz 13 In the region approaching the polar axis, one expects that the magnetic flux vanishes and thus . Therefore, in the region near the polar axis, mathematically λ ≥ 0 is required to guarantee a finite value of Ω (notice that λ > 0 is likely unphysical). Magnetic field lines just around the polar axis would connect to the central CO, which is expected to rotate with a roughly constant angular velocity10 10 In the case of threading a BH, magnetic field lines at different polar angles may not rotate with exactly the same frequency; see discussion in Section 8. (see details below), implying λ = 0 for the case of magnetic field lines threading the CO. In the region where magnetic field lines are threading the AD, one usually expects λ 0. The choice of Φ, which determines the toroidal magnetic field, is important (e.g., Camenzind 1987; Sulkanen & Lovelace 1990). Physically, it is the rotation that develops a toroidal magnetic field and a poloidal electric field in the lab frame (or the inertial frame), which seems to imply that Φ would not be chosen arbitrarily and would be self-consistently determined by the MHD equations, given the Ψ and Ω specified (e.g., Beskin & Tchekhovskoy 2005; Contopoulos et al. 2013; Huang et al. 2019, 2020). To solve the rotation term, Equation (11), one can see that in the case of 14 the function Ψ can be variable-separated, 15 where the subscript “r” denotes “rotation.” The negative sign in Equation (14) exists to guarantee that there is always a swept-back magnetic field line with respect to the direction of rotation. This relation implies that the strength of the toroidal magnetic field would be proportional to the angular velocity and the enclosed magnetic flux, which can be reasonably understood because it is the rotation of the poloidal magnetic field (related to the magnetic flux) that produces the toroidal magnetic field. In terms of Equation (15), Equation (11) can be expressed as 16 where , , , and . The left-hand side of the above equation is only a function of r (the r component), and the right-hand side is only a function of θ (the θ component). Both equal the same constant. Let us set this constant as , a choice making the solution of the r component equation concise: 17 We introduce a new variable, 18 which makes the θ-component equation become 19 where and . Let us first consider its asymptotic properties. In the case of θ ≪ 1 (keeping in mind when ), the leading-order terms give 20 It is clear that this equation has a solution of the form 21 Therefore, a magnetic field line forms a “general parabolic” configuration11 11 In the case of ν = 0, Ψ is only a function of θ, which presents a monopole solution. The case of ν = β leads to Ψ ∝ R, which gives a cylindrical solution. at θ ≪ 1, that is, Ψ ∝ rνθβ. Now, let us consider what value β might take. In order to do this, we have to consider the higher-order terms of Equation (19), which may be comparable to the nonrotation term. Therefore, we have to consider the original Equation (10). Let us substitute a general form of (with coefficients a1, a2, a3... to be determined) into the original Equation (10). One gets the first two leading-order terms (note that a1 = 0): 22 It can be seen that, for any values of β, λ, and ν, one always has an a2 to make the second term vanish, whereas the first term yields β ≈ 2 (β = 0 corresponds to the nonrotation case). We note that this choice cannot guarantee that the higher-order terms vanish, so this solution is only an approximation. In the case of β 2ν (i.e., ν ≳ 1), the first term dominates over the second term in Equation (22), whereas in the case of β > 2ν (i.e., ν ≲ 1), the second term dominates over the first one. We therefore expect that the approximation β ≈ 2 would be more efficient in the former case (i.e., ν ≳ 1). In another aspect, from Equation (2), one has , which implies that the choice of β = 2 can avoid singularity or vanishing magnetic fields on the magnetic polar axis (either Bθ or Bϕ vanishes). This choice is also supported by some numerical simulations, which showed that this choice corresponds to a minimum torque (i.e., the least amount of toroidal magnetic fields) and is the one picked by a “real” system (see, e.g., Michel 1969; Contopoulos 1995; Narayan et al. 2007; Tchekhovskoy et al. 2008). Although the coefficient β ≈ 2 is derived asymptotically (θ ≪ 1), which must hold throughout the jet region because Φ, Ω, and Ψ are each conserved along magnetic field lines. In Appendix A, we come back to this question and present another proof of the relation Φ ≈ −2ΩΨ based on a more physical consideration, showing that this relation is only valid in the limit of a highly magnetized jet flow (e.g., Lyubarsky 2009).

2018AandA...611A..74R__Grady_et_al._2013_Instance_1

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

2022AandA...661A..10B__Ghirardini_et_al._2021a_Instance_4

It is also possible that these clusters have a smaller extent and can just be missed by our extent selection as our detection algorithm sets the extent to zero if it is smaller than 6 (Brunner et al. 2022). Following the method presented in Ghirardini et al. (2021a), we estimated several dynamical properties of the clusters in the point source sample and compared them with the extent-selected sample presented in Ghirardini et al. (2021a). In Fig. 5 we compare the distributions of the core radii (Rcore) constrained by the V06 model and the concentration parameter (cSB) between these two samples. The concentration parameter is defined as the ratio of the surface brightness within 0.1 R500 to the surface brightness within R500 (Ghirardini et al. 2021a; Santos et al. 2008; Maughan et al. 2012). Intuitively, the expectation is that the smaller the core radius, the more compact the cluster. The left panel of Fig. 5 clearly shows that the clusters in the point source sample have relatively smaller core radii, hence the emission is more concentrated in a smaller area. Consistently, the concentration of the point source sample shows a clear excess in higher values than the extent-selected sample, indicating that a significantly larger fraction of cool-core clusters and clusters host a central AGN. We performed the same experiment by applying cuts in flux 1.5 × 10−14 ergs s−1 cm−2 and in detection likelihood to test whether the clusters are missed by the extent selection because they are fainter and/or more compact than the extent-selected clusters. The distribution of number density, core radius, and concentration parameter remains the same, indicating that the population of clusters in the point source catalog is more compact than the extent-selected sample. The extent-selected sample does not show a clear bias toward cool-core clusters or clusters with a central AGN, but contains the fraction of cool-cores is similar to that of SZ surveys (Ghirardini et al. 2021a). In this sample, we observe the opposite trend.

2017ApJ...849..109P__Lee_et_al._2014_Instance_1

Lastly, we model the evolution of the ejecta discussed in Section 2.2 into circumstellar profiles discussed in Section 2.3. We use our cosmic-ray hydrodynamics code, hereafter called ChN to model the evolution of the ejecta to an age of t SNR = 400 yr. ChN is a Lagrangian hydrodynamics code that includes a prescription for diffusive shock acceleration (DSA; Ellison et al. 2007; Lee et al. 2012). We have modified the code to include the effects of DSA on non-equilibrium ionization (Patnaude et al. 2009, 2010) and have coupled the code to SN ejecta models (Lee et al. 2014; Patnaude et al. 2015). We have also included radiative losses via forbidden line cooling (Lee et al. 2015). This effect will be important in the evolution of the SN shock with a nearby CSM shell, or if we choose to model the radiative shock that could form in the ejecta during early SN evolution (Nymark et al. 2006). However, we begin our simulations at an age of 5 yr, and over the lifetime of the simulation the shocks remain adiabatic, so we do not consider the radiative shock model presented in our previous work here. Since ChN couples nonlinear particle acceleration to the SNR shock dynamics, we are able to reproduce the broadband thermal and nonthermal emission (Ellison et al. 2010, 2012; Castro et al. 2012; Slane et al. 2014; Lee et al. 2013). The diffusive shock acceleration process is an integral part of ChN, and some injection of thermal particles into the acceleration process is always assumed. Here we set the injection parameter to the test particle limit, though we note that the interaction of a strong shock with a massive CSM shell or cloud will lead to enhanced particle acceleration (e.g., Ellison et al. 2012; Lee et al. 2014), and the differing CSM configurations, combined with the differing ejecta profiles and compositions, may result in differences in the broadband nonthermal emission. The study of nonthermal emission in evolving SNe is sufficiently broad that we defer its study to future papers.

2022MNRAS.509.5155R__Richard_et_al._2009_Instance_1

In addition to being useful laboratories for studying the evolution of galaxies in dense environments, galaxy clusters can be effective gravitational lenses (for a review, see Kneib & Natarajan 2011). Gravitational lensing is the deflection of light by intervening mass, that can produce highly magnified and distorted images of background galaxies. The large mass and solid angle covered by highly concentrated galaxy clusters make them ideal gravitational lenses, which can be used as ‘cosmic telescopes’ to observe very distant galaxies (e.g. Richard et al. 2009). The amplification of sources through gravitational lensing has been extremely effective in observing faint, distant sources across the electromagnetic spectrum, including continuum and spectral line emission in the radio domain (e.g. Carilli & Walter 2013, and references therein). While molecular gas has been studied across the Universe up to z ∼ 1 and beyond, H i emission remains undetected through lensing, with two searches for galaxy–galaxy lensed H i sources at z ∼ 0.4 (Hunt, Pisano & Edel 2016; Blecher et al. 2019). Gravitational lensing conserves surface brightness while increasing the solid angle of the source, boosting the observed flux. This amplification μ can facilitate the detection of unresolved lensed sources, which maximises their detection probability, and reduces the integration time needed for a given source by μ2. Next-generation cm-wavelength interferometers are now sensitive enough to observe the higher redshift H i Universe, and the detection of gravitationally lensed H i is probable in new surveys (Deane, Obreschkow & Heywood 2015). The detection of lensed H i behind intermediate-redshift galaxy clusters will provide a deep cosmic view of H i emission in galaxies, pre-SKA era, within a fraction of the observation time of unlensed detections. Successful lensed H i detections, along with readily detected CO emission lines, will constrain the H i/H2 ratio at these redshifts, an important parameter in understanding galaxy evolution over cosmic time (Obreschkow & Rawlings 2009).

2020MNRAS.498.6069P__Dressler_1980_Instance_1

The present Universe is full of galaxies that come in various shapes and sizes with different mass, luminosity, colour, star formation rate (SFR), metallicity, and H i content. Understanding the galaxy properties and their evolution is an important goal of cosmology. The modern galaxy surveys, 2dF Galaxy Redshift Survey (2dFGRS; Colless et al. 2001) and Sloan Digital Sky Survey (SDSS; Strauss et al. 2002) reveal that the galaxies are distributed in the cosmic web (Bond, Kofman & Pogosyan 1996), which is an interconnected web-like network comprising of different types of environments such as filaments, sheets, knots, and voids. The galaxy properties vary across the different environments in the cosmic web. For example, the well-known density–morphology relation reveals that the ellipticals are preferably found inside the dense groups and clusters, whereas the spirals are intermittently distributed in the fields (Hubble 1936; Zwicky 1968; Oemler 1974; Dressler 1980; Goto et al. 2003). These findings are further supported by other studies with two-point correlation function (Willmer, da Costa & Pellegrini 1998; Brown, Webstar & Boyle 2000; Zehavi et al. 2005), genus statistics (Hoyle et al. 2002; Park et al. 2005), and filamentarity (Pandey & Bharadwaj 2005, 2006) of the galaxy distribution. It is now well known that many other galaxy properties are strongly sensitive to their environment (Davis & Geller 1976; Guzzo et al. 1997; Zehavi et al. 2002; Blanton et al. 2003; Einasto et al. 2003a; Hogg et al. 2003; Kauffmann et al. 2004; Mouhcine, Baldry & Bamford 2007; Koyama et al. 2013). The formation and evolution of galaxies are known to be driven by accretion, tidal interaction, merger, and various other secular processes. These physical processes are largely determined by the environment of the galaxies. The environment thus play a central role in the formation and evolution of galaxies and the study of the environmental dependence of the galaxy properties provides crucial inputs to the theories of galaxy formation and evolution.

