adsabs/FOCAL huggingface dataset:
Supermassive black holes (SMBHs) are believed to exist in the centres of all massive galaxies (Kormendy & Richstone 1995). A small proportion of these are growing, with gas accretion rates ranging from ∼10−4 to 10 M⊙ yr−1 and a proportionately wide range of bolometric luminosities (∼1042–1047 erg s−1). These are active galactic nuclei (AGNs) and may accrete large fractions of their mass in bursts of rapid accretion (Croton et al. 2006), requiring rapid inflow of gas from galaxy length-scales. Stripping the gas of enough angular momentum to allow for such rapid accretion, thereby powering the most luminous AGN, proves extremely challenging. Theoretical work suggests major mergers can provide the torque to displace such an overwhelming fraction of the angular momentum of the gas, allowing for the highest accretion rates on to the central black hole whilst transforming the galaxy morphology (Toomre & Toomre 1972; Barnes 1988; BarnesBarnes & Hernquist 1991; Di Matteo, Springel & Hernquist 2005; Cox et al. 2008). Gas rich mergers may trigger nuclear and global starbursts (Mihos & Hernquist 1994, 1996; Hopkins et al. 2006) and major mergers disrupt the morphologies of the colliding galaxies, often exhibiting long tidal tails or shells of expelled gas and stars soon after the merger has begun. Detecting this can be challenging however, since the single new galaxy has a relaxation time-scale after which morphological features of mergers fade (Tinsley 1978; Kennicutt et al. 1987; Ellison et al. 2013). Observational evidence suggesting a link between major mergers and SMBH accretion has been mixed (e.g. Gabor et al. 2009; Cisternas et al. 2011; Schawinski et al. 2011; Kocevski et al. 2012; Treister et al. 2012; Ellison et al. 2013; Villforth et al. 2014; Kocevski et al. 2015; Villforth et al. 2017). Alternatively, AGNs may be triggered secularly through, for example, disc instabilities (Bournaud et al. 2011), bars (Knapen, Shlosman & Peletier 2000; Oh, Oh & Yi 2012) or otherwise by minor mergers (Kaviraj 2013). It remains unclear whether alternatives to major merger triggering can drive several M⊙ yr−1 of gas to the central SMBHs, as is necessary to power the most luminous AGN.
Citation: Toomre & Toomre 1972
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Citation: Cox et al. 2008
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Kochanek (2009) examined the statistical properties expected for surviving binary companions to SNe assuming passively evolving systems (i.e. no binary interactions). As already noted, the companions are generally significantly fainter than the exploding star, although this is frequently not the case for stripped SN progenitors – for Type Ibc SNe, it should not be surprising to find that the binary companion is more visually luminous than the SN progenitor. This point is of considerable importance for the one candidate Type Ib progenitor iPTF13bvn (Cao et al. 2013, Groh, Georgy & Ekström 2013, Bersten et al. 2014, Fremling et al. 2014, Eldridge et al. 2015, Eldridge & Maund 2016, Folatelli et al. 2016). If the initial binary fraction is F, then the fraction of passively evolving binaries that are in stellar binaries at death is
(1)
\begin{eqnarray}
f_{\rm b} = { F \over 1 + F f_q } \quad {\rm where}\quad f_q = \int _{q_{{\rm min}}}^{q_{{\rm max}}} q^{x-1} P(q) {\rm d}q,
\end{eqnarray}
x ≃ 2.35 is the slope of the initial mass function (IMF), qmin ≤ q = M2/M1 ≤ qmax ≤ 1 is the mass ratio and P(q) with ∫dqP(q) ≡ 1 is the distribution of mass ratios. For a Salpeter IMF and a flat P(q) distribution extending over 0 ≤ q ≤ 1, fq = 0.426 and the fraction of SNe in stellar binaries at death is 23 per cent, 41 per cent, 57 per cent and 70 per cent for initial binary fractions of F = 25 per cent, 50 per cent, 75 per cent and 100 per cent, respectively. Such a flat f(q) distribution is commonly found for massive star binaries, although there is evidence that the widest binaries show a different distribution (e.g. Sana et al. 2012, Kobulnicky et al. 2014, Moe & Di Stefano 2016). Essentially, only the explosions of primaries occur in stellar binaries, so the fraction of SNe in stellar binaries is less than the initial fraction of binaries because some of the SNe are the explosions of secondaries. Binary evolution, particularly stellar mergers then adds further complications, but changes the rough statistics little (e.g. Sana et al. 2012).
