adsabs/FOCAL huggingface dataset:
The H α studies of Umeda et al. (2004) and Stroe et al. (2014a, 2015) are tracing instantaneous (averaged over 10 Myr) SF and little is known about SF on longer time-scales and the reservoir of gas that would enable future SF. An excellent test case for studying the gas content of galaxies within merging clusters with shocks is CIZA J2242.8+5301 (Kocevski et al. 2007). For this particular cluster unfortunately, its location in the Galactic plane, prohibits studies of the rest-frame UV or FIR tracing SF on longer time-scales, as the emission is dominated by Milky Way dust. However, the rich multiwavelength data available for the cluster give us an unprecedented detailed view on the interaction of their shock systems with the member galaxies. CIZA J2242.8+5301 is an extremely massive (M200 ∼ 2 × 1015 M⊙; Dawson et al. 2015; Jee et al. 2015) and X-ray disturbed cluster (Akamatsu & Kawahara 2013; Ogrean et al. 2013, 2014) which most likely resulted from a head-on collision of two, equal-mass systems (van Weeren et al. 2011; Dawson et al. 2015). The cluster merger induced relatively strong shocks, which travelled through the ICM, accelerated particles to produce relics towards the north and south of the cluster (van Weeren et al. 2010; Stroe et al. 2013). There is evidence for a few additional smaller shock fronts throughout the cluster volume (Stroe et al. 2013; Ogrean et al. 2014). Of particular interest is the northern relic, which earned the cluster the nickname ‘Sausage’. The relic, tracing a shock of Mach number M ∼ 3 (Stroe et al. 2014c), is detected over a spatial extent of ∼1.5 Mpc in length and up to ∼150 kpc in width and over a wide radio frequency range (150 MHz–16 GHz; Stroe et al. 2013, 2014b). There is evidence that the merger and the shocks shape the evolution of cluster galaxies. The radio jets are bent into a head–tail morphology aligned with the merger axis of the cluster. This is probably ram pressure caused by the relative motion of galaxies with respect to the ICM (Stroe et al. 2013). The cluster was also found to host a high fraction of H α emitting galaxies (Stroe et al. 2014a, 2015). The cluster galaxies not only exhibit increased SF and AGN activity compared to their field counterparts, but are also more massive, more metal rich and show evidence for outflows likely driven by SNe (Sobral et al. 2015). Stroe et al. (2015) and Sobral et al. (2015) suggest that these relative massive galaxies (stellar masses of up to ∼1010.0–10.7 M⊙) retained the metal-rich gas, which was triggered to collapse into dense star-forming clouds by the passage of the shocks, travelling at speeds up to ∼2500 km s−1 (Stroe et al. 2014c), in line with simulations by Roediger et al. (2014).
Citation: Stroe et al. 2013
Citation function: Motivation; Motivation
Star formation and supermassive resblack hole (SMBH) growth are two important processes in galaxies that influence their evolution throughout cosmic history. However, we do not yet understand why the global rates of star formation (e.g. Hopkins & Beacom 2006; Madau & Dickinson 2014; Driver et al. 2018) and SMBH growth (e.g. Ueda et al. 2003; Shankar, Weinberg & Miralda-Escudé 2009) both peaked at z ≈ 2, and then declined by an order magnitude to this epoch. It is clear that a ready supply of cold (Tk ≪ 104 K) gas is important; in the nearby Universe the surface densities of star formation and neutral gas, particularly the molecular component, are strongly correlated (e.g. Schmidt 1959; Kennicutt 1998; Bigiel et al. 2008), and likewise radiatively efficient active galactic nuclei (AGNs) are predominantly hosted by star-forming galaxies with a central young stellar population and therefore ample cold gas reservoirs (e.g. Kauffmann et al. 2003, 2007; Kauffmann & Heckman 2009; LaMassa et al. 2013; Ellison et al. 2019). Determining how the neutral interstellar medium in galaxies has evolved over the history of the Universe is therefore a key component in understanding their evolution. Much of our knowledge of the global content of neutral gas in galaxies comes from observing hydrogen gas, the most common element in the Universe. In its neutral atomic (H i) phase, hydrogen is readily detectable in nearby galaxies via 21-cm emission at radio wavelengths (see Giovanelli & Haynes 2016 for a review) or, at cosmological distances, through Lyman α (n = 1–2) absorption in the ultraviolet and visible bands (see Wolfe, Gawiser & Prochaska 2005). The total H i mass density shows comparatively less evolution over cosmological time-scales than that of star formation, decreasing by at most two-fold since z ≈ 2 (e.g. Zwaan et al. 2005; Martin et al. 2010; Braun 2012; Noterdaeme et al. 2012; Zafar et al. 2013; Crighton et al. 2015; Sánchez-Ramírez et al. 2016; Bird, Garnett & Ho 2017; Rhee et al. 2018), suggesting that much of the neutral gas content of galaxies is replenished over these time-scales.