2015MNRAS.446.3002B__Diemand,_Moore_&_Stadel_2004_Instance_1

We recall that the velocity anisotropy profile is given by a combination of the radial and tangential velocity dispersion: (15) \begin{equation} \beta _{\rm ani}(r)\equiv 1-\frac{\bar{v_{\theta }^2}(r)}{\bar{v_r^2}(r)}\,. \end{equation} Due to the lack of observational constraints on this quantity, the first anisotropy profiles discussed in the literature were based on analytical studies aiming at building dynamical models (in spherical symmetry) with self-consistent stellar phase-space distribution functions. Many such models have simple anisotropy profiles that are either constant or change from isotropic near the centre to radial at large radius (e.g. Osipkov 1979; Merritt 1985, see below). More recently, indications of radial anisotropy in the outer regions of DM haloes have been obtained from numerical simulations (e.g. Diemand, Moore & Stadel 2004). In the inner region, a strong anisotropy can be generated by dynamical formation and evolution processes. To better describe these profiles, Baes & van Hese (2007) introduced a technique to construct dynamical models with arbitrary mass density and anisotropy profiles. These three different families of anisotropy profiles are described below and will be explored in Section 5. The constant anisotropy modelling (e.g. used by Charbonnier et al. 2011) simply reads (16) \begin{equation} \beta _{\rm ani}^{\rm Cst}(r)=\beta _0. \end{equation} The Osipkov–Merritt profile (Osipkov 1979; Merritt 1985) is parametrized as (17) \begin{equation} \beta _{\rm ani}^{\rm Osipkov}(r)=\frac{r^2}{r^2+r_a^2}, \end{equation} with a single free scale parameter ra which locates the transition from βani = 0 in the inner parts (isotropic) to 1 at large radii (full radial anisotropy). The Baes and van Hese profile (Baes & van Hese 2007) is more general and is written as (18) \begin{equation} \beta _{\rm ani}^{\rm Baes}(r) =\frac{\beta _0 + \beta _\infty (r/r_a)^\eta }{1+(r/r_a)^\eta }\,, \end{equation} where the four parameters are the central anisotropy β0, the anisotropy at large radii β∞, and the sharpness of the transition η at the scale radius ra. The Osipkov–Merritt profile is recovered when using β0 = 0, β∞ = 1 and η = 2.

2017MNRAS.471.3057M__Bovy_et_al._2016b_Instance_1

We have performed the first detailed dissection of the stellar populations of the Milky Way disc in age, [Fe/H] and $\mathrm{[ \alpha \mathrm{/Fe]}}$ space, bridging the gap between the detailed observational understanding of MAPs (e.g. Bovy et al. 2012b, 2016b) and the plethora of studies of co-eval stellar populations in simulated galaxies (e.g Bird et al. 2013; Stinson et al. 2013; Martig et al. 2014a). We have placed novel constraints on models for the formation of the Milky Way disc by combining detailed density models fit to the mono-age, mono-[Fe/H] populations of the low and high $\mathrm{[ \alpha \mathrm{/Fe]}}$ disc, with surface mass density contributions calculated on the basis of these density fits and stellar evolution models. We summarize our key results as follows: Radial and vertical profiles: The mono-age, mono-[Fe/H] populations of the $\mathrm{[ \alpha \mathrm{/Fe]}}$ poor disc are well fitted by a radially broken exponential, with a peak radius, Rpeak, that varies as a function of age and [Fe/H]. We find that the distance between Rpeak's of the low and high [Fe/H] populations increases with age, which we interpret as evidence for a decreasing [Fe/H] gradient with time (e.g. Anders et al. 2017). The radial variation of the stellar surface density of the high $\mathrm{[ \alpha \mathrm{/Fe]}}$ mono-age populations is found to have insignificant breaks, and they are better fit by a single exponential in this disc region. As these populations are the oldest, this may be a sign of the disc evolution washing out the density peak over time, or may point to a different formation scenario for high $\mathrm{[ \alpha \mathrm{/Fe]}}$ stars, where no density peak ever existed. These findings are in good agreement with earlier studies of MAPs (Bovy et al. 2016b). We measure an average high $\mathrm{[ \alpha \mathrm{/Fe]}}$ population scalelength of hR, in = 1.9 ± 0.1 kpc, and find scaleheights between 600 and 1000 pc, in good agreement with current measures of the $\mathrm{[ \alpha \mathrm{/Fe]}}$ rich disc scalelength and scaleheight (e.g. those outlined in Bland-Hawthorn & Gerhard 2016).Profile broadening: We show that the radial surface density profile of the low $\mathrm{[ \alpha \mathrm{/Fe]}}$ populations broadens with age in a given [Fe/H] bin, which we interpret as evidence of the gradual dispersal of mono-[Fe/H] populations, presumably due to radial migration and radial heating. The variation in shape of the broken exponential profile changes differently depending on the population [Fe/H], with low [Fe/H] populations inner profiles flattening faster, whereas the high [Fe/H] outer profiles flatten faster. We interpret this effect as tentative evidence for [Fe/H] dependent radial migration arising from pre-existing [Fe/H] gradients in the star-forming disc. We showed that our results qualitatively reproduce those of Hayden et al. (2015), finding a skewed MDF that varies as a function of R.Flaring: We find that flaring seems to be present in almost all mono-age populations, at differing levels. We have shown that the inverse flaring scalelength Rflare− 1 increases with age, meaning that the youngest populations flare most strongly. This finding appears inconsistent with that above, under the assumption that flaring is the result of radial migration. However, these results may be reconciled by invoking a more active accretion history in the early life of the disc, which could have suppressed flaring (e.g. Minchev et al. 2014b).The surface-mass density at R0: We have measured the surface mass density at the solar radius for each mono-age, mono-[Fe/H] population, finding a total surface mass density of $\Sigma _{R_0, {\rm tot}} = 20.0_{-2.9}^{+2.4}\mathrm{(stat.)}_{-2.4}^{+5.0}\mathrm{(syst.)}\ \mathrm{M_{{\odot }} \ pc^{-2}}$. Before allowing for systematics, this value is less than current estimates (e.g. Flynn et al. 2006; Bovy et al. 2012a; McKee et al. 2015), however, the systematic uncertainties are large, mainly due to a mismatch between the log g scales in APOGEE and the PARSEC models, and as such, we find our value to be consistent within the uncertainties. The relative contribution of high to low $\mathrm{[ \alpha \mathrm{/Fe]}}$ populations, $f_\Sigma$, is 18 per cent ± 5 per cent, which is consistent with existing measurements (e.g. Bland-Hawthorn & Gerhard 2016).The hZ distribution at R0: The shape of the mass-weighted hZ distribution found by this study is in good agreement with that of Bovy et al. (2012a), calling into question the existence of a vertical structural discontinuity in the Milky Way disc. The reconciliation of this finding with the discontinuity in chemical space (e.g. the bimodality in $\mathrm{[ \alpha \mathrm{/Fe]}}$ at fixed [Fe/H]: Nidever et al. 2014; Hayden et al. 2015) may shed new light on our understanding of the formation of the Galactic disc.The surface-mass density profile of the Milky Way: We have found the combined (from mono-age, mono-[Fe/H] populations at low and high $\mathrm{[ \alpha \mathrm{/Fe]}}$) surface-mass density-weighted profiles of the Milky Way disc as a function of $\mathrm{[ \alpha \mathrm{/Fe]}}$, age and [Fe/H], and found that the total surface density is also described by a broken exponential. We find that our results fail to determine the sign of the inner exponential to high significance out to ∼10 kpc, but detect a turnover to a declining exponential, at high significance, thereafter. We find evidence of a radial mean age and [Fe/H] gradient driven by the changing dominant population as a function of radius. A detailed comparison of these findings with numerical simulations is necessary for a proper interpretation. Our finding of a decline in stellar density may be consistent with that found in other studies (e.g. Reylé et al. 2009; Sale et al. 2010), albeit at shorter radii.

2021AandA...652A.117B__Rieder_&_Kenworthy_2016_Instance_1

Ring systems are a ubiquitous feature in planetary systems – all the gas giants in the Solar System have ring systems around them of varying optical depths (see, e.g., Tiscareno 2013; Charnoz et al. 2018), and ring systems have been detected around minor planets (e.g., Chariklo; Braga-Ribas et al. 2014), so it is reasonable that exoplanets and substellar objects host ring systems as well. Long-period eclipsing binary star systems, where one star is surrounded by an extended dark disk-like structure that periodically eclipses the other component, have already been observed, such as EE Cep (Mikolajewski & Graczyk 1999), ϵ Aurigae (Guinan & Dewarf 2002), and TYC 2505-672-1, with a companion period of 69 yr (Lipunov et al. 2016; Rodriguez et al. 2016). A large ring-like structure around a substellar companion was proposed to explain observations from 2007 from the J1407 system (Mamajek et al. 2012). 1SWASP J140747.93-394 542.6 (V1400 Cen; hereafter called “J1407”) is a young, pre-main-sequence star in the Sco-Cen OB association (Mamajek et al. 2012) with spectral type K5 IV(e) Li and is similar in size and mass to the Sun. In 2007, it displayed a complex symmetric dimming pattern of up to ~ 3 magnitudes during a 56 day eclipse. This has been attributed to the transit of a substellar companion (called “J1407 b”) with a mass of 60–100 MJup (Rieder & Kenworthy 2016) surrounded by an exoring system consisting of at least 37 rings and extending out to 0.6 au in radius (Kenworthy & Mamajek 2015). For these rings to show detectable transit signatures, they must be significantly misaligned with respect to the orbital plane of J1407 b (Zanazzi & Lai 2017). This potential ring system would be considerably larger than the ring system of Saturn, which is located within the planet’s tidal disruption radius. The proposed rings around J1407 b would even cover a significant fraction of the companion’s Hill sphere and would not be expected to be stable over gigayear timescales. If the candidate ringed companion is in a bound orbit around the star, this orbit must be moderately eccentric in order for no othereclipses to have been detected to date (Kenworthy et al. 2015), raising the possibility that there might be a second as yet undetected companion in the system that causes the implied orbital eccentricity for J1407 b. Radial velocity measurements are overwhelmed by the chromospheric noise of the star and do not place strong constraints on other substellar companions (Kenworthy et al. 2015). The transit of J1407 suggests that its orbital plane has a high inclination to our line of sight – if there are other planets inside the orbit of J1407 b, their orbits may well be coplanar with J1407 b and there is a high chance that these companions may transit J1407.

2020AandA...644A.159C__Titov_&_Lambert_2013_Instance_1

In order to try to get insights into such systematics, we produced several variants of the ICRF3 S/X band frame by changing the reference epoch of the catalog or alternately by not considering Galactic acceleration in the modeling. Interestingly, the D2 and D3 glide terms for these variants were found to vary by several tens of microarcseconds in the comparison to ICRF2, in line with the level of the systematics observed for those terms. Such findings are not unexpected since Galactic acceleration manifests itself as a dipolar deformation in the source coordinates (e.g., Titov & Lambert 2013). Moving further, and noting that Mignard et al. (2016) mentioned this phenomenon as a possibility for explaining the observed glide between ICRF2 and the Gaia Data Release 1 (Gaia DR1) auxiliary quasar solution, we decided to reproduce an equivalent of ICRF2 by considering only the stretch of data used for ICRF2 (i.e., including only the VLBI sessions up to March 2009 in the solution) and to make a variant that adds Galactic acceleration in the modeling, as implemented for ICRF3. To guarantee the maximum consistency, those two analyses were conducted by employing the same software package as that used for ICRF2, namely CALC-SOLVE (see Fey et al. 2015). Looking at the results, we first observed that our “reproduced” ICRF2 shows similar deformations as the original ICRF2 when compared to ICRF3, hence ruling out the possibility that ICRF2 was in error. Most importantly, the ICRF2 variant that incorporates Galactic acceleration modeling was found to have much reduced glide terms compared to the original or reproduced ICRF2. This is illustrated by the bar chart in Fig. 16 which shows that the D2 term has now vanished while the D3 term has been cut by more than half (down to a value of −39 ± 4 μas) in this variant, hence indicating that the deformations between the two frames, in large part, stem from Galactic acceleration not accounted for in ICRF2. This is somehow not surprising since the data set for ICRF2 already covered 30 years, enough for Galactic acceleration effects to emerge, even though the accuracy of the frame was lower than that of ICRF3.