Citation: Fremling et al. 2014
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We detect 1.33 mm continuum extended emission originating from HD 36546 (see Fig. 3). Peak and integrated flux, size, and inclination are reported in Table 2. Once deconvolved from the beam, the major axis of the disc spans 180 au, compatible with the size reported from scattered light observations (semimajor axis of 85 au, Currie et al. 2017). The inclination is directly provided by the casa tool, as obtained from the ratio of the major and minor axis deconvolved from the beam. The total mass can be estimated by assuming an optically thin dust disc as $M_d = \frac{F_{\nu } d^2}{B_{\nu }(T_{d,c}) \kappa _\nu }$, where Fν is the measured flux at 1.33 mm, d is the distance to the source, Bν is the Planck function at the corresponding dust temperature Td, c, and κν is the mass absorption coefficient that we take as κν = 2 cm2 g−1 following Nilsson et al. (2010). In order to estimate a temperature for the dust, we have fitted a modified blackbody to the available photometry at wavelengths longer than 10 µm (AKARI, WISE, IRAS, Herschel)3 and the new ALMA photometry using the emcee Affine Invariant Markov chain Monte Carlo Ensemble sampler implementation (Foreman-Mackey et al. 2013). This wavelength range was chosen to avoid the silicate emission observed in the mid-IR spectra reported by Lisse et al. (2017) around ∼10 µm. Additionally, there is some discrepancy between the photometric data of WISE, Herschel, and ALMA, and those of IRAS and AKARI. Given their larger point spread functions and lower sensitivites, we decided to exclude the latter two from the fitting. The modified blackbody model assumes all dust grains have the same composition and size, and accounts for changes in the dust emission efficiency (Qλ) via two additional free parameters: β and a reference wavelength λ0, such that the blackbody emission is modified by a factor Qλ = 1 − exp [(λ0/λ)β] (e.g. Williams et al. 2004) Therefore, our model has four free parameters: a scaling factor that controls the disc luminosity, the dust temperature, β, and λ0. Uniform priors were used for all parameters within reasonable ranges: scaling values that produce disc luminosities consistent with the observed photometry, dust temperatures between 20 and 250 K, β values between 0 and 1.5, and λ0 between 0.3 and 300 µm (the latter was explored in log scale). This analysis yields a dust temperature value of 153 ± 3 K, and a β value of 0.24 $^{+0.07}_{-0.05}$ as shown in Fig. 1. λ0 is unconstrained. Adopting this temperature value results in a dust mass of (9.0 ± 1.0) × 10−2 M⊕. Additionally, the resulting models yield Ldisc/L* = (4.43 ± 0.15) × 10−3, compatible with previous results (see Table 1).