Citation: Ellison et al. 2019
Citation function: Motivation; Motivation; Motivation
The observation of massive neutron stars Demorest et al. (2010), Antoniadis et al. (2013) indicates that the EoS of nuclear matter must be very stiff in the regime of high densities and low temperatures. The degree of stiffness in the nuclear matter EoS is directly related to the repulsive interaction among particles at high densities, as well as to the particle content in the core of the stars. In particular, it has been extensively discussed in the literature whether exotic degrees of freedom might populate the core of neutron stars. On the one hand, it is more energetically favorable for the system to populate new degrees of freedom, such as hyperons (Dexheimer & Schramm 2008; Ishizuka et al. 2008; Bednarek et al. 2012; Fukukawa et al. 2015; Gomes et al. 2015; Maslov et al. 2015; Oertel et al. 2015; Lonardoni et al. 2015, 2016); Biswal et al. 2016; Burgio & Zappalà 2016; Chatterjee & Vidana 2016; Mishra et al. 2016; Vidaña 2016; Yamamoto et al. 2016; Tolos et al. 2017); Torres et al. 2017), delta isobars (Fong et al. 2010;Schurhoff et al. 2010; Drago et al. 2014; 2016; Cai et al. 2015; Zhu et al. 2016), and meson condensates (Ellis et al. 1995; Menezes et al. 2005; Takahashi 2007; Ohnishi et al. 2009; Alford et al. 2010; Fernandez et al. 2010; Mesquita et al. 2010; Mishra et al. 2010; Lim et al. 2014; Muto et al. 2015), in order to lower its Fermi energy (starting at about two times the saturation density). On the other hand, the EoS softening due to the appearance of exotica might turn some nuclear models incompatible with observational data, in particular with the recently measured massive neutron stars. One possible way to overcome this puzzle is the introduction of an extra repulsion in the YY interaction Schaffner & Mishustin (1996), Bombaci (2016), allowing models with hyperons to be able to reproduce massive stars (Dexheimer & Schramm 2008; Bednarek et al. 2012; Weissenborn et al. 2012; Banik et al. 2014; Bhowmick et al. 2014; Gusakov et al. 2014; Lopes & Menezes 2014; van Dalen et al. 2014; Yamamoto et al. 2014; Gomes et al. 2015). Another possible solution is the introduction of a deconfinement phase transition at high densities Bombaci (2016), with a stiff EoS for quark matter, usually associated with quark vector interactions (see Klähn et al. 2013 and references therein).
Citation: Dexheimer & Schramm 2008; Dexheimer & Schramm 2008
Citation function: Compare/Contrast; Compare/Contrast; Compare/Contrast
Our models for the density distribution in the thin and thick stellar disks of the Galaxy are based on the structural disk parameters presented by PJL. These authors performed a star counts model of the Galaxy using near-infrared data of the 2MASS survey (Skrutskie et al. 2006) with lines of sight covering the entire sky and including the Galactic plane. The authors explored the parameter space and estimated its optimal values with statistical methods such as the Markov chain Monte Carlo (MCMC; Gilks et al. (1996)) and the nested sampling (NS) algorithm (Skilling 2004). Using a modified exponential law, PJL modelled the radial profile of the density of each subcomponent of the stellar disk based on the Galactic model of Lépine & Leroy (2000). Such profile is equivalent to the Freeman Type II disk brightness profile, which contains a depletion in the centre with respect to a pure exponential law (Freeman 1970; Kormendy 1977). The stellar surface densities Σd★ for the thin and thick disks can then be written as (1)\begin{equation} \label{eq:sigma_thin_thick} \Sigma_{\mathrm{d}_{\bigstar,\,i}}(R)=\Sigma_{0\mathrm{d}_{\bigstar,\,i}}\,\exp\left[-\,\frac{(R-R_{0})}{R_{\mathrm{d}_{\,i}}}-R_{\mathrm{ch}_{\,i}}\left(\frac{1}{R}-\frac{1}{R_{0}}\right)\right], \end{equation}Σd★, i(R)=Σ0d★, i exp− (R−R0)Rd i−Rch i1R−1R0,where Σ0d★ corresponds to the local disk stellar surface density (at R = R0), Rd is the radial scale length, and Rch is the radial length of the “central hole” in the density of each stellar disk i subcomponent (i = thin, thick). The hypothesis that the Galactic disk is hollow in its centre has been justified by some models that use observational data at infrared bands to describe the inner structure of the Galaxy (e.g. Freudenreich 1998; Lépine & Leroy 2000; López-Corredoira et al. 2004; Picaud & Robin 2004). In the particular case of the PJL model, only the thin disk needs a density depression in its inner part; in contrast, the thick disk can be described by a simple radial exponential decay, i.e.  Rch thick = 0.