2019ApJ...870...39V__Veron-Cetty_&_Veron_1986_Instance_1

NGC 3557 is a bona fide southern-sky elliptical galaxy (E3) at a distance of 40 Mpc (1″ is 198 pc at this distance7 7 For distance derivations, we have assumed a cosmology model with H0 =73 km s−1 Mpc−1, Ωmatter = 0.27, and Ωvacuum = 0.73. ), and a member of a small group of galaxies (Brough et al. 2006). It has been classified as a LINER (e.g., Annibali et al. 2010) and as a flat-spectrum radio galaxy (Healey et al. 2007), with a jet that bends at distances of a few arcmin from the center (Schmitt et al. 2002). Detections of several of the ISM components of this object have been reported in the literature. Dust has been observed both as FIR emission (Pasquale et al. 2009) and as absorption against the central stellar continuum (Lauer et al. 2005). Nuclear optical line emission has been reported from spectroscopy (Veron-Cetty & Veron 1986; Rampazzo et al. 2005) as well as narrowband photometry (Goudfrooij et al. 1994). The MIR spectrum of NGC 3557 is of the most common Class-2 type, which is currently associated with a post-star-formation phase (Vega et al. 2009). Regarding the cold gas component, atomic gas (H i) has been reported as nondetection in several works (Serra & Osterloo 2010), while molecular gas emission has been detected in single-dish observations (Prandoni et al. 2010). NGC 3557 was included in our sample because of its relative proximity and CO(2–1) brightness (as reported by Prandoni et al. 2010), which suggested the possibility to study the molecular structures in detail. Since the object is considered to be in a stage where little current star formation may be happening, it was considered important as a representative of the molecular gas structures to be expected in post-star-formation scenarios. Furthermore, the disk-like nuclear dust distribution seen in the photometry by Lauer et al. (2005) indicated the possible presence of a molecular gas disk, which is a very interesting dynamical structure linked to the presence of organized angular momentum at those spatial scales.

2020ApJ...889...15Y__Yang_et_al._2016b_Instance_1

Although each one of the four aforementioned mechanisms has some observational support in certain systems, there is not a single mechanism that can explain all observed polarization in protoplanetary disks. Alignment with respect to the local radiation anisotropy (“k-RAT alignment” thereafter) is best supported by the azimuthal polarization pattern observed at ALMA Band 3 in the HL Tau system (Kataoka et al. 2017). However, it predicts a strong azimuthal variation of polarization and circular pattern (rather than elliptical pattern) (Yang et al. 2019). There is some tentative evidences for alignment with respect to the magnetic field, through either Radiative Alignment Torques (“B-RAT alignment”; Lazarian & Hoang 2007), or recently proposed Mechanical Alignment Torques (Hoang et al. 2018), in, e.g., the IRAS 4A system at cm wavelengths (Cox et al. 2015; Yang et al. 2016b) and BHB07-11 (Alves et al. 2018) at (sub)millimeter wavelengths. But there is no well-resolved system that matches the theoretical expectations (see, e.g., Cho & Lazarian 2007; Yang et al. 2016b; Bertrang et al. 2017) assuming the widely expected disk toroidal magnetic field yet (Flock et al. 2015). Mechanical alignment has recently received some attention. Hoang et al. (2018) claims that under MATs, grains can be aligned with respect to local dust-gas streaming direction, in the case of a weak or zero magnetic field, even if the velocity difference is sub-sonic. Within this picture, Kataoka et al. (2019) investigated the direction of streaming velocities for dust grains with different Stokes numbers, and the resulting polarization orientations. They found that their polarization pattern in the order-of-unity Stokes number case resembles that observed by Alves et al. (2018) in BHB07-11. The BHB07-11, however, is a binary system, and we expect more complicated velocity fields than the simple one assumed in Kataoka et al. (2019). Yang et al. (2019) investigated the observational features of another mechanical alignment mechanism, the Gold mechanism (Gold 1952), to address the circular versus elliptical pattern problem in the ALMA Band 3 polarization observations of HL Tau disk. However, they failed to explain the nonexistence of strong azimuthal variation, and suggested the scattering by dust grains aligned under the Gold mechanism may be the origin of the polarization at ALMA Band 3 in the HL Tau system.

2018ApJ...860...24P__Warmuth_2015_Instance_1

Figure 13 shows the temporal evolution of the density, ρ, plasma flow velocity, vx, position of the wave crest, PosA, phase speed, vw, and magnetic field component in the z-direction, Bz, for the primary waves in every different case of initial amplitude, ρIA. In Figure 13(a), we observe that the amplitude of the density remains approximately constant at their initial values until the time when the shock is formed and the density amplitude of the primary wave starts decreasing (see Vršnak & Lulić 2000), i.e., at t ≈ 0.03 (blue), t ≈ 0.04 (red), and t ≈ 0.055 (green). For the case of ρIA = 1.3 (magenta), a decrease of the amplitude of the primary can hardly be observed, as expected for low-amplitude wave (Warmuth 2015). One can see that the larger the initial amplitude, ρIA, the stronger the decrease of the primary wave’s amplitude, which is consistent with observations (Warmuth & Mann 2011; Muhr et al. 2014; Warmuth 2015). The amplitudes decrease to values of ρ ≈ 1.6 (blue), ρ ≈ 1.5 (red), and ρ ≈ 1.4 (green) until the primary wave starts entering the CH. Due to the fact that the waves with larger initial amplitude enter the CH earlier than those with small initial amplitude, we can see in Figure 13(a) that the tracking of the parameters of the faster waves stops at an earlier time than the one for the slower waves. A similar behavior to the one of the density, ρ, can be observed for the plasma flow velocity, vx, in Figure 13(b) and the magnetic field component, Bz, in Figure 13(e). Here, the amplitudes decrease from vx = 0.75, Bz = 1.9 (for ρIA = 1.9, blue), vx = 0.6, Bz = 1.7 (for ρIA = 1.7, red), vx = 0.45, Bz = 1.5 (for ρIA = 1.5, green), and vx = 0.27, Bz = 1.3 (for ρIA = 1.3, magenta) to vx = 0.55, Bz = 1.6 (for ρIA = 1.9, blue), vx = 0.46, Bz = 1.5 (for ρIA = 1.7, red), vx = 0.36, Bz = 1.4 (for ρIA = 1.5, green), and vx = 0.25, Bz = 1.25 (for ρIA = 1.3, magenta). Figure 13(c) shows how the primary waves propagate in the positive x-direction. In all four cases of different initial amplitude, ρIA, the phase speed decreases slighty (consistent with observations; see Warmuth et al. 2004 and Warmuth 2015) until the waves enter the CH at different times, i.e., the values for the phase speed start at vw ≈ 2.2 (for ρIA = 1.9, blue), vw ≈ 1.9 (for ρIA = 1.7, red), vw ≈ 1.7 (for ρIA = 1.5, green), and vw ≈ 1.4 (for ρIA = 1.3, magenta) and decrease to vw ≈ 1.5 (for ρIA = 1.9, blue), vw ≈ 1.39 (for ρIA = 1.7, red), vw ≈ 1.2 (for ρIA = 1.5, green), and vw ≈ 1.13 (for ρIA = 1.3, magenta).

2019AandA...623A..11P__Simm_et_al._2016_Instance_1

Another clear difference for Ark 120 with the NT thin disc predictions is the variability. From the best simultaneous fit of the 2013 and 2014 observations, we infer a significant increase in mass accretion rate through the disc from 0.03 to 0.07 Lbol/LEdd in only one year, but a standard thin disc around a SMBH cannot vary on such timescale. Indeed, the radial mass accretion rate change via viscous processes has a time-scale of torb(R)/[α(H/R)2]. For Ark,120, assuming an orbital time-scale at R = 100 Rg, a viscosity parameter of 0.1 and a H/R (H is the height scale of the disc) value of 0.1, this corresponds to ∼150 years. Moreover, the optical-UV flux significantly changes in less than a year, varying for example by a factor of 50% in the UVW2 band between 2013 and 2014 (e.g. see Fig. 1, Lobban et al. 2018). Similar rapid changes in the optical-UV flux are typically seen in other BLS1s, especially those at low Lbol/LEdd (e.g. MacLeod et al. 2010; Kozłowski 2016; Simm et al. 2016; Rakshit & Stalin 2017). These are generally assumed to be from reprocessing, where the X-ray flux illuminates the outer disc (e.g. Buisson et al. 2017), and adds to the intrinsic emission. An additional reprocessed component in the optical-UV would lead us to overestimate the value of the intrinsic Ṁ, so to an underestimate of BH spin via the efficiency argument (Kubota & Done 2018). Nonetheless, changes as large as about 50% in the UV flux are unlikely to be driven by X-ray reprocessing, as the UV flux in Ark 120 is much higher than in the X-ray band. Besides, detailed models of the expected optical-UV variability from X-ray reprocessing fail to fit the excellent long term simultaneous optical-UV-X-ray datasets, and would imply a larger disc size than expected by standard thin disc (e.g. NGC 5548: McHardy et al. 2014; Edelson et al. 2015; Gardner & Done 2017; NGC 4151: Edelson et al. 2017; Ark 120: Gliozzi et al. 2017; Fairall 9: Pal et al. 2017; NGC 4593: Cackett et al. 2018; Pal & Naik 2018; Microlensing studies: Morgan et al. 2010; Dai et al. 2010). Such large discs should be significantly brighter than observed and this discrepancy may be explained for example by a flatter temperature profile than in NT discs, from scattering of a significant part of the optical flux on larger scales, by electron scattering in the disc atmosphere (Dai et al. 2010; Morgan et al. 2010; Hall et al. 2018).

2021ApJ...914L..19Z__Metzger_et_al._2008_Instance_1

Thermonuclear explosions and AICs of WDs in AGN disks are potential sources for future joint gravitational wave (GW), EM, and neutrino multi-messenger observations. In addition to AIC of WDs, another possible formation channel of millisecond magnetars in AGN disks is mergers of BNSs. Such a merger may produce a millisecond magnetar if the NS equation of state is stiff enough (e.g., Ai et al. 2020). This would also drive a magnetar-powered explosion as discussed above. The mechanism by which a nascent millisecond magnetar might power a GRB jet has been studied in detail over the past decade (Bucciantini et al. 2008, 2012; Metzger et al. 2008, 2011; Siegel et al. 2014).8 8 Some indirect evidence for the magnetar mechanism in GRBs are the presence of a plateau in the early X-ray afterglow of long-duration GRBs, which may be explained as the continuous energy injection from the spindown of a magnetar (Dai & Lu 1998; Zhang & Mészáros 2001; Zhang et al. 2006). A putative jet may thus be launched from the AIC of WDs and BNS mergers occurring in AGN disks. However, Zhu et al. (2021b, 2021a) and Perna et al. (2021a) recently showed that GRB jets embedded in AGN disks would be usually choked by the dense material of the accretion disks. Although it is hard to observe gamma-ray signals, Zhu et al. (2021a) suggested that these choked GRBs may effectively produce TeVPeV neutrinos that could be detected by IceCube and IceCube-Gen2. Furthermore, the dissipation of magnetic energy during the merger of BWDs is expected to accelerate cosmic rays and produce high-energy neutrinos (Xiao et al. 2016). In the GW channel, BWD mergers are promising astrophysical GW sources for space-borne GW observatories, e.g., LISA (Amaro-Seoane et al. 2017), TaiJi (Ruan et al. 2020), and TianQin (Luo et al. 2016), while the GW signals from BNS mergers are readily detected with the ground-based GW detectors such as LIGO and Virgo (Abbott et al. 2017). Future joint observations of GW, EM, and neutrino signals can reveal the existence of WD and NS populations in AGN disks.

2022AandA...668A..10F__Walker_et_al._2008_Instance_1

The most common approaches to observe SPI are spectral observations of typical emission lines for stellar chromospheres and coronae. The earliest approach to observe SPI dates back to the early 2000’s and focused on non-thermal chromospheric Ca II H and K emissions (Shkolnik et al. 2003). Subsequent studies by Shkolnik et al. (2005, 2008) of the system HD 179949 saw enhanced emissions in four out of six observational epochs that appeared to be periodic with the planetary orbital period. Other authors observed different systems and likewise saw chro-mospheric excess emissions (Walker et al. 2008; Staab et al. 2017). In addition, Cauley et al. (2019) estimated possible magnetic field strengths of hot Jupiters based on chromospheric excess emissions. The derived energy fluxes from chromospheric Ca II H and K emissions are larger than typical fluxes derived from Alfvén wing models and magnetohydrostatic models (Saur et al. 2013; Lanza 2015) and the observed periodicity only appears in some epochs, which was suggested to be alternatively explained by star spots (Miller et al. 2012). Recently, Strugarek et al. (2019) investigated how modeling and observations could reconcile by including the magnetic topology of stellar coronae based on the example of Kepler-78. In the UV range, France et al. (2016, 2018) conducted large surveys with the Hubble Space Telescope, however, the authors could not identify any signals related to SPI. At coronal X-ray wavelengths, several studies have investigated the influence of planets on stellar X-ray activity, such as Kashyap et al. (2008); Scharf (2010); Poppenhaeger et al. (2010). Some studies found correlations between planets and X-ray activity in stars and some did not. Poppenhaeger & Schmitt (2011a,b) explain previously observed correlations, attributed to SPI, as a result of selection effects due to planet detection methods and the limitations in X-ray observations. The radio wavelength range is particularly promising to search for SPI. Recent observations with LOFAR showed strong hints for the existence of SPI in several systems (Vedantham et al. 2020; Callingham et al. 2021; Pérez-Torres et al. 2021). In addition, a recent campaign in the radio range provided the first tentative direct observational hints of an intrinsic magnetic field on an exoplanet (Turner et al. 2021).