Citation: Foreman-Mackey et al. 2013
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We created 10 000 3D models of galaxies, each with an exponential disc plus a Sérsic bulge. We adopted the following functional form for the exponential disc (López-Corredoira et al. 2002): (1)\begin{equation} \label{eq:Corredoira}  \rho(R,z)=\rho_{\mathrm{0}}\cdot\exp{\Bigg(\frac{-R}{h_{R}}\Bigg)}\cdot \exp{\Bigg(\frac{-|z|}{h_{z}(R)}\Bigg)}\cdot \frac{h_{z}(R)}{h_{z}(0)} \cdot \end{equation}ρ(R,z)=ρ0·exp−RhR·exp−|z|hz(R)·hz(R)hz(0)·Following the observations, we explored the effect of a linear increase in the vertical scale height, as follows: (2)\begin{equation} \label{eq:Flares_linear} h_{z}(R) = \begin{cases} h_{z}(0) &amp; \text{if } R \leq R_{\mathrm{flare}} \\ h_{z}(0) + \dhzdR \cdot R &amp; \text{if } R > R_{\mathrm{flare}}. \end{cases} \end{equation}hz(R)=ifR≤RflareifR>Rflare.Graham (2001) analysed a sample of 86 face-on disc-dominated galaxies previously selected by de Jong & van der Kruit (1994). This author performed a bulge + disc decomposition for 69 galaxies in the I-band, correcting for the effects of the internal extinction, Galactic extinction, inclination, and cosmological dimming (Graham 2003), that we used as a reference for our models. We estimated stellar masses using the relationship between the V-band mass-to-light ratio of galaxies and their dust-corrected rest-frame colours derived by Wilkins et al. (2013). According to these authors, for z 0.1 the optimal observed colour is (B − V), so we have estimated this colour for the 69 galaxies of Graham (2003) from HyperLeda data1, and estimated the stellar mass of each galaxy using the relations in Wilkins et al. For those objects without (B − V) available in HyperLeda, we estimated them from their SDSS (g − r) colour following the transformations published in Jester et al. (2005). To simulate realistic images of the disc galaxies, we adopted the observational I-band distributions of Graham (2001, 2003) for the photometric parameters (re, Sérsic index n, hR, μ0, μe, B/T, the absolute magnitudes of the disc Mabs,disc and the bulge Mabs,bulge), and four morphological type bins (S0–Sa, Sb–Sbc, Sc–Scd and Sd–Sdm), in three mass bins (10  log 10M/M⊙ 10.7,10.7  log 10M/M⊙ 11 and log 10M/M⊙> 11) in order to explore realistic mass distributions for the morphological type bins. In Fig. 1 we represent the distributions of the structural and photometric parameters from which we created the models and compared them to the observations they are based on. For each morphological type bin we randomly chose the ratio of scale height to scale length (hz/hR) from the observational range of values corresponding to each type reported by Kregel et al. (2002) and Mosenkov et al. (2015) in the I-band, as shown in Fig. 1.
Citation: de Jong & van der Kruit (1994)
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Other important result we reported in Section 3.3 is the reversing behaviour of red and blue galaxies with respect to velocity and groupcentric distances segregation, with redshift. Regarding velocity segregation, the preceding paragraph provides a qualitative scenario. Now, to explain the spatial segregation, we should notice that our analyses in Sections 3.2 and 3.3 take into account galaxies within 2R/R200. One can reasonably assume that such objects at lower redshifts correspond to a mixture of descendants of galaxies at higher redshifts in the same radii and of infalling objects from outer radii. Thus, both survival and replenishment of galaxies should be expected over the time, and two important factors come into play: (i) the accretion rate of galaxies; and (ii) the orbital dependence of galaxy properties (e.g. Biviano & Katgert 2004; Iannuzzi & Dolag 2012). Indeed, regarding velocity segregation, it has also been interpreted as red and blue galaxies having different kinds of orbits, with the orbits of blue galaxies being more anisotropic than the red ones (e.g. Biviano & Katgert 2004). Recently, Biviano et al. (2016) verified that the anisotropy profile of z ∼ 1 clusters is nearly isotropic near the cluster centre, and increasingly elongated with radius. This result is consistent with a halo evolution through an initial phase of fast collapse and a subsequent slow phase of inside-out growth by accrection of field material (e.g. Lapi & Cavaliere 2009). Since the accretion rate of galaxies from the field is higher at higher redshifts (e.g. McGee et al. 2009), our sample at z ∼ 0.8 is expected to be more affected by recent infalls, which had less time to go deeper into the group potential. This could explain the development of a more marked difference between the mean groupcentric distance of red and blue galaxies (see Fig. 12). After ∼3 Gyr, part of these infalling galaxies may reach the R  2R200 region, at z ∼ 0.4, mixing with virialized and backsplash objects, and thus presenting a less pronounced radial segregation between red and blue galaxies.