Citation: Kormendy 1977
Citation function: Similarities
The Bayesian approach is indeed robust and optimal, within the context mentioned above. It focuses on the reconstruction of the LSS within the framework of the standard model of cosmology and for a given data base. However, most previous studies have not addressed the question how consistent is the assumed cosmological model with the observed data. This is not a trivial issue – the model needs to agree with the data so as to provide a solid foundation for the WF/CRs construction. Ideally, one should have started with establishing the agreement of the model with the data and only then reconstruct the LSS in the manner described above. However, history does not always proceeds in a linear fashion. The aim of the paper is to amend that situation and establish the likelihood of peculiar velocities data bases given the standard model of cosmology. The relevant methodology is straightforward and well established. One needs to calculate the likelihood function of the data given the model – namely the probability of the occurrence of the data within the framework of the assumed model (Jaffe & Kaiser 1995; Zaroubi et al. 1995; Hoffman 2001; Press et al. 2007). The likelihood function establishes the goodness-of-fit (GoF) of the data by the model. In the cosmological case and under the assumption of the linear regime, where the velocity field constitutes a random Gaussian vector field and the observational errors are normally distributed, the likelihood analysis amounts to calculating a χ2 statistics. This approach was indeed applied to velocity data bases (Jaffe & Kaiser 1995; Zaroubi et al. 1997, 2001). The application of the likelihood analysis to actual velocity data bases suffers however from one major drawback. The gravitational dynamics of structure formation induces non-linear contributions to the velocities of galaxies. These non-linear corrections render the parameter estimation and GoF analysis to be rather uncertain. The remedy to the problem involves the filtering of small scales to give linearized data. The likelihood analysis can then be safely applied to the linearized data. Here, we suggest such a small-scales filtering procedure and study the extent by which Cosmicflows-2 (CF2; Tully et al. 2013) is compatible with the Λ cold dark matter (ΛCDM) standard model of cosmology.
Citation: Jaffe & Kaiser 1995
Citation function: Background
Galactic winds have been ubiquitously observed in galaxies at both low and high redshifts, and they are critical to galaxy formation and evolution. Simulations calibrated to match these observations predict that a large amount of galactic material is ejected as a wind before reaccreting to either form stars or be ejected once again (Oppenheimer et al. 2010; Anglés-Alcázar et al. 2017). Current cosmological hydrodynamic simulations of galaxy formation employ a variety of subgrid models (e.g. Springel & Hernquist 2003; Oppenheimer & Davé 2006; Stinson et al. 2006; Dalla Vecchia & Schaye 2008; Agertz et al. 2013; Schaye et al. 2015; Davé, Thompson & Hopkins 2016; Tremmel et al. 2017; Pillepich et al. 2018; Davé et al. 2019; Huang et al. 2020a) that artificially launch galactic winds, but the results are sensitive to numerical resolution and the exact subgrid model employed (Huang et al. 2019, 2020a). Simulations without these subgrid wind models (e.g. Hopkins et al. 2018; Kim & Ostriker 2015; Martizzi et al. 2016) allow winds to occur ‘naturally’, but these simulations may not resolve the scales necessary to resolve the important known physical processes (Scannapieco & Brüggen 2015; Brüggen & Scannapieco 2016; Schneider & Robertson 2017; McCourt et al. 2018; Huang et al. 2020b). Hence, modelling galactic winds accurately remains a theoretical challenge for even the most refined high-resolution simulations of galaxies (see Naab & Ostriker 2017, for a review). Even if one were able to accurately model the formation of galactic winds, the subsequent propagation in galactic haloes depends on a complicated interplay of many physical processes that occur on a wide range of physical scales that cannot be simultaneously resolved in a single simulation. For example, to robustly model the propagation and disintegration of moving clouds in various situations requires cloud-crushing simulations with at least sub-parsec scale resolution (Schneider & Robertson 2017; McCourt et al. 2018), which is orders of magnitudes below the resolution limits of cosmological simulations. Furthermore, most cosmological hydrodynamic simulations concentrate their resolution in the dense, star-forming regions of galaxies and thus have lower resolution in the circumgalactic medium (CGM, but see Hummels et al. 2019; Mandelker et al. 2019; Peeples et al. 2019; Suresh et al. 2019; van de Voort et al. 2019). To date, cosmological simulations do not include physically motivated subgrid models for galactic wind evolution, which are required to capture these small-scale physical processes.