2022MNRAS.514.2974M__Dadina_2007_Instance_1

Active galactic nuclei (AGNs) are extragalactic sources that emit across the whole electromagnetic spectrum. Such systems are composite and each sub-structure has its own role in shaping the emerging spectrum (see Padovani et al. 2017, for a comprehensive review). It is ubiquitously accepted that the X-ray emission originates in the very inner regions of AGNs, near the central supermassive black hole (SMBH). Accretion of matter infalling on to the SMBH is responsible for the enormous amount of optical-UV photons, a fraction of which can be further energized via inverse-Compton (Sunyaev & Titarchuk 1980) off thermal electrons (the so-called hot corona: Haardt & Maraschi 1991, 1993; Madejski et al. 1995; Zdziarski et al. 1995) up to the X-rays. The maximum energy gain for these seed photons is mainly set by the hot plasma’s temperature, and, to a lower extent, by its opacity (e.g. Rybicki & Lightman 1979; Beloborodov 1999; Middei et al. 2019). In fact, the X-ray continuum in AGNs is well modelled by a power law with a high energy roll-over (e.g. Perola et al. 2002; Dadina 2007; Molina et al. 2009, 2013; Malizia et al. 2014; Fabian et al. 2015, 2017; Ricci et al. 2018; Tortosa et al. 2018). AGN X-ray spectra may show additional features due to reprocessing of the primary X-ray emission by the circumnuclear material. A fluorescence emission line from the Fe K-shell is commonly observed as the most prominent feature (e.g. Bianchi et al. 2009) and its analysis carries a wealth of information on the physics of the reflecting material. This emission line has an intrinsically narrow profile that can undergo distortions, such as broadening, due to special and general relativistic effects. In particular, the closer to the SMBH the reflectors, the more distorted (i.e. the broader) the neutral or ionized Fe line profile (e.g. Fabian et al. 1995). On the contrary, at larger distance, these effects are negligible, thus the Fe Kα shape is consistent with a narrow profile. Additionally, in the case of Compton-thick reflectors (i.e. NH ≳ 1.5 × 1024 cm−2) the X-ray spectra show a typical emission excess around 30 keV, the so-called Compton-hump (e.g. Matt, Fabian & Ross 1993). The effect of any absorbing matter crossing our line of sight can significantly attenuate the observed number of photons, especially in the soft X-rays (e.g. Cappi et al. 1999; Awaki et al. 2000; Matt 2002; Bianchi et al. 2009; Middei et al. 2021).

2017AandA...608A..16R__Ravindranath_et_al._2006_Instance_1

The measurement of clumps at redshifts beyond the peak of cosmic star formation is notoriously difficult. The identification of clumpy galaxies in the dominant population of irregular galaxies at high redshift dates back to the first deep Hubble Space Telescope (HST) images (e.g., Williams et al. 1996). Subsequent studies at z ~ 1−3 revealed that clumpy galaxies are more numerous than in the local Universe (e.g., Abraham et al. 1996; van den Bergh et al. 1996; Giavalisco et al. 1996; Elmegreen et al. 2004, 2007, 2008, 2009; Elmegreen & Elmegreen 2006; Elmegreen et al. 2013; Kubo et al. 2013, 2016; Glazebrook 2013; Tadaki et al. 2014; Murata et al. 2014; Guo et al. 2015; Garland et al. 2015; Bournaud 2016). The fraction of clumpy galaxies was studied from z = 0 up to the most distant galaxies identified today at z ~ 10 (Ravindranath et al. 2006; Guo et al. 2012, 2015; Shibuya et al. 2016). In the sample of galaxies with 0.5 z 3 in the CANDELS survey, Guo et al. (2015) find that galaxies with low mass log (M⋆/M⊙) 9.8 have a high fraction of off-center clumps fclumpy ~ 60% constant over the observed redshift range, while for intermediate and massive galaxies fclumpy decreases from ~40% at z ~ 3 to ~15% at z ~ 0.5. Combining deep HST imaging from the 3D-HST, CANDELS, HUDF and HFF surveys Shibuya et al. (2016) claim that \hbox{$f_{\rm clumpy}^{\rm UV}$}fclumpyUV follows an evolution similar to that of the star formation rate density (e.g., Madau & Dickinson 2014), increasing from z ≃ 8 to z ≃ 1−3 and decreasing from z ≃ 1 to z ≃ 0. In comparing these observed trends with the predictions of simulations, Guo et al. (2015) conclude that VDI are likely responsible for fclumpy at high mass and that minor mergers are a viable explanation for fclumpy at intermediate mass for z 1.5, while Shibuya et al. (2016) conclude that VDI is the main origin of all clumps. Both these studies exclude major mergers as a possible contribution to the evolution of the fraction of clumps. This is somewhat surprising as the major merger fraction for star-forming galaxies is observed to increase up to ~20% at z ≃ 1−2 (e.g., Lotz et al. 2011; López-Sanjuan et al. 2011, 2013), staying high at least to z ~ 3−4 (e.g., Conselice et al. 2008; Tasca et al. 2014a), and one would therefore expect that a fraction of the clumps is related to ex situ major merging.

2020MNRAS.499.1788W__Wolfire_et_al._2003_Instance_2

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

2021MNRAS.503..324M__Zhao_et_al._2019_Instance_1

We first determined the orbital parameters for RS Ser, V449 Per, and V1095 Her. Further, we updated the parameters for V593 Cen and MR Del. Using the formula f = (Ωin – Ω1)/(Ωin – Ωout), we calculated the contact factors f for RS Ser, V593 Cen, and V1095 Her as 6.5 per cent, 40 per cent, and 53 per cent, respectively. RS Ser is a contact binary with a small temperature difference of 131 K and a low contact factor. For V593 Cen, we updated the orbital parameters using more complete light curves. The orbital inclination of 83°.18 is similar to the result (82°.6) obtained by Zhao et al. (2019). The temperature of the secondary component (15 284 K) is higher than the previous result of 15 099 K. However, the mass ratio of 0.6 is lower than the previous result of 1.05 (Zhao et al. 2019). More spectroscopic observations are required to confirm the mass ratio. We confirmed that V593 Cen is an early-type contact binary with a deep contact factor as well as a black hole candidate. For MR Del, we revised the absolute parameters using its full light curve and the published radial velocities, which are similar to those published previously (Zhao et al. 2019; Pribulla et al. 2009; Djurašević et al. 2011). V1095 Her is also a contact binary with a deep contact factor of 40 per cent and a temperature difference of about 172 K. Looking over our four complete light curves, we found no evident starspot activity, and estimated variations exist over a long-term time-scale of years. V449 Per is an interesting target for detecting extra-solar and brown dwarfs using the minima timing variability of a low-mass eclipsing binary (Pribulla et al. 2012). Additional minima with higher precision are required to study its periodic variation further. Our physical parameters for RS Ser, V593 Cen, and V1095 Her are based on a light curve with a q-search-determined mass ratio. The nature of these parameters is speculative and preliminary. Radial velocities may eventually come to rescue them and provide a more definitive determination.

2020MNRAS.494.2851C__Dijkstra_et_al._2008_Instance_1

Previously it has been postulated that the SMS formation by DC is only possible in atomic cooling haloes both with intense FUV irradiation and with primordial gas composition. Here we have shown that SMSs can form also in slightly metal-enriched cases as long as FUV irradiation is intense enough. This relaxation of the condition will increase the expected number density of massive seed BHs. Several authors have estimated the number density of such seeds formed in the usual DC scenario, which requires metal-free gas composition. Using the critical intensity advocated by recent studies (Agarwal et al. 2014; Sugimura et al. 2014; Inayoshi & Tanaka 2015), this ranges from a few Gpc−3 (e.g. Dijkstra et al. 2008; Dijkstra, Ferrara & Mesinger 2014), to 10−6 to 10−4 Mpc−3 (e.g. Agarwal et al. 2012; Visbal, Haiman & Bryan 2014a; Chon et al. 2016; Habouzit et al. 2016; Valiante et al. 2016). The dynamical heating model by Wise et al. (2019) predicts the number density of 10−7 to 10−6 Mpc−3. Those seeds can account for the origin of the rare BHs in the high-z universe. If all the SMBHs down to z = 0 shares the universal origin, the seed density should be comparable to that of the SMBHs ubiquitously residing in massive galaxies, ∼0.01–0.1 Mpc−3 (Aller & Richstone 2002; Davis et al. 2014), which is much larger than the seed density predicted by the DC model. The DC in the primordial environment is terminated around z ∼ 10, as the metal enrichment proceeds (e.g. Trenti & Stiavelli 2009; Chon et al. 2016): once a Pop III star ends its life as a core-collapse SN, metallicity inside the host halo jumps up to 10−4 to 10−3 Z⊙ (e.g. Maio et al. 2010; Ritter et al. 2015; Sluder et al. 2016; Chiaki, Susa & Hirano 2018). According to our result, the SMS formation can continue even in such second-generation haloes. Since the second-generation haloes tend to be under stronger radiation field than the pristine ones (e.g. Dijkstra et al. 2014), we expect significant increase in the number density of the SMSs. For example, the first episode of star formation delays another star formation for a few hundred million years by the radiative and SNe mechanical feedback, which ejects a gas from the halo. If the haloes approach close enough to a luminous galaxy before another episode of star formation, they can be ideal sites for SMS formation. Not only the radiation sources outside the halo, but also those inside the same halo can trigger SMS formation in an irradiated massive cloud as long as the metallicity is low enough. With such new varieties of SMS formation sites, the expected seed BH number will be largely enhanced. We will pursue the validity of this scenario using samples from the cosmological simulations in the future studies.

2020MNRAS.492.3509B__Garsden_et_al._2015_Instance_1

In the context of RI imaging techniques, the standard clean algorithm implements a non-linear, greedy approach to perform deconvolution in an iterative manner (Högbom 1974). Working pixelwise, clean implicitly assumes sparsity of the sought image, removing at each iteration, a fraction of the maximum intensity pixel convolved with the dirty beam from the computed residual image. Over the past years, many variants of this celebrated algorithm have been developed, for instance, its multiscale version (Cornwell 2008). In addition to these clean-based approaches, recent developments in the field of compressive sensing (CS) applied for astronomical imaging have given birth to many imaging algorithms, particularly for RI (Wiaux et al. 2009; Carrillo, McEwen & Wiaux 2012; Garsden et al. 2015; Onose et al. 2016). Leveraging optimization frameworks, these methods aim to solve the underlying image recovery problem by enforcing sparsity of the image of interest in some suitable domain. These techniques have shown the potential to surpass the image reconstruction quality obtained by clean -based approaches (Carrillo, McEwen & Wiaux 2014; Onose et al. 2016; Pratley & Johnston-Hollitt 2016; Onose, Dabbech & Wiaux 2017; Dabbech et al. 2018). While the aforementioned methods have been developed mainly for Stokes I imaging, as previously mentioned these can be extended to polarimetric imaging by following the same imaging approach for all the Stokes parameters. In the context of sparsity regularized approaches, one such extension for polarimetric imaging has been presented in Akiyama et al. (2017), promoting sparsity of each of the Stokes parameters using ℓ1 norm combined with total variation (TV) regularization (Rudin, Osher & Fatemi 1992). A point worth noting here is that the above-mentioned approaches, whether clean and its variants or the sparsity regularized method, solve for the Stokes parameters totally independently. However, these images are physically linked via polarization constraint, i.e. the polarized intensity cannot be greater than the total intensity. Within the CS framework, this constraint has been exploited by a recently proposed approach, namely Polarized SARA, estimating jointly the Stokes parameters (Birdi, Repetti & Wiaux 2018a, b). This approach has been shown to provide better reconstruction quality in comparison with the case when the constraint is not accounted for.