Citation: Iannuzzi & Dolag 2012
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Citation: Biviano & Katgert 2004
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Massive stars are believed to exist in the accretion disks of active galactic nuclei (AGNs). Such AGN stars and compact objects can be either the result of in situ formation inside the accretion disk or be captured from the nuclear star clusters around the AGNs (e.g., Artymowicz et al. 1993; Collin & Zahn 1999; Goodman 2003; Goodman & Tan 2004; Wang et al. 2011, 2012; Fabj et al. 2020; Cantiello et al. 2021). These AGN stars will end up with supernovae (SNe), which can eject heavy elements into the disk; this offers a possible explanation for the observational features of high-metallicity environments in AGN disks (e.g., Artymowicz et al. 1993; Hamann & Ferland 1999; Warner et al. 2003). Some compact objects, including white dwarfs (WDs), neutron stars (NSs), and black holes (BHs), can be thus formed within AGN disks. These compact objects can also be captured from the surrounding nuclear star clusters. The disk of an AGN provides a natural environment for stars and compact objects to accrete materials and to migrate within it (e.g., McKernan et al. 2012; Yang et al. 2020; Dittmann et al. 2021; Jermyn et al. 2021; Wang et al. 2021; Tagawa et al. 2021; Kimura et al. 2021). Some of these stars can be very massive and have high spin caused by accretion (Dittmann et al. 2021; Jermyn et al. 2021), so that they can easily produce high-spin stellar remnants. Abundant compact objects, especially with the presence of the massive BHs (M > 10M⊙), would likely accrete, collide, and merge within the trapping orbits, and hence would grow into ∼100 M⊙ intermediate-mass BHs (McKernan et al. 2012; Secunda et al. 2019; Yang et al. 2019b). Some AGN stars can be tidally disrupted by these BHs that can power micro-tidal disruption events (Yang et al. 2021). The death of high-spin stars and neutron star mergers are expected to power gamma-ray burst (GRB) jets, which would be always choked by the dense atmosphere of the disks (Zhu et al. 2021a, 2021b; Perna et al. 2021a). Zhu et al. (2021a) suggested that these choked jets can produce high-energy neutrinos that may contribute a substantial fraction of the diffuse neutrino background. A candidate electromagnetic (EM) counterpart that emerged from an AGN, explained as ram pressure stripping of gas within the kicked BH hill sphere colliding with the AGN disk gas (McKernan et al. 2019), was reported by the Zwicky Transient Facility (Graham et al. 2020). This was thought to be associated with a (85 + 66)M⊙ binary BH merger (GW190521) detected by the LIGO/Virgo collaboration (Abbott et al. 2020). This connection provided plausible evidence of a potentially important AGN channel for compact star mergers.
