adsabs/FOCAL huggingface dataset:
The most general third-order statistics is the three-point correlation function (hereafter referred to as 3PCF), which is defined in configurations space. Alternatively, one can study its Fourier space counterpart, the bispectrum. These two statistics contain, in principle, the same information. However, their analyses implicate different limitations and challenges, which can affect the physical interpretation of the results. A main advantage of the bispectrum is that an analysis in Fourier space allows for a clear exclusion of high-frequency modes in the density fluctuations, which are difficult to interpret theoretically due to their highly non-linear evolution. In configuration space, these high-frequency modes contribute to the 3PCF, in principle, at all scales. In practice, one therefore needs to restrict the analysis to large scales, where their contribution is negligible, lavishing a lot of valuable data. Another advantage of the bispectrum is that its covariance is diagonal for Gaussian density fluctuations. This approximation works well, even for evolved density fields, while deviations from Gaussianity can also be taken into account (Scoccimarro 2000; Sefusatti et al. 2006; Chan & Blot 2017). The covariance of the 3PCF, on the other hand, is not diagonal, even for Gaussian fluctuations, which makes the modelling more difficult (Srednicki 1993; Slepian & Eisenstein 2015; Byun et al. 2017; Gualdi et al. 2017). An additional difference in the analysis of the bispectrum and the 3PCF lies in the fact that the computation of the latter is more expensive. However, this aspect can be tackled by employing advanced algorithms and appropriate computational resources, as done in this work (see also, Barriga & Gaztañaga 2002; McBride et al. 2011a; Jarvis 2015; Slepian & Eisenstein 2015, and references therein). Besides its disadvantages, there are some arguments that speak for the 3PCF. One of them is the fact that the amplitude of the 3PCF (but not its errors) is not affected by shot-noise, whereas the latter affects the bispectrum amplitude at all scales and hence needs to be modelled for correcting the measurements. In addition, an analysis in configuration space has the advantage that complicated survey masks can be easily taken into account in the analysis of observational data, while in Fourier space such masks impose complicated effects on the measured bispectrum, which are difficult to model (e.g. Scoccimarro 2000). A more general consideration is that it is easier to interpret effects such as redshift space distortions or baryon acoustic oscillations (BAOs) on the statistics in configuration space, since that is where the physical processes that cause these effects happen. Studies of third-order correlations in the literature usually focus on either Fourier or configuration space (e.g. McBride et al. 2011b; Marín et al. 2013; Gil-Marín et al. 2015). However, it is worthwhile studying both statistics and cross-check the results, since their different advantages and disadvantages are quite complementary.
Citation: Byun et al. 2017
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Citation: Scoccimarro 2000
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Other examples of AGN variability are given by the so-called changing-look AGN, which present a change in the AGN type (e.g. from Type 1 to Type 1.9) due to broadening or narrowing of the Balmer lines4 (Denney et al. 2014; LaMassa et al. 2015; Ruan et al. 2015; Gezari et al. 2016; Husemann et al. 2016; McElroy et al. 2016; MacLeod et al. 2016; Runnoe et al. 2016; Stern et al., in preparation). The appearance or disappearance of broad emission lines is often accompanied by a change in luminosity of a factor ∼10 over ∼10 yr time-scales. As described above, these time-scales are much shorter compared to time-scales expected for accretion state changes (e.g. Sobolewska, Siemiginowska & Gierliński 2011; Hickox et al. 2014), and possible alternative explanations of the changing-look behaviour are variable absorption due to a clumpy torus (e.g. Elitzur 2012), transient events, e.g. tidal disruption of a star by the central black hole (e.g. Eracleous et al. 1995; Merloni et al. 2015), or major changes in the photoionization balance. The magnitude of the drop in luminosity measured in IC 2497 is at least a factor of ∼2 higher than what has been observed in a changing-look AGN. Moreover, the Chandra  and NuSTAR data do not show significant variability, and the upper limits obtained from archival WISE, NEOWISE and IRAS data seem to exclude that the total drop in luminosity happened within the last decades. For these reasons, we argue that the AGN in IC 2497 should not be classified as a changing-look AGN. On the other hand, we suggest that a changing-look AGN corresponds to a short-time (∼10–100 yr) variability which is superimposed on the long-term (∼105–6 yr) AGN phases suggested by this work and other observations (e.g. Schawinski et al. 2015), high resolution (sub-kpc) simulations (Hopkins & Quataert 2010; Bournaud et al. 2011; Novak, Ostriker & Ciotti 2011; Gabor & Bournaud 2013; DeGraf et al. 2014; Sijacki et al. 2015) and theoretical models (Siemiginowska & Elvis 1997; Sanders 1981; Di Matteo, Springel & Hernquist 2005; Hopkins et al. 2005; Springel, Di Matteo & Hernquist 2005; King & Pringle 2007; King & Nixon 2015).