2022MNRAS.517.5473G__Kapanadze_et_al._2018_Instance_1

Various outbursts in GeV–TeV energies from 1ES 1959+650 have been reported by Fermi-LAT and several ground-based Cherenkov experiments like VERITAS, MAGIC, FACT (Albert et al. 2006; Aliu et al. 2014; Biland et al. 2016) including a new highest historical γ-ray activity, detected by MAGIC collaboration on 2016 June 13–14, when the VHE flux above 100 GeV reached up to 3 Crab unit (C.U) (Bhattacharyya et al. 2019). Many multiwavelength campaign from radio to TeV γ-ray energies have been conducted since its discovery (Krawczynski et al. 2004; Biland et al. 2016) and this source has exhibited a number of outbursts across all energies. One interesting VHE outburst was detected on 2002 June 4 by the Whipple telescope without any activity in contemporaneous X-ray energies, called ‘orphan flare’, during a multiwavelength campaign (Krawczynski et al. 2004). In the recent past, 1ES 1959+650 has undergone a few major outbursts in all wavelengths specially in X-ray energies since 2015 (Kapanadze et al. 2016). Unprecedented flux and spectral variability during these episodes have been observed (Kapanadze 2015; Kaur et al. 2017; Kapanadze et al. 2018; Patel et al. 2018). Such flux and spectral variations in different energy bands over time provide an opportunity to study underlying physical processes in terms of particle acceleration processes, evolution of the accelerated particles (leptons/hadrons) within the source, and their radiative cooling and escape processes. Many authors explained the broad-band emission from this source with leptonic one-zone SSC process (Krawczynski et al. 2004; Tagliaferri et al. 2008). But the lack of correlation between X-ray and VHE γ-rays several times and also during the orphan flare, mentioned earlier, challenges the leptonic one-zone SSC model of emission. Alternatively, EC, lepto-hadronic and two-zone SSC models have been also tried to explain the broad-band SED of the source (Backes et al. 2012; Aliu et al. 2014; Asano & Hayashida 2018; Patel et al. 2018). Recently, the MAGIC collaboration again introspected the VHE flaring episodes in 2016, mentioned earlier, to study the feasibility of neutrino emission from 1ES 1959+650 as well under the framework of mixed lepto-hadronic model (MAGIC Collaboration 2020a). Although they (MAGIC collaboration) have concluded that it is difficult to detect neutrinos from the same source during extreme γ-ray flares, it is customary to mention that more study with well-sampled data from multiple experiments are inevitable to understand the true physical processes inside this type of astrophysical sources in a better way.

2019MNRAS.488.5671I__Inoue_&_Iwata_2008_Instance_1

While both Suprime-Cam/NB359 and HST/F336W trace LyC for sources at z > 3.06, NB359 has a narrower filter bandpass, and it preferentially captures ionizing photons closer to the Lyman limit (see Fig. 1). Because IGM attenuation varies as a function of wavelength, expected transmissions of photons through the IGM (here we denote the ratio of flux density with and without IGM attenuation as ‘IGM transmission’) are different for different filters. In Fig. 2 we show the median and 68 percentile IGM transmission values of NB359 andF336W for a source at a redshift range of 3.1 ≤ z ≤ 3.8. These IGM transmissions are estimated from Monte Carlo simulations (Inoue & Iwata 2008) which generate 10 000 sightlines for redshifts consistent with the H i cloud distribution defined analytically by Inoue et al. (2014). For each sightline we calculate IGM transmission through NB359 or F336W for an object with a flat SED in fν (i.e. fν = constant) and obtain median and 68 percentile values from the 10 000 instances. These calculations are repeated from z = 3.1 to 3.8 with a redshift step of 0.1. The median values of IGM transmission for NB359 are higher than those for F336W, especially at the lower redshift range. This is because NB359  traces a rest-frame wavelength range close to the Lyman limit where IGM transmission is higher than that for photons with shorter wavelengths. If the same limiting magnitude is achieved, NB359 is more sensitive for detecting LyC photons from z > 3 galaxies than F336W. Median values of IGM transmission for both NB359 and F336W rapidly decrease as the source redshift increases, which indicates that the detection of LyC photons becomes increasingly difficult due to increasing IGM opacity. However, higher-side 68 percentile IGM transmission values at z = 3.5 are 0.33 for NB359 and 0.20 for F336W, respectively. The fluctuation of IGM transmission among different sightlines is large, and there are still a reasonable number of sightlines with significant IGM transparency for LyC in the redshift range studied in this paper.

2018MNRAS.477.4308R__Novak,_Ostriker_&_Ciotti_2011_Instance_1

It is well known that the accretion on to compact objects may influence the nearby ambient around SMBHs in the centre of galaxies (e.g. Salpeter 1964; Fabian 1999; Barai 2008; Germain, Barai & Martel 2009). Together with the outflow phenomena, it is believed to play a major role in the feedback processes invoked by modern cosmological models (i.e. Λ-Cold Dark Matter) to explain the possible relationship between the SMBH and its host galaxy (e.g. Magorrian et al. 1998; Gebhardt et al. 2000) as well as in the self-regulating growth of the SMBH. The problem of accretion on to an SMBH has been studied via hydrodynamical simulations (e.g. Ciotti & Ostriker 2001; Di Matteo, Springel & Hernquist 2005; Li et al. 2007; Ostriker et al. 2010; Novak, Ostriker & Ciotti 2011). In numerical studies of galaxy formation, spatial resolution permits resolving scales from the kpc to the pc, while the sub-parsec scales of the Bondi radius are not resolved. This is why a prescribed sub-grid physics is employed to solve this lack of resolution. With sufficiently high X-ray luminosities, the falling material will have the correct opacity, developing outflows that originate at sub-parsec scales. Therefore, calculations of the processes involving accretion on to SMBH have become of primary importance (e.g. Proga, Stone & Kallman 2000; Proga 2000, 2003; Proga & Kallman 2004; Proga 2007; Ostriker et al. 2010). Numerical calculations of the accretion of matter on to SMBHs, including the radiative-outflow component, have been mostly performed using Eulerian finite-difference methods (Mościbrodzka & Proga 2013) [see also the overviews by Edgar (2004) and Foglizzo et al. (2005) and references therein for earlier work], while only a few calculations have been reported using smoothed particle hydrodynamics (SPH) techniques (Barai 2008; Barai, Proga & Nagamine 2011, 2012; Nagamine, Barai & Proga 2012), where results for the accretion rates, outflow rates, thermal instabilities, and impact of the thermal, mechanical, and X-ray feedbacks have been obtained for evolutions up to 5 Myr and scales from 0.1 to 200 pc.

2019MNRAS.485.5453S__Morlino_et_al._2012_Instance_1

As well as being directly excited from the ground state, Balmer lines (intensity, line profile, polarization and so on) are affected by the conversion of Lyman lines to Balmer lines. For example, the absorption of Ly β by a hydrogen atom results in radiative excitation from 1s to 3p, and the excited atom can emit H α by the spontaneous transition from 3p to 2s. Simultaneously, the conversion yields the 2s-state hydrogen atom, which creates the two-photon continuum by the spontaneous transition from 2s to 1s. Thus, the Ly β to H α conversion impacts the total intensity, line profile, and net polarization of H α. Moreover, an adequate density of 2s-sate atoms can further scatter H α photons. Although such fundamental physics is well known, it has not been well studied in SNR shocks. In fact, it is usually assumed that the Ly β photons are at the limits of either completely optically thick or optically thin at SNR shocks, i.e. they are completely converted to H α photons or not at all (e.g. Heng & McCray 2007; van Adelsberg et al. 2008; Morlino et al. 2012, 2013b; Shimoda et al. 2018). Contrary to this, Ghavamian et al. (2001) studied the conversion of Ly β and Ly γ to H α and H β by Monte Carlo simulations and claimed that intermediate conversion occurs. However, they and previous studies did not consider the population of 2s-state hydrogen atoms. In this paper, we provide a formulation of the radiative line transfer with the rate equation of atomic population and study the nature of Balmer line emissions from SNR shocks. In this paper we do not consider the polarization, deferring that instead to a later work. Note that as a first step, our model makes several simplifications in the treatment of the SNR shock, handling the hydrogen atoms as fluids and supposing no particles leaking back upstream (e.g. cosmic rays). Our calculation of radiative transfer is based on so-called the ray-tracing method and uses updated atomic data from the literature (e.g. Heng & Sunyaev 2008; Tseliakhovich, Hirata & Heng 2012). Moreover, we consider only hydrogen line emissions and ignore bremsstrahlung radiation, thermal emissions from the SNR ejecta, and external radiation sources. Thus, our model possibly predicts somewhat smaller population of 2s-state hydrogen atoms than would be the case in a realistic SNR shock.

2020ApJ...899..120T__Chou_et_al._2008_Instance_1

The energy dependent pulse arrival time can usually be observed in AMXPs. Soft lags are most often seen in AMXPs, where the pulse arrival times of the pulsations from softer energy bands lag compared to the ones from the harder energy bands. This phenomenon was first discovered by Cui et al. (1998) during the 1998 outburst of the SAX J1808.4–3658. The soft lag tendency can clearly be detected from 2 keV extended up to 10 keV (hereafter, the break point) for about 200 μs (∼0.08 cycles) but saturated for harder X-ray bands. Similar energy dependent pulse arrival time behavior can also be found in XTE J1751–305 (Gierliński & Poutanen 2005), XTE J1814–338 (Watts & Strohmayer 2006), HETE J1900.1–2455 (Galloway et al. 2007), and XTE J1807–294 (Chou et al. 2008) with different break point energies. However, the energy dependent pulse arrival time acts differently in IGR J00291+5934. Falanga et al. (2005) found that the soft lags can extend to the break point energy at ∼6 keV but the tendency reverses instead of saturation for the pulse of energy bands harder than the break point (hereafter hard lags) during its 2005 outburst. Similar behaviors are also observed during its 2015 outburst (Sanna et al. 2017) with a different break point energy at ∼8 keV. Such hard lags are also marginally detected in IGR J17511–3057 (Falanga et al. 2011) and IGR J17498–2921 (Falanga et al. 2012). On the other hand, the energy dependent pulse arrival times for two AMXPs are rather peculiar. The pulse arrival times seem independent of energy bands below ∼17 keV for SAX J1748.9–2021 (Patruno et al. 2009a) and only hard lags are detected in IGR J18245–2452 (De Falco et al. 2017). The newly discovered AMXP IGR J17379-3747 also shows unusual energy dependent pulse arrival times. Regular soft lags can be observed between 0.5 and 6 keV with no break point being detected; however, the phase difference between the softest and hardest bands can be as high as ∼0.3 cycles (or ∼110°; Bult et al. 2019).

2015ApJ...805....4Z__Terradas_et_al._2015_Instance_1

Solar prominences or filaments are cool, dense plasmas embedded in the million-Kelvin corona (Mackay et al. 2010). The plasmas originate from the direct injection of chromospheric materials into a pre-existing filament channel, levitation of chromospheric mass into the corona, or condensation of hot plasmas from the chromospheric evaporation due to the thermal instability (Xia et al. 2011, 2012; Keppens & Xia 2014; Zhou et al. 2014). Prominences are generally believed to be supported by the magnetic tension force of the dips in sheared arcades (Guo et al. 2010b; Terradas et al. 2015) or twisted magnetic flux ropes (MFRs; Cheng et al. 2012, 2014a; Su & van Ballegooijen 2012; Sun et al. 2012a; Zhang et al. 2012a; Xia et al. 2014a, 2014b). They can keep stable for several weeks or even months, but may get unstable after being disturbed. Large-amplitude and long-term filament oscillations before eruption have been observed by spaceborne telescopes (Chen et al. 2008; Li & Zhang 2012; Zhang et al. 2012b; Bi et al. 2014; Shen et al. 2014) and reproduced by numerical simulations (Zhang et al. 2013), which makes filament oscillation another precursor for coronal mass ejections (CMEs; Chen 2011) and the accompanying flares. When the twist of a flux rope supporting a filament exceeds the threshold value (2.5π–3.5π), it will also become unstable and erupt due to the ideal kink instability (KI; Hood & Priest 1981; Kliem et al. 2004; Török et al. 2004, 2010; Fan 2005; Srivastava et al. 2010; Aschwanden 2011; Kumar et al. 2012). However, whether the eruption of the kink-unstable flux rope is failed or ejective depends on how fast the overlying magnetic field declines with height (Török & Kliem 2005; Liu 2008; Kumar et al. 2010). When the decay rate of the background field exceeds a critical value, the flux rope loses equilibrium and erupts via the so-called torus instability (TI; Kliem & Török 2006; Amari et al. 2014; Jiang et al. 2014). On the other hand, if the confinement from the background field is strong enough, the filament will decelerate to reach the maximum height before falling back to the solar surface, which means the eruption has failed (Ji et al. 2003; Liu et al. 2009; Guo et al. 2010a; Kumar et al. 2011; Joshi et al. 2013, 2014; Song et al. 2014).