Citation: Huang et al.; 2020a
Citation function: Background
Some studies use HIPPARCOS or Gaia data to determine the evolutionary status of field LiRG and show that these objects tend to accumulate close to the RGB bump, the clump, and the early-AGB (e.g. Charbonnel & Balachandran 2000; Kumar et al. 2011; Smiljanic et al. 2018; Deepak 2019), which is in agreement with open cluster studies (e.g. Delgado Mena et al. 2016). Other works report, however, that LiRG can be randomly located in the HRD (Jasniewicz et al. 1999; Smith et al. 1999; Monaco et al. 2011; Lebzelter et al. 2012; Martell & Shetrone 2013; Casey et al. 2016). The distinction is crucial to understanding the processes that may provide an explanation for the phenomenon, such as fresh Li production by internal mixing processes (Sackmann & Boothroyd 1999; Palacios et al. 2001; Guandalini et al. 2009; Strassmeier et al. 2015; Cassisi et al. 2016), prompt mass loss events (de La Reza et al. 1996, 1997), Li accretion during engulfment of planets or planetesimals (Alexander 1967; Siess & Livio 1999; Carlberg et al. 2010; Aguilera-Gómez et al. 2016a,b; Delgado Mena et al. 2016), tidal interactions between binary stars (Casey et al. 2019), or a combination of these mechanisms (Denissenkov & Weiss 2000; Denissenkov & Herwig 2004). However, since the evolution tracks of evolved stars all converge to the same area of the CMD, the definitive determination of the actual evolution status of LiRG requires asteroseismology to probe their internal structure and disentangle RGB from clump stars. As of today, very few LiRG have been observed with CoRoT and Kepler. The majority seems to be located in the core-He burning clump (Silva Aguirre et al. 2014; Bharat Kumar et al. 2018; Casey et al. 2016; Smiljanic et al. 2018; Singh et al. 2019), with the others being at the RGB bump or higher on the first ascent giant branch (Jofré et al. 2015; Casey et al. 2019). In a recent study using LAMOST spectra to derive both the Li abundance and asteroseismic classification, Casey et al. (2019) showed that ∼80% of their large sample of low-mass LiRG (2330 objects) probably have helium burning cores. They find that LiRG are more frequent at higher metallicity.
Citation: Carlberg et al. 2010
Citation function: Motivation; Motivation
Age–velocity dispersion relations have been found in many resolved (Nordström et al. 2004; Grieves et al. 2018) and simulated (Martig, Minchev & Flynn 2014) studies. They primarily conclude that stars born earlier have a higher velocity dispersion compared to those formed later. The underlying physical cause of this relation, however, has evaded a general consensus in the literature. Some scenarios broadly claim that the increase in velocity dispersion is a dynamical effect of internal interactions that build up over time, with a number of different specific mechanisms being proposed as the culprit. Since the older stars have been experiencing these interactions for a longer period of time, they should therefore show the largest increase in velocity dispersion. Evidence in favour of such internal mechanisms has come from both observations (Yu & Liu 2018) and simulations (Saha, Tseng & Taam 2010; Aumer, Binney & Schönrich 2016; Grand et al. 2016). An alternative explanation is that in the early Universe, conditions were generally more chaotic (Wisnioski et al. 2015), so that any stars born at that time were more likely to have higher velocity dispersion. As conditions gradually settled over cosmic time, stars were being born in progressively lower-dispersion conditions. A number of studies have identified the conditions at birth as the dominant effect in determining a population’s present-day velocity dispersion, again both from resolved observations (Leaman et al. 2017) and simulations (Bird et al. 2013; Ma et al. 2017). Finally, the comparison between observations and simulations in Pinna et al. (2018) has identified the underlying complexity and inherent degeneracy in discriminating between these scenarios. They claim that many of the effects described above likely play a role to a varying degree and that the imprint of some mechanisms fade over time, further complicating any attempt to constrain the physical cause of disc heating.