Citation: Merloni et al. 2015
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According to simulations, blue galaxies infalling from the field reach pericenter in about 2.4 Gyr (McGee et al. 2009; see also Oman et al. 2013), and we can hypothesize that, by the time they get there, they lose most of their gas. In the first part of this time frame, they can start feeling the action of the ram pressure, and their neutral gas content, which is less bound, starts being stripped. No signs at optical wavelengths are visible yet, but the stripping has started (Tonnesen & Bryan 2010). In some galaxies, ram pressure stripping might be able to unwind the spiral arms (Bellhouse et al. 2021), while in other galaxies it just strips the gas that at some point collapses and starts forming new stars (e.g., Poggianti et al. 2019a). In this phase, tails shine at optical wavelengths, as OB massive stars are very bright. We can assume the visibility of this phase lasts on the order of ∼6 × 108 yr (Fumagalli et al. 2011; Poggianti et al. 2019a). Stripping and star formation consume the available gas and galaxies first appear as truncated disks (Koopmann & Kenney 2004; Fritz et al. 2017) and then become passive, showing k+a spectra (Vulcani et al. 2020). Galaxies typically maintain blue colors for 0.5 Gyr after becoming passive and then move to the red sequence (Poggianti et al. 2004). In these phases, tails are not visible anymore at optical wavelengths. So to summarize, an infalling galaxy maintains its blue color for at least 2.4 + 0.5 ∼3 Gyr since infall and a tail is visible only for 6 × 108yr. We can assume that the sum of RS+SC+UG samples corresponds to all the noninteracting blue late-type galaxies in the clusters and that the tailed galaxies are either only SC or SC+UG. In the first case, ∼15% of the blue cluster galaxies currently show signs of stripping, but since the visibility phase is 6 × 108/3 × 109 ∼ 0.2, the total amount of galaxies undergoing stripping is 15%/0.2 ∼ 75%. In the second case, the incidence of blue cluster galaxies currently showing signs of stripping is even higher. On one hand, this suggests that all blue cluster galaxies undergo a stripping phase during their life in clusters, and on the other hand, it indicates that most likely we are overestimating the number of ram pressure stripped galaxies only using optical imaging.
Citation: Koopmann & Kenney 2004
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Andromeda is a galaxy that lies in the green valley (Mutch et al. 2011; Tempel et al. 2011; Jin et al. 2014). According to Belfiore et al. (2016), it is typically a low-ionisation emission-line region (LIER), as first observed by Rubin & Ford (1971) and discussed by Heckman (1996). González-Martín et al. (2015) discussed that the torus is disappearing in LIER: there is indeed little gas in the inner part of M31 (Melchior et al. 2000; Melchior & Combes 2011, 2013). It is the closest external large galaxy in which we can explore the mechanisms that quenched the star formation activity. Optical ionised gas has been observed by Menezes et al. (2013) next to the black hole in a field of view1 of 5′′ × 3.5′′, but this emission is weak. Jacoby et al. (1985) estimated the ionised gas mass in the bulge (10′ × 10′) to be of the order of 1500 M⊙. It also hosts a very massive black hole of 1.4 × 108M⊙ (Bender et al. 2005), but as studied by Li et al. (2011a), it is non-active and only murmurs at a level of 10-10LEdd. It hosts very little star formation of the order of 0.25−0.3 M⊙ yr-1, mainly located in the 10 kpc ring of the disc (e.g. Ford et al. 2013; Rahmani et al. 2016). Inside the central region (10′ × 10′), no obvious sign of star formation is detected (e.g. Kang et al. 2012; Azimlu et al. 2011; Amiri & Darling 2016), except for a central cluster of A stars formed 200 Myr ago that is located next to the black hole (within 1′′) (Lauer et al. 2012), designated by P3 by Bender et al. (2005). Viaene et al. (2014) estimated the star formation rate (SFR) on a pixel basis with panchromatic spectral energy distribution modelling. This infrared-based SFR estimated in the central pixel (36′′ × 36′′) is 4 × 10-5M⊙ yr-1, while an integration over the central region with a radius of 1 kpc corresponds to 1.25 × 10-3M⊙ yr-1. This negligible SFR is much lower than the value predicted by Rimoldi et al. (2016), considering supernovae remnants expected within the sphere of influence of quiescent supermassive black holes. For M31, an SFR of 0.13 M⊙yr-1 is expected in the sphere of influence (RSOI = 14 pc = 3.7”) of its supermassive black hole. A past AGN activity is also expected, and the associated molecular torus, if it survives, should have a radius RMT = 25 pc = 6.7′′. In parallel, Chang et al. (2007) expected next to the black hole an accumulation of molecular gas (about 104M⊙) originating from stellar feed-back. Melchior & Combes (2013) estimated a minimum molecular mass of 4.2  ×  104M⊙ within 30″ from the centre, while about 106M⊙ of gas is expected from stellar feedback (e.g. Gallagher & Hunter 1981).