2019AandA...631A..88Y__Bohren_&_Huffman_(1998)_Instance_2

Starting from the four aforementioned materials, we consider several composition mixtures and grain structures. For the sake of comparison, we first consider compact grains of purely a-Sil, a-C, or a-C:H. Subsequently, according to Köhler et al. (2015), we consider compact grains made of two thirds a-Sil and one third a-C (Mix 1) or one third a-C:H (Mix 2), in terms of volume fractions. These allow reproduction of the mass fractions derived by Jones et al. (2013) for the diffuse ISM. The effect of porosity is tested for the Mix 1 mixture, with a porosity degree of 50% (Mix 1:50). We also evaluate theimpact of the presence of a water ice mantle on compact Mix 1 grains (Mix 1:ice). We further consider two material compositions defined in Pollack et al. (1994) based on depletion measurements: (i) 21% a-Sil and 79% a-C (Mix 3); and (ii) 8% a-Sil, 30% a-C, and 62% water ice (Mix 3:ice). The various grain compositions are summarised in Table 1. For each grain composition, we derive the absorption and scattering efficiencies Qabs and Qsca, respectively, and the asymmetry factor of the phase function g = ⟨cosθ⟩. To allow fast calculations, we make the major assumption that the grains are spherical and compute their optical properties using the Mie theory (Mie 1908; Bohren & Huffman 1983) with the Fortran 90 version of the BHMIE routine given in Bohren & Huffman (1998). For grains consisting of two or three materials, we first derive effective optical constants following the Maxwell Garnett mixing rule (Maxwell Garnett 1904; Bohren & Huffman 1998). Indeed, we assume that in Mix 1 grains, for example, carbon appears as proper inclusions in the silicate matrix rather than assuming a completely random inhomogeneous medium. Mishchenko et al. (2016a,b) performed exhaustive studies of the applicability of the Maxwell Garnett mixing rule to heterogeneous particles. These latter authors showed that this rule can provide accurate estimates of the scattering matrix and absorption cross-section of heterogeneous grains at short wavelengths (typically up to the visible for a 0.1 μm grain and to the mid-infrared(MIR) for a 10 μm grain) if twocriteria are met: both the size parameter of the inclusions and the refractive index contrast between the host material and the inclusions have to be small. Moreover, Mishchenko et al. (2016a) demonstrated that the extinction and asymmetry-parameter errors of the Maxwell Garnett mixing rule are significantly smaller than the scattering-matrix errors, remaining small enough for most typical applications and in particular the kind of applications we perform here. It is however well known that this kind of mixing rule systematically underestimates the absorption efficiency in the FIR to millimetre wavelength range, the implications of which are discussed in Sect. 3.2. We perform our computations with the emc routine of V. Ossenkopf3. For Mix 1 and Mix 2, we assume a matrix of a-Sil with inclusions of a-C or a-C:H, and for Mix 3 a matrix of a-C with inclusions of a-Sil. For grains surrounded by an ice mantle, the optical properties are derived with the core-mantle Mie theory using the BHCOAT routine given in Bohren & Huffman (1998).

2022AandA...663A..15W__Widmark_et_al._2021a_Instance_1

The dynamics of stars can be related to the gravitational potential that they inhabit via the collisionless Boltzmann equation. For systems in a steady state with certain symmetry properties (typically spherical or axisymmetric) it is possible to find solutions to the phase-space distribution of a stellar tracer population, either through distribution function modelling or via the moments of the Boltzmann equation (Kapteyn 1922; Oort 1932; Bahcall 1984a,b; Kuijken & Gilmore 1989; Crézé et al. 1998; Holmberg & Flynn 2000; Bienayme et al. 2006; Binney & Tremaine 2008; Garbari et al. 2012; Bovy & Rix 2013; Salomon et al. 2020; Guo et al. 2020; Widmark et al. 2021a). Given the relatively quiet conditions necessary to form disk galaxies, the assumption of equilibrium for near-equilibrium systems has been widely and favourably applied to the Milky Way and other galaxies (McMillan 2011; Binney & McMillan 2011). Our place in the Milky Way makes it ideal to accurately measure its gravitational potential and mass distribution, since it is the only system where we have access to full six-dimensional phase space information, from its inner regions all the way to its outermost edge (e.g. Deason et al. 2021). A precise and robust measurement of the gravitational potential is crucial for our general understanding of the Milky Way (Dehnen & Binney 1998; Klypin et al. 2002; Widrow et al. 2008; Weber & de Boer 2010; McMillan 2011, 2017; Kafle et al. 2014; Cole & Binney 2017), and also for probing its distribution of dark matter (Read 2014; Nitschai et al. 2020; Cautun et al. 2020; Li et al. 2020; de Salas & Widmark 2021). The local dark matter density is of fundamental importance for direct and indirect dark matter detection experiments (Jungman et al. 1996; Klasen et al. 2015). In a broader sense, dark matter’s gravitational signatures, studied via stellar dynamics and gravitational lensing, is one of the most competitive avenues for constraining its thus far elusive particle nature (Bertone & Tait 2018; Ferreira 2021). The Gaia satellite has been instrumental to this field, pushing the size of the astrometric sample from a few hundred thousand stars (Perryman et al. 1997) to roughly two billion (Gaia Collaboration 2018a).

2018AandA...618A.128C__Kenney_et_al._2004_Instance_1

In addition to the galaxy mergers, the ram pressure may also induce AGN activity together to star formation in cluster galaxies (e.g., Poggianti et al. 2017; Marshall et al. 2018; Ramos-Martínez et al. 2018). The ram pressure, acting on galaxies in a galaxy cluster moving through the intra-cluster medium (ICM), can strip (ram pressure stripping) gas out of the galaxy where the gas is gravitationally bound to the galaxy less strongly than the force from the ICM medium wind due to the ram pressure. A typical effect of the ram pressure stripping is the formation of long tails of stripped gas behind galaxies. A good example of this effect is the Virgo cluster, the closest rich galaxy cluster, considered a ram pressure stripping laboratory since a number of clearly ram pressure stripped galaxies have been observed (e.g., Kenney et al. 2004; Crowl et al. 2005; Chung et al. 2007). Another example of long tails of stripped gas is the Norma cluster (Abell 3627), containing a very extended multi-phase gas stripped tail of a late-type galaxy (ESO137-001 Sun et al. 2007, 2010). In the literature, there is an open debate on the role of the ram pressure stripping on the AGN activity. Observations suggest that ram-pressure stripping tends to produce a decreasing of the radiative-mode AGN activity in the centres of clusters with respect to low density regions (e.g., Ellison et al. 2011; Ehlert et al. 2014; Khabiboulline et al. 2014). This happens because the ram pressure has depleted the gas supply of the central galaxies. However, models and hydrodynamical simulations show that a moderate ram pressure is also able to compress the gas in the galaxy and trigger star formation (e.g., Fujita & Nagashima 1999; Kronberger et al. 2008; Kapferer et al. 2009; Tonnesen & Bryan 2009; Bekki 2014). This effect, produced by a low level of ram pressure, is observationally supported (e.g., Lee et al. 2017). Moderate ram pressure can also produce the removal of angular momentum from the disk gas (Tonnesen & Bryan 2009), producing gravitational instability in the galactic disk (Schulz & Struck 2001) and consequentially the gas fueling towards the central AGN.

2016MNRAS.463.4121T__Brouillet_et_al._2005_Instance_2

Molecular line ratio diagrams for NGC 4710, NGC 5866 and a variety of other galaxies. Our data for NGC 4710 and NGC 5866 are shown as filled circles and squares, respectively, while our data for the nuclear discs and inner rings are shown in blue and red, respectively (black for the intermediate region). Upper and lower limits are represented by arrows. Other lenticular galaxies are indicated by magenta filled stars (Krips et al. 2010; Crocker et al. 2012), starburst nuclei by dark green filled stars, Seyferts by brown filled stars, spiral arm GMCs by black circles with an X (see Baan et al. 2008; table 3 in Krips et al. 2010 and references therein), NGC 6946 (starburst) GMCs by black circles with a cross (Topal et al. 2014), and M31 GMCs by turquoise circles with an X (Brouillet et al. 2005). The data for NGC 1266 (a lenticular galaxy with a molecular outflow) are shown by magenta squares with a filled star (Alatalo et al. 2011). The green shaded region in panel a indicates the typical range of 12CO(1–0)/HCN(1–0) ratios in starbursts with LFIR > 1011 L⊙ (see table B2 in Baan et al. 2008). The range of R11 ratios in the nuclear disc and inner ring of NGC 5866 (this work) are indicated by respectively the blue and red horizontal lines in panel b, while the typical range in spirals with LFIR 1011 L⊙ (Paglione et al. 2001) is indicated by the pale grey shaded region. In panels a and b, Crocker et al.'s (2012) single-dish observations of NGC 4710 and NGC 5866 are shown as an open black circle and an open black square, respectively (see table 4 of Crocker et al. 2012). The HCN(1–0)/HCO+ ratios for M31 GMCs (Brouillet et al. 2005) are indicated by the turquoise shaded region in panels c and d. The green shaded region in panel d indicates the typical range of 13CO(1–0)/HCO+(1–0) ratios in the disc of M82 (starburst; Tan et al. 2011). The 12CO(1–0)/HCN(1–0) ratios in spirals (Gao & Solomon 2004a) are indicated by the dark grey shaded region in panels a, e and f, respectively. The black solid lines in a number of panels show the 1 : 1 relation and are there to guide the eye. Similarly, the black dashed lines show a ratio of 1 in panels c, d and f.

2022MNRAS.516..731B__Hattori,_Valluri_&_Vasiliev_2021_Instance_1

Now with the recent availability of high quality full 6D phase-space information for large numbers of sources, much effort has been made to decrease the uncertainties in the Milky Way mass estimate. Recent works using a tracer mass estimator with 6D phase-space information include Sohn et al. (2018, globular clusters), Watkins et al. (2019, globular clusters), and Fritz et al. (2020, satellites). The most recent work using the spherical Jeans equation by Zhai et al. (2018) is very similar to our current investigation in method and data (LAMOST K giants) although only line-of-sight velocities were included, whereas we additionally make use of proper motions from Gaia to obtain the stellar tangential velocities. Using Bayesian analysis to fit a distribution function to full 6D phase-space data (globular clusters, satellites, and halo stars) has been a recent popular choice among many works (Eadie & Jurić 2019; Posti & Helmi 2019; Vasiliev 2019; Deason et al. 2021; Correa Magnus & Vasiliev 2022; Shen et al. 2022; Slizewski et al. 2022; Wang, Hammer & Yang 2022) and a similar distribution function analysis using 5D phase-space data from Gaia (Hattori, Valluri & Vasiliev 2021). In addition to fitting the observational data with a distribution function, several works have incorporated into the fitting a comparison of the observed data with Milky Way-type galaxies from cosmological simulations (Callingham et al. 2019; Li et al. 2020). Newly discovered high velocity stars with full 6D phase-space information have been used to estimate the mass of the Milky Way (Hattori et al. 2018; Monari et al. 2018; Deason et al. 2019; Grand et al. 2019; Koppelman & Helmi 2021; Necib & Lin 2022). Vasiliev, Belokurov & Erkal (2021) and Craig et al. (2021) have estimated the Milky Way mass by fitting models for the Sagittarius and Magellanic Steams, respectively. Several recent studies have estimated the Milky Way mass using measurements of the rotation curve (de Salas et al. 2019; Eilers et al. 2019; Ablimit et al. 2020; Cautun et al. 2020; Karukes et al. 2020; Jiao et al. 2021). Other works have used 6D satellite phenomenology, characterizing simulated Milky Way-type satellite populations and comparing to the observations of satellites in the Milky Way, to estimate the mass of the Milky Way (Patel et al. 2018; Villanueva-Domingo et al. 2021; Rodriguez Wimberly et al. 2022). Zaritsky et al. (2020) apply the timing argument to distant Milky Way halo stars to derive a lower limit to the Milky Way mass.