Citation: McKernan et al. 2012
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An implication of the respective escape fractions of the two regimes is visible in Fig. 12. Here we show several values of NHI,cl for the static setup using τd,cl = 10-4 (empty symbols) and τd,cl = 1 (filled symbols), which correspond to metallicities of \hbox{$Z/Z_\odot = 0.63\left(\tau_{\rm d}/10^{-4}\right)\left(10^{17}\cm^{-2}/N_{\HI,\cl}\right)$}Z/Z⊙=0.63τd(/10-4)(1017 cm-2/NHI,cl) (Pei 1992; Laursen et al. 2009); this reaches clearly unrealistic values. However, as in this paper we are interested in the fundamental impact of the individual parameters, we also study these extreme values. Also shown in Fig. 12 (with a black [gray] solid line for the low [high] dust content) is the proposed analytic solution for fesc by Hansen & Oh (2006)(18)\begin{equation} f_{\rm esc}^{\rm HO06} = 1/{\rm cosh}(\!\sqrt{2 N_{\cl}\epsilon}), \label{eq:fescHO06} \end{equation}fescHO06=1/cosh(2Nclϵ),where for Ncl we used Eq. (8)(with (a1,b1) = (3/2, 2) as found in Sect. 4.1) and for the clump albedo (i.e., the fraction of incoming photons that are reflected) ϵ, we adopted a value of c1(1−e− τd,cl) with c1 = 1.6 [c1 = 0.06] to match the NHI,cl = 1022 cm-2 data points for τd,cl = 10-4 [τd,cl = 1]. The behavior for the low- and high-dust contents is quite different. On the one hand, the escape fractions versus NHI,cl scales for τd,cl = 1 (filled symbols in Fig. 12) as predicted by Hansen & Oh (2006) in their “surface scatter” approximation, that is, a larger clump hydrogen column density “shields” the dust better from the Lyα photons and thus prevents their destruction more efficiently. On the other hand, however, this is not the case for the low-dust scenario presented in Fig. 12 (with unfilled symbols) where a larger value of NHI,cl implies a lower fesc. This is because here the dust optical depth through all the clumps (shown in the black dotted line in Fig. 12) is lower than the accumulated dust optical depth through the subsequent random-walk clump encounters (black solid line), i.e., \hbox{$\exp(-4/3 \fc \tau_{\rm d, cl}) \lesssim f_{\rm esc}^{\rm HO06}$}exp(−4/3fcτd,cl)≲fescHO06. Consequently, configurations in the “free-streaming” regime can possess enhanced Lyα escape fractions compared to the “random walk” regime (see Sect. 5.2 for a more detailed discussion). Still, both cases possess (much) larger escape fractions than a homogeneous slab, which is shown in Fig. 12 with a black dashed line. Here, we use the derived escape fraction by Neufeld (1990) with NHI = 4/3 × fc1022 cm-2 and τd = 4/3fcτd,cl, i.e., with equal column densities as in the NHI,cl = 1022 cm-2 case.
Citation: Hansen & Oh (2006)
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Citation: Hansen & Oh (2006)
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Analyses of 21-cm signals are mainly based on traditional N-point correlation statistics. Beyond the simplest two-point function (power spectrum), higher-order correlations are quite non-trivial to calculate and sometimes they suffer from conceptual challenges. On the other hand, the Minkowski functionals (MFs) are extremely useful tools in quantitatively describing the morphology because, in principle, they contain information on all the higher-order moments. The MFs were first introduced in cosmology by Mecke, Buchert & Wagner (1994). Since then they have been extensively employed to study the morphology of the large-scale structure of the universe and the cosmic web (Schmalzing & Buchert 1997; Sahni, Sathyaprakash & Shandarin 1998; Sathyaprakash, Sahni & Shandarin 1998; Bharadwaj et al. 2000; Hikage et al. 2003; Bharadwaj, Bhavsar & Sheth 2004; Pandey & Bharadwaj 2008; Einasto et al. 2011; Wiegand & Eisenstein 2017) as well as the CMB (Schmalzing & Gorski 1998; Novikov, Feldman & Shandarin 1999; Novikov, Schmalzing & Mukhanov 2000; Hikage, Komatsu & Matsubara 2006). Since the reionization landscape is similarly rich in geometrical properties because of growth and overlap of ionized ‘bubbles’, studying the morphology of reionization using MFs is highly compelling and feasible. The physics underlying the reionization process is expected to be manifested in the geometry and morphology of H i and H ii regions. The ratios of MFs are introduced in Sahni et al. (1998) as Shapefinders that precisely assess the shape of an object by directly estimating its physical dimensions. Therefore, using MFs and Shapefinders of the ionization field, it should be possible to probe the physics of the high-redshift universe. For instance, if reionization is driven in a non-standard manner through large energy output from multiple quasar jets, the very first ionized bubbles might be filamentary and not spherical (as they would be for point-like sources like stars in galaxies). Clearly the 3D structure of cosmological reionization in this scenario would be very different from the standard mechanism of point-like sources.