Citation: Menezes et al. (2013)
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Alongside the above theoretical uncertainties in the physics of core formation in ellipticals, there have also been observational challenges. In particular, determining the size of the core has proven to be a non-trivial task. The light profiles of ellipticals are well described by the 3-parameter Sérsic profile (Sérsic 1963, 1968) over a large radial range. The most luminous ellipticals, however, show a departure from the Sérsic law in their central regions, at a radius widely known as the ‘break’ or ‘core’ radius. In these galaxies, the profiles break downward from the inward extrapolation of the outer Sérsic law. Initially the core size of a galaxy was determined by fitting the so-called ‘Nuker-profile’ (Lauer et al. 1995) to the surface brightness profile, a method that however depends sensitively on the radial fitting range and yields unreliable results when fit to surface brightness profiles with a large radial extent (e.g. Graham et al. 2003; Dullo & Graham 2012). In more recent years, it has become customary to incorporate a central flattening in the light profile by adopting a 6-parameter core-Sérsic profile (Graham et al. 2003; Trujillo et al. 2004) which provides a reliable measurement of the core size even over a large radial range (e.g. Dullo & Graham 2012, 2013, 2014). Furthermore, it has been shown that adopting a multicomponent model rather than a single core-Sérsic model over the entire radial range provides a more reliable estimate of the core size (Dullo & Graham 2014; Dullo 2019). Measured core sizes for massive ellipticals – derived in this way – are typically tens to a few hundred parsecs (e.g. Dullo & Graham 2014), while cores larger than $1{\, \mathrm{kpc}}$ are rare. A study by Lauer et al. (2007) considered a large sample of brightest cluster galaxies (BCGs) and found that fewer than 10 systems had a core size of $\sim 1\rm {kpc}$ or greater, with the largest cored system being NGC 6166 which has a core size of $\sim 1.5{\, \mathrm{kpc}}$. More recently, Dullo (2019) considered the largest sample of ‘large-core’ galaxies to date, finding that only 13(7) galaxies have core sizes larger than $0.5(1){\, \mathrm{kpc}}$.
Citation: Dullo & Graham 2012
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The mechanism(s) driving the transport of angular momentum (e.g., Aerts et al. 2019a) and chemical elements (e.g., Salaris & Cassisi 2017) within stars are still not understood from stellar evolution theory. Discrepancies between observations and theory have been shown for stars with birth masses between 1.3 and 8 M





, which comprise a convective core, enshrouded by a radiative envelope (possibly with internal convective shells from partial ionization zones or a thin outer convective envelope for 





 M





). In these radiative envelopes, the transport of chemical elements on a macroscopic scale is ascribed to convective core overshooting (e.g., Viallet et al. 2015), rotation (e.g., Maeder 2009), or internal gravity waves (IGWs, e.g., Rogers & McElwaine 2017), whereas the transport of chemical elements on a microscopic scale is the result of atomic diffusion (Michaud et al. 2015). In stellar evolution codes, the description of macroscopic mixing introduces additional free parameters, whereas mixing from atomic diffusion can be derived from first principles. So far, the theory of element transport has been mainly evaluated by measurements of surface abundances. Asteroseismology constitutes a novel technique to empirically assess the conditions deep inside the interior (Aerts et al. 2010) of a star, as well as its evolutionary history (e.g., Bowman et al. 2019). The unprecedented high-quality data from the space-based CoRoT (Auvergne et al. 2009), Kepler  (Borucki et al. 2010), and TESS (Ricker et al. 2015) missions allow for scrutiny of the current stellar evolution models of the stars’ interiors by means of gravito-inertial asteroseismology (Aerts et al. 2018). The current state-of-the-art stellar models and pulsation codes are not capable of reproducing the observed oscillation frequencies of gravity (g) modes in γ Doradus (γ Dor; see Kurtz et al. 2014; Saio et al. 2015; Schmid & Aerts 2016; Van Reeth et al. 2016) and slowly pulsating B-type (see Pápics et al. 2014; Moravveji et al. 2015; Szewczuk & Daszyńska-Daszkiewicz 2018; Aerts et al. 2019b) stars within the uncertainties of the data. Hence, additional physics is required in order to improve both the current stellar models and the prediction of the g-mode frequencies from these equilibrium models. Studies have already demonstrated the potential of g-modes to distinguish between different near-core mixing profiles (Pedersen et al. 2018) and the temperature gradient close to the convective core interface (Michielsen et al. 2019). The work of Aerts et al. (2018) has evaluated a hierarchy of input physics when modeling g-modes across a wide mass range. In the current work, we investigate to what extent the process of atomic diffusion can improve the theoretically predicted oscillation frequencies in two slowly rotating γ Dor stars.