2018ApJ...866L...1S__Pecharromán_et_al._1999_Instance_2

It was found that the complex dielectric function from Pecharromán et al. (1999) for the sample obtained by heating bayerite at 1273 K, assuming a spheroid with depolarization parameters of (0.35, 0.003), produced an opacity with 11, 20, 28, and 32 μm features, so this component was included in the models. However, with only this component, the observed 20 μm features in the residual spectra were found to be wider than those in the models. By adding the opacity of the sample obtained by heating boehmite at 1173 K, the width of the 20 μm feature could be matched. This was done using the complex dielectric function for the sample obtained by heating boehmite at 1173 K from Pecharromán et al. (1999), assuming a spheroid with depolarization parameters of (0.35, 0.035). The complex dielectric functions of the samples obtained by heating bayerite and boehmite to various temperatures (Pecharromán et al. 1999) were derived by modeling the reflectance spectra of pellets obtained by pressing powders of these materials under great pressure. This method required Pecharromán et al. (1999) to assume an effective medium theory, such that a pellet is a mixture of one of their samples with a matrix of air. Pecharromán et al. (1999) noted that heating bayerite at 500°C eliminates the XRD pattern of bayerite, and they note that at 700°C, the infrared reflectance spectrum of the boehmite sample no longer shows OH− stretching bands. This must mean that the samples obtained from heating bayerite at 1273 K and from heating boehmite at 1173 K are no longer bayerite or boehmite, respectively. XRD performed by Pecharromán et al. (1999) of the sample of bayerite prepared at 1273 K suggests only θ-alumina was present, and their infrared and NMR spectroscopy confirms this. XRD of their sample obtained from heating boehmite to 1173 K (Pecharromán et al. 1999) suggests δ-alumina to be present, though some amounts of θ-alumina and α-alumina are present, as they deduce from XRD and infrared and NMR spectroscopy.

2018ApJ...854...63O__Nakamura_et_al._2015_Instance_1

Many of the earliest simulations of core-collapse supernovae used or were concerned with a general relativistic (GR) approach (Misner & Sharp 1964; Colgate & White 1966; May & White 1966; Wilson 1971; Bruenn 1985; Burrows 1988), and rightly so since neutron stars are sufficiently compact that GR dramatically effects their equilibrium structure. While the importance of including GR gravity in simulations of core-collapse supernovae has always persisted in the literature and is in use in many current and state-of-the-art multidimensional, core-collapse supernova calculations (Marek & Janka 2009; Kuroda et al. 2012; Müller et al. 2012a; Bruenn et al. 2013, 2016; Ott et al. 2013; Lentz et al. 2015; Skinner et al. 2016; Burrows et al. 2018), many modern simulations have used a purely Newtonian approximation for gravity (Takiwaki et al. 2014; Couch & O’Connor 2014; Handy et al. 2014; Couch & Ott 2015; Dolence et al. 2015; Nakamura et al. 2015; Pan et al. 2016; Suwa et al. 2016). Liebendörfer et al. (2001) extensively compared GR gravity and Newtonian gravity in spherical symmetry with a full Boltzmann neutrino transport solver. While their baseline simulations in both prescriptions of gravity fail to explode in 1D, their conclusion is that, overall, GR is helpful for the development of the core-collapse supernova explosion. This conclusion comes out of serendipitous simulations where incorrect nucleon isoenergetic scattering cross sections were used. In these simulations, when GR gravity was used, the simulation predicted an explosion, but when Newtonian gravity was used, the simulations failed to achieve explosions. Bruenn et al. (2001), Buras et al. (2006b), and Lentz et al. (2012) also compared Newtonian and GR simulations in spherical symmetry with energy-dependent neutrino transport. Like Liebendörfer et al. (2001), they observe higher neutrino luminosities and energies but do not extensively study the differences, in part because both simulations still fail to explode owing to the 1D nature of the simulations. Kuroda et al. (2012) examined the difference between special relativistic hydrodynamics and GR hydrodynamics in both 1D and 3D core-collapse simulations using approximate neutrino transport (a gray M1 scheme). However, while the 3D GR simulations show signs of increased susceptibility to explosion, the simulated time was not long enough to observe an explosion. Müller et al. (2012a) also investigated the influence of Newtonian gravity, GR gravity, and GR effective potential gravity in 2D core-collapse simulations using a variable-Eddington-factor, two-moment, energy-dependent neutrino transport scheme and the ray-by-ray+ approximation (where the neutrino transport is done along radial rays assuming spherical symmetry and with minimal coupling between neighboring rays). For the classic 15 M⊙ model from Woosley & Weaver (1995), Müller et al. (2012a) find a late and asymmetric explosion when using fully GR gravity, but not with Newtonian gravity, GR effective potential gravity, or reduced set neutrino opacities. This was, and still is, the most direct evidence that GR aids in the explosion mechanism. It is important to validate the hypothesis that GR gravity does indeed lead to more favorable conditions for explosion in modern-day simulations, with updated progenitor models, and loosening the assumption of spherically symmetric.

2017MNRAS.464..635M__Ceverino_et_al._2012_Instance_1

The basic idea, summarized in Dekel et al. (2009), is that during VDI, the high surface density of gas and ‘cold’ young stars, Σ, drives the Toomre Q parameter below unity, Q ∼ σΩ/(πGΣ) ≲ 1, where σ is the 1D velocity dispersion and Ω is the angular frequency, a proxy to the epicyclic frequency κ, which is related to the potential well (Toomre 1964). It has been established that under such conditions, the disc will fragment and produce large star-forming clumps. This has been shown using idealized simulations of isolated galaxies (Noguchi 1999; Gammie 2001; Immeli et al. 2004a,b; Bournaud, Elmegreen & Elmegreen 2007; Elmegreen, Bournaud & Elmegreen 2008; Bournaud & Elmegreen 2009; Hopkins et al. 2012b), as well as cosmological simulations (Agertz, Teyssier & Moore 2009; Ceverino et al. 2010; Ceverino et al. 2012; Genel et al. 2012; Mandelker et al. 2014; Oklopcic et al. 2016). The ratio of clump mass to the mass of the cold disc scales as Mc/Md ∝ δ2, where δ = Md/Mtot is the ratio of the cold disc mass to the total mass within the disc radius, which includes the bulge and dark matter halo (e.g. Dekel et al. 2009). This leads to much larger clumps at z ∼ 2 than the low-redshift giant molecular clouds (GMCs). Gravitational interactions in the perturbed disc drive turbulence causing the disc to self-regulate in a marginally stable state with Q ≲ 1 (Dekel et al. 2009; Ceverino et al. 2010; Krumholz & Burkert 2010; Cacciato, Dekel & Genel 2012; Forbes, Krumholz & Burkert 2012; Forbes et al. 2014) that can last for more than a Gyr so long as the accretion is not interrupted. Some recent works have called into question the validity of linear Toomre analysis in the context of these highly non-linear galaxies (Behrendt, Burkert & Schartmann 2015; Tamburello et al. 2015; Inoue et al. 2016) and others have suggested alternate fragmentation mechanisms related to turbulence (e.g. Hopkins 2013). However, since clump formation is largely determined by the balance between self-gravity, turbulent pressure and the centrifugal force, the largest clumps are always roughly at the Toomre scale. Larger clumps would be disrupted due to the shear and/or tidal forces within the disc, or would not collapse in the first place due to the centrifugal force. Therefore, regardless of the full validity of linear Toomre analysis, it is plausible that the Toomre Q parameter can serve as a crude criterion for instability, possibly with a critical value that is larger than unity.

2021MNRAS.504.1473L__Muñoz,_Miranda_&_Lai_2019_Instance_1

Large numbers of works have extensively studied the binary-disk system in the Newtonian regime with analytic methods (Paczynski 1977; Papaloizou & Pringle 1977; Kocsis, Haiman & Loeb 2012a, b) and hydrodynamical simulations (Lin & Papaloizou 1979; Artymowicz & Lubow 1994; MacFadyen & Milosavljević 2008; Mayama et al. 2010; de Val-Borro et al. 2011; Shi et al. 2012; D’Orazio et al. 2013; Farris et al. 2014; Ju, Stone & Zhu 2016; Muñoz & Lai 2016; Nelson A. & Marzari 2016; Miranda, Muñoz & Lai 2017; Tang, MacFadyen & Haiman 2017; Tang, Haiman & MacFadyen 2018; Muñoz, Miranda & Lai 2019). Simulations within the Newtonian regime during the inspiral of the binary black hole have also been investigated (Baruteau, Ramirez-Ruiz & Masset 2012; Farris et al. 2015; Cerioli, Lodato & Price 2016; Tang et al. 2018). Two-dimensional simulations by Noble et al. (2012) and three-dimensional ones by Zilhão et al. (2015) conducted the fully relativistic magnetohydrodynamic evolution of a circumbinary disk surrounding two non-spinning black holes with equal mass using the near zone metric. Later on, the fully relativistic magnetohydrodynamic simulations of SMBBH–disk interaction with both the near zone metric and the inner zone metric have been performed (Bowen et al. 2017, 2018, 2019; d’Ascoli et al. 2018) and these simulations are limited to several binary orbits. In particular, Bowen et al. (2017) showed that the gravitational potential of the binary black hole in the post-Newtonian (PN) regime is shallower than that in the Newtonian regime, and that such shallow potential in the PN regime has significant effects on the dynamics of the mini-disk around each SMBH. Simulations of SMBBH–disk interaction with full numerical relativity are so computationally expensive that the evolution of disk around SMBBH is constrained within the stage near merger (Farris et al. 2012; Giacomazzo 2012). In this work, we present hydrodynamical simulations of accretion of equal mass SMBBH by using PN hydrodynamics in which the near zone metric of SMBBH is used.

2021ApJ...910...82L__Schrijver_2001_Instance_1

Similar results of the on-disk condensations are obtained to those of the on-disk quiescent coronal rain in AR closed loops in Hα (see Section 3.2). If we considered the AIA 304 Å observations alone, the on-disk condensation, and hence coronal rain events we report here would resemble those occurring in magnetically closed field lines (Antolin & Rouppe van der Voort 2012; Antolin et al. 2012; Ahn et al. 2014), which are generally interpreted as a manifestation of the heating-condensation cycles due to thermal nonequilibrium (Schrijver 2001; Müller et al. 2003, 2004; Antolin 2020). However, combining the observations of SDO and STEREO A and B at different viewing angles, we find that the on-disk coronal rain in this study corresponds to the downflows of condensations facilitated by reconnection between open and closed structures. Similarly, if we analyze only the on-disk observations as recorded by the AIA as shown in Figure 7, it appears that the structures gradually brighten first in the 171 Å channel and then in the 131 Å channel. Such sequential appearance of coronal structures in the AIA channels sensitive to emission from progressively cooler plasma could be interpreted as a case of loop cooling after nanoflare heating (e.g., Viall & Klimchuk 2012; Li et al. 2015), for instance. In contrast, by employing observations from multiple vantage points, we show that the on-disk structure brightening in the AIA images is actually due to cooling and condensation of plasma facilitated by reconnection in the high corona that is not necessarily regulated by any heating mechanism. To search for the origination of structures harboring on-disk flow, e.g., coronal rain, in the transition region or chromospheric lines, observations from different viewing angles are thus quite important. If there is no observation from other viewing angles, evolution of the associated structures, that may be difficult to observe on the disk, in multiwavelength images during the cooling and condensation process needs to be examined because the condensation facilitated by reconnection cools down from ∼0.9 MK, the characteristic temperature of the 171 Å channel, rather than from the higher temperatures.