Citation: Yu & Liu 2018
Citation function: Compare/Contrast
The stochastic accretion of gas and galaxy merger-driven gas inflows are both known triggers of supermassive black hole (SMBH) growth and nuclear activity, but the relative contributions of each is still unclear. Simulations of galaxy mergers show that they drive gas to the centers of merger-remnant galaxies (e.g., Springel et al. 2005; Hopkins & Hernquist 2009), predicting that merger-driven SMBH mass growth occurs when the black hole nears the center of the merger remnant. Observations have shown that the AGN fraction does increase with decreasing distance between two merging galaxies (Ellison et al. 2011; Koss et al. 2012; Ellison et al. 2013), but this has not been well tested at the very centers of merger-remnant galaxies because of the observational difficulty of detecting and resolving two AGNs with separations 10 kpc. This is known as the “dual AGN” phase.4

4
The separation scale expected for dual AGNs is between 0.1 and 10 kpc. The SMBHs in a merger stay at these separations for a few hundred megayears before evolving into a gravitationally bound, parsec-scale separation binary AGN system (Begelman et al. 1980).
 Hundreds of AGN pairs with >10 kpc separations have been discovered (Myers et al. 2008; Hennawi et al. 2010; Liu et al. 2011). However, there are only a few confirmed kiloparsec-scale dual AGNs (Junkkarinen et al. 2001; Komossa et al. 2003; Hudson et al. 2006; Rodriguez et al. 2006; Bianchi et al. 2008; Fu et al. 2011b; Koss et al. 2011, 2012; Mazzarella et al. 2012; Liu et al. 2013; Comerford et al. 2015). Dual AGNs are an intermediate evolutionary stage between first encounter and final coalescence of two merging gas-rich galaxies (e.g., Comerford et al. 2009; Liu et al. 2012), in which strong tidal interactions are more likely to influence the nuclear accretion and star formation in both galaxies (Barnes & Hernquist 1996). Indeed, galaxy merger simulations and observations clearly show that the dual AGN phase is the critical stage when SMBH growth and star formation activity are the most vigorous (e.g., Koss et al. 2012; Van Wassenhove et al. 2012; Blecha et al. 2013).
Citation: Koss et al. 2012
Citation function: Motivation
Citation: Koss et al.; 2012
Citation function: Background
In this context, massive (ℳ>1011 M⊙) PGs (MPGs) deserve particular attention. These systems are expected to evolve mainly through (dry) mergers (e.g. Hopkins et al. 2009; De Lucia & Blaizot 2007). If this is the case, in this mass range we should detect a stronger signal of the size-growth with respect to a lower mass range. So far, because MPGs are extremely rare, there have been very few studies that have investigated the combined evolution of the number density and of the age of MPGs as a function of their compactness (Carollo et al. 2013; Fagioli et al. 2016). Carollo et al. (2013) found that the number density of massive quiescent and elliptical galaxies with Re 2.5 kpc decreases by about 30% from z~1 to z~0.2 and that their U−V colours are consistent with passive evolution. They concluded that the driving mechanism for the average size-growth of the whole population is the appearance at later epochs of larger quiescent galaxies. More recently, Fagioli et al. (2016, hereafter F16) analysed the spectroscopic properties of ~500 MPGs (defined as galaxies with absent or very weak emission lines and no MIPS detections) at 0.2 z 0.8 in the zCOSMOS-bright 20 K catalogue (Lilly et al. 2007). From the analysis of stacked spectra of small and large MPGs, they dated the stellar content of these groups and found that the two sub-populations have similar ages. The authors concluded that, in this mass regime, the size growth of individual galaxies through dry mergers is the most likely explanation for the increase in the mean effective radius of the whole population. A recent analysis by Zahid et al. (2016) on the physical properties of compact post starburst galaxies at 0.2z0.8 with ℳ>1011 M⊙ provides new insights. On the basis of both their number density and of their ages, which have been found to be 1 Gyr, the authors suggest that this class of objects are the progenitors of compact quiescent galaxies. They conclude that a substantial fraction of dense quiescent galaxies at z0.8 are newly formed.
Citation: Carollo et al. 2013
Citation function: Motivation