Citation: Schmalzing & Buchert 1997
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During the likelihood analysis, the normalizations and spectral parameters of all sources within 5° of 3FGL J1640.4-4634c, as well as the normalizations of the two diffuse backgrounds, are left free. First, we create a Test Statistic (TS) map by subtracting the emission from the sources and backgrounds in the best-fit model with gttsmap, which is shown in the top panel of Figure 1. Some residual emission are shown in this TS map. Then we add additional point sources with power-law spectra in the model. The accurate positions of these sources obtained using the gtfindsrc tool, together with their TS values, are listed in Table 1. Next, we adopt the position of 3FGL J1640.4-4634c provisionally provided by the 3FGL catalog (Acero et al. 2015) and investigate the spectrum of 3FGL J1640.4-4634c. We bin the data into 12 equal logarithmic energy bins from 1 to 500 GeV and repeat the same likelihood fitting for each energy bin. In the model, the normalization parameters of sources within 5° around 3FGL J1640.4-4634c and the two diffuse backgrounds are left free, while all spectral indices, except 3FGL J1640.4-4634c, are fixed. The 95% upper limits are calculated for energy bins with TS values smaller than 4. The resulting spectral energy distribution (SED) is shown in the bottom panel of Figure 1. An obvious spectral upturn is shown in the SED of 3FGL J1640.4-4634c at an energy of about 10 GeV. To test whether the upturn spectrum is intrinsic or is due to two overlapping sources, we do the same likelihood fitting using the events with energies of 1–10 GeV and 10–500 GeV, respectively. For each analysis, we create a TS map with all sources (except 3FGL J1640.4-4634c) included in the model, which are shown in the Figure 2. The TS maps show a clear difference between two energy bands, and the centroids of emission in both energy bands deviate from that of 3FGL J1640.4-4634c. We thus expect that 3FGL J1640.4-4634c should consist of two different sources (labeled as “Source A” for the 1–10 GeV source and “Source B” for the 10–500 GeV source), and the source in the 3FGL catalog is simply the sum of these two sources.
Citation: Acero et al. 2015
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Among the existing IACT systems, HESS has the largest FoV and hence provides the highest sensitivity for the diffuse γ-ray flux. Its electron spectrum analysis technique could be directly used to obtain a measurement of the diffuse Galactic γ-ray flux above energies of several TeV in the Galactic Ridge (|l|  30°, |b|  2°) region; see Figs. 3 and 4. A multi-year exposure of HESS could be sufficient for detection of the diffuse emission even from regions of higher Galactic latitude. This is illustrated in Fig. 5, where thick blue and red data points show mild high-energy excesses of the electron spectra derived by Kraus (2018), Kerszberg et al. (2017), Kerszberg (2017) over broken power-law models derived from the fits to lower energy data. Comparing these excesses with the level of the IceCube astrophysical neutrino flux and with the Fermi/LAT diffuse sky flux from the region |b| > 7° (corresponding to the data selection criterium of HESS analysis Kerszberg et al. 2017; Kerszberg 2017) we find that the overall excess flux levels are comparable to expected diffuse γ-ray flux from the sky region covered by the HESS analysis (the quoted systematic error on the electron flux is Δlog(EFE) ≃ 0.4). The overall excesses within 805 and 1186 h of HESS exposures (Kraus 2018; Kerszberg 2017) are at the levels of >4σ for the analysis of Kraus (2018) and 1.7σ for the analysis of Kerszberg (2017). A factor-of-ten longer exposure (which is potentially already available with HESS) could reveal a higher significance excess at the level of up to 5σ. Such an excess is predicted in a range of theoretical models including interactions of cosmic rays injected by a nearby source (Andersen et al. 2018; Neronov et al. 2018; Bouyahiaoui et al. 2019) or decays of dark matter particles (Berezinsky et al. 1997; Feldstein et al. 2013; Esmaili & Serpico 2013; Neronov et al. 2018) or a large-scale cosmic ray halo around the Galaxy