2022MNRAS.514.5178D__Ruderman_&_Roberts_2002_Instance_1

There are several natural scenarios for the initial flare-caused impulsive perturbation of an active region to develop into a quasi-periodic response, which includes the effects of resonance in closed coronal plasma structures (acting as resonators), dispersion of a wave-guide, and non-linearity/self-organization (McLaughlin et al. 2018; Zimovets et al. 2021). The observed doubling of the QPP and shorter lifetime of shorter-period QPP modes strongly indicate in favour of resonant dynamics of magnetohydrodynamic waves in a coronal loop, for which the oscillation period is prescribed by the local plasma conditions (i.e. the Alfvén and sound speeds) and the loop length (Nakariakov et al. 2021; Wang et al. 2021). More specifically, fast- and slow-mode magnetoacoustic waves in coronal plasma structures are well-known to be subject to a frequency-dependent damping by e.g. resonant absorption and thermal conduction (e.g. Ofman & Aschwanden 2002; Ruderman & Roberts 2002; De Moortel & Hood 2003). Likewise, excitation of even and/or uneven parallel harmonics of fast- and slow-mode standing waves in a plasma loop is known to be highly sensitive to the location of the initial perturbation along the loop. For example, Tsiklauri et al. (2004) and Selwa, Murawski & Solanki (2005) theoretically demonstrated that the second parallel harmonic of a slow standing wave can be effectively excited if the impulsive energy release occurs near the apex of the loop. Observations of higher harmonics of fast-mode oscillations in coronal loops were also shown to be subject to the excitation mechanism and location of the initial displacement of the loop (e.g. De Moortel & Brady 2007; Srivastava et al. 2008; Yuan & Van Doorsselaere 2016; Pascoe et al. 2017; Duckenfield et al. 2019). Thus, taking cs = 600 km s−1 for the sound speed in a hot flaring loop, the Alfvén speed cA = 1200 km s−1 (e.g. Mathioudakis et al. 2006), and treating the observed QPP periods as characteristic acoustic or Alfvén transit times along the loop, we can estimate the corresponding loop lengths as 80–160 Mm for the 2018 flare and 50–100 Mm for the 2019 flare, i.e. 0.2–0.7 R⋆. These estimations agree with a typical length of solar coronal loops, and, are approximately an order of magnitude larger than those derived by Mathioudakis et al. (2006). However, the above authors ruled out these small loop lengths suggesting instead that they may be due to a fast-MHD wave, with the modulation of the emission being due to the magnetic field. The present observation in the doubling of the QPP in both YZ CMi flares presents rare and compelling evidence for the presence of compact plasma loops in a stellar corona.

2018AandA...615A..77L__Tacconi_et_al._2010_Instance_1

A different approach is to count the amount of baryonic material within the proto-cluster bounds associated with the member galaxies and attempt to relate that back to the overall mass of the structure, an approach which has been employed successfully at low redshift when the galactic baryonic content of cluster member galaxies is dominated by stars (Andreon 2012). The approach we take here is similar to that of Lemaux et al. (2014a). Briefly, the total amount of stellar matter of the zspec members is counted and a completeness correction is made to this value for galaxies at stellar masses $\log(\mathcal{M}_{\ast}/M_{\odot})\ge 9.5$log(M∗/M⊙)≥9.5 (see Sect. 4.2.1 for the reasoning behind this cut) based on the number of zphot members and non-members without secure spectral redshifts within the bounds of the proto-cluster and the likelihood of their being true members. An additional correction is made to correct for galaxies in the stellar mass range $8.0 < \log(\mathcal{M}_{\ast}/M_{\odot})< 9.5$8.0log(M∗/M⊙)9.5 by integrating the stellar mass function of Davidzon et al. (2017) appropriate for this redshift. Here we additionally make the assumption that stellar mass comprises 50% of the baryonic content of galaxies by mass at these redshifts, a value broadly consistent with the few measurements made at or near these redshifts (e.g., Tacconi et al. 2010; Capak et al. 2011b; Schinnerer et al. 2016; Scoville et al. 2016). We assume for the purposes of this calculation that the proto-cluster is a closed system, with all gas being converted to stars by z = 0 and that the completeness-corrected galaxy population which lies within Rproj ≤ 3 Mpc at z ~ 4.57 comprises the entirety of the galaxy population which will eventually be contained within the cluster virial radius at z = 0. The latter assumption is broadly consistent with simulations (Muldrew et al. 2015) to ~10% accuracy, a factor which we account for in the calculation below. Any total to stellar mass conversion then provides a z = 0 total mass, which we de-evolve to z ~ 4.57 using the correction factors of Muldrew et al. (2015) appropriate for z ~ 4.57 (0.20 ± 0.03), a correctionwhich is appropriate for descendents of all masses. Into this formalism we input the resulting completeness-corrected baryonic content of $\log(\mathrm{\Sigma}\mathcal{M}_{\ast}/M_{\odot})=12.39^{0.05}_{-0.07}$log(ΣM∗/M⊙)=12.39−0.07+0.05 to the r200 stellar mass to M500 total mass relation of Andreon (2012) and scale the resulting M500 to the virial radius (Rvir = 0.33 Mpc) using the methods presented in Lemaux et al. (2014a) giving: (2) \begin{equation*} \log(\mathcal{M}/\mathcal{M}_{\odot})_{z=4.57, \, \mathrm{\Sigma}\mathcal{M}_{\ast, corr}} = 13.31^{0.23}_{-0.27}.\end{equation*}log(M/M⊙)z=4.57, ΣM∗,corr=13.31−0.27+0.23.

2020ApJ...904..185O__Takakuwa_et_al._2014_Instance_1

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

2019ApJ...871..191O__Vaucouleurs_et_al._1991_Instance_1

NGC 4418 is one of the closest and best-studied galaxies hosting CONs. It is an LIRG with its 8–1000 μm infrared luminosity (LIR) of 1.4 × 1011 L (Sanders et al. 2003)4 4 With our assumed distance, the luminosity is larger than the threshold for the LIRG classification of LIR = 1 × 1011 L (Sanders & Mirabel 1996). We note, however, that NGC 4418 is sometimes classified as a non-LIRG if one adopts smaller distance to the galaxy. For example, with its recession velocity (cz) and an assumed Hubble constant of H0 = 75 km s−1 Mpc−1, the distance is estimated to be 28.32 Mpc and LIR = 9. 4 × 1010 L. at a distance of 34 Mpc (1″ = 165 pc; Sakamoto et al. 2013).5 5 Sakamoto et al. (2013) adopted the distance from Sanders et al. (2003), in which distance is calculated with cz using the cosmic attractor model outlined in Appendix A of Mould et al. 2000, using H0 = 75 km s−1 Mpc−1 and adopting a flat cosmology in which ΩM = 0.3 and Ωλ = 0.7. We adopt this distance for consistency with recent closely related studies of this galaxy (Aalto et al. 2012; Costagliola et al. 2013; Varenius et al. 2014). In spite of its huge infrared luminosity, the host galaxy is classified from the optical morphology as an ordinary Sa-type galaxy ([R’]SAB[s]a; de Vaucouleurs et al. 1991) with moderate inclination (i = 62°; taken from Sakamoto et al. 2013 for consistency; based on Jarrett et al. 2000). It has a neighbor galaxy about 32 kpc (32) away (VV 655 = MCG+00- 32-013 = SDSS J122704.47-005420.6; km s−1; Evans et al. 2003; Varenius et al. 2017). Varenius et al. (2017) found a bridge of H i 21 cm emission connecting these two galaxies and argued that their strong tidal interaction occurred about 190 Myr ago. The optical nuclear emission line spectrum of NGC 4418 is classified as LINER (Armus et al. 1989; Shi & Gu 2005) or Seyfert 2 (Baan et al. 1998), but no direct signature of AGNs such as very broad permitted lines is known (see also Lehnert & Heckman 1995). NGC 4418 is deficient of X-ray emission for its infrared luminosity, and its interpretation has been a matter of controversy. Maiolino et al. (2003) tentatively identified, with low statistics, a Compton-thick (reflection-dominated) AGN on the basis of its small photon index (or flat X-ray spectrum; , where , E is the photon energy, and N(E) is the photon number density). On the other hand, Lehmer et al. (2010) found the opposite (soft) spectral index ( ), which is even softer than the one of Compton-thin AGNs (Γ ≃ 1.7; Mushotzky et al. 1993). We note that both analyses are based on the Chandra AICS-S data, and Lehmer et al. (2010) added ≃30% more integration onto the earlier data used by Maiolino et al. (2003).

2017ApJ...849..149S__Lee_2004_Instance_1

There is a similarity between the ISM and the young stellar structures identified here. First, similar to the young stellar structures, the ISM also displays irregular morphologies and contains large amounts of substructures (clouds, clumps, cores, filaments, etc.) that are hierarchically organized (Rosolowsky et al. 2008). Second, the ISM substructures also follow a power-law size distribution, which indicates a scale-free behavior (e.g., Elmegreen & Falgarone 1996). The third aspect of their similarity comes from the fractal dimension. The projected fractal dimension of the ISM has been investigated based on the perimeter–area relation of its projected boundaries. Typical values are close to D2 = 1.4–1.5 (e.g., Beech 1987; Scalo 1990; Falgarone et al. 1991; Vogelaar & Wakker 1994; Lee 2004; Lee et al. 2016; although smaller values have also been reported by, e.g., Dickman et al. 1990; Hetem & Lepine 1993), which are consistent with the fractal dimension as derived for the young stellar structures. Using power-spectrum analysis, Stanimirovic et al. (1999, 2000) reported D2 = 1.4 or 1.5 for the ISM in the SMC, also close to that of the young stellar structures. On the other hand, it is possible to measure the volume fractal dimension of the ISM, since clouds along the line of sight can be distinguished by their velocities. For instance, Elmegreen & Falgarone (1996) reported D3 = 2.3 ± 0.3 based on the size distribution for a number of Galactic molecular clouds, and Roman-Duval et al. (2010) found D3 = 2.36 ± 0.04 using the mass–size relation. If the relation D3 = D2 + 1 holds for the ISM, these results would not be far from the fractal dimension of the young stellar structures. Unfortunately, there is no reported measurement of the fractal dimension of the ISM in the LMC bar region. However, it has been suggested that, despite a few exceptions, the fractal dimension is invariant from cloud to cloud, regardless of their nature as star-forming or quiescent, whether gravitationally bound or unbound (e.g., Williams et al. 2000).

2017MNRAS.470..612F__Feng_etal._2016_Instance_1

The millimetre bump in M87 as recently observed by the Atacama Large Millimeter/submillimeter Array can be naturally modelled by the synchrotron emission of the thermal electrons in the ADAF, which is different from the prediction of the jet model. Therefore, it provides an opportunity to explore the accretion process near the BH horizon. In particular, Feng etal. (2016) and Li etal. (2016) both found that the rotation measure predicted from the ADAF is roughly consistent with the observational values. It is still difficult to constrain the BH spin parameter from the modelling of the SED of M87 due to some degeneracy in model parameters (wind parameter, s, magnetic parameter ; Feng etal. 2016). The spin parameter can be better constrained from the jet model if the relativistic jet is indeed powered by the rotating BHs as suggested by MHD simulations and some observations. We find that the dimensionless BH spin parameter should be larger than 0.96 for the lower limit of jet power derived from the X-ray cavities (e.g. Rafferty et al. 2006; Russell etal. 2013b). In this work, we adopt several typical values of parameters (e.g. 0.1, 0.3 and 0.5). The larger value of will lead to a lower accretion rate near the horizon to explain the observed millimetre bump, and the BHs need to rotate faster to reproduce the observed jet power. The peak of synchrotron emission from the thermal electrons of ADAF will move to the submillimetre waveband if is too small, which is different from the observed millimetre bump. We adopt the equipartition case of 0.5 in our calculations, where magnetic energy will become dominant if the BH is fast spinning, considering the possible amplification of the magnetic field by the frame dragging effect. For the weaker magnetic case (e.g. 0.5), the BH needs to rotate faster to explain the observed SED and jet power. We find that our results are not sensitive to the viscosity parameter . Therefore, we suggest that the BH should be fast rotating in M87 even after considering the possible uncertainties.