Citation: Rogers & McElwaine 2017
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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.
Citation: Novak, Ostriker & Ciotti 2011
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Citation: Di Matteo, Springel & Hernquist 2005
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In addition, the Abell 901/902 field has deep and extensive photometry in the UV (Galex, Gray et al. 2009), optical (COMBO-17 survey, Wolf et al. 2003), near-infrared (Spitzer 24 μm, Bell et al. 2007), and X-ray (XMM-Newton, Gilmour et al. 2007) wavelength range. Out of the four main substructures that embody Abell 901/902, only the two most massive (A901a and A901b) show significant X-ray emission, but this may come from a very bright AGN close to the cluster center in A901a (Gilmour et al. 2007). The evolution of the cluster members’ colors, morphologies, and star-formation activity has been studied over the years, and redder stellar populations, lower star-formation rates, and indications of interactions within the cluster population of galaxies were reported (Wolf et al. 2009; Gallazzi et al. 2009). More recently, the emission-line OMEGA-OSIRIS survey provided similar results (e.g., Chies-Santos et al. 2015; Rodríguez del Pino et al. 2017; Weinzirl et al. 2017; Roman-Oliveira et al. 2019). Our group carried out a kinematic analysis of a subsample of cluster galaxies using slit spectra taken by VIMOS at the Very Large Telescope (VLT) with the HR-blue grism (R ∼ 2000) to search for indications of ram-pressure stripping (Bösch et al. 2013a) and study the slope and scatter of the TFR (Bösch et al. 2013b). Galaxies within three times the velocity dispersion (3σ) of each substructure are considered to be cluster members (Bösch et al. 2013a). We retrieved a sample of 45 cluster galaxies from Bösch et al. (2013b) characterized by their high-quality rotation curves, their disk morphology, and stellar masses above log(M*) = 9.5. This sample is used in Sect. 4 to explore the evolution of the TFR between clusters at different redshifts. The distribution of the main parameters (M* and Vmax) and their mean properties are shown in Fig. 1 and listed in Table 3. However, the sizes and exact coordinates of these galaxies within the Abell 901/902 cluster complex are not provided in the publications mentioned above, and we therefore excluded this sample from the analysis that requires them.
Citation: Roman-Oliveira et al. 2019
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After the disruption phase, the star is tidally stretched into a very long thin stream and the evolution of the stream structure in the transverse and longitudinal directions are decoupled (Kochanek 1994). Thus, the system enters the free-fall phase where each stream segment follows its own geodesic like a test particle (Coughlin et al. 2016). Then, after passing the apocentres of the highly eccentric orbits, the bound debris falls back towards the BH at a rate given by the distribution of specific energy (Evans & Kochanek 1989; Phinney 1989). Due to relativistic apsidal precession, the bound debris, after passing the pericentre, collides violently with the still in-falling stream (see Fig. 1). It has been shown that shocks at the self-intersection point is the main cause of orbital energy dissipation and the subsequent formation of an accretion disc (Rees 1988; Kochanek 1994; Hayasaki, Stone & Loeb 2013; Guillochon, Manukian & Ramirez-Ruiz 2014; Shiokawa et al. 2015; Bonnerot et al. 2016). However, the aftermath of the self-intersection is an extremely complex problem, which depends on the interplay among magnetohydrodynamics, radiation, and general relativity in 3D. No numerical simulations to date have been able to provide a deterministic model for TDEs with realistic star-to-BH mass ratio and high eccentricity (see Stone et al. 2018a, for a review). Many simulations consider either an intermediate-mass BH (e.g. Guillochon et al. 2014, Evans, Laguna & Eracleous 2015; Shiokawa et al. 2015; Sa̧dowski et al. 2016) or the disruption of a low-eccentricity (initially bound) star (e.g. Bonnerot et al. 2016; Hayasaki, Stone & Loeb 2016). It is unclear how to extrapolate the simulation results to realistic configurations and provide an answer to the following questions: How long does it take for the bound gas to form a circular accretion disc (if at all)? How much radiative energy is released from the system? What fraction of the radiation is emitted in the optical, UV, or X-ray bands?
Citation: Shiokawa et al. 2015
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Citation: Shiokawa et al. 2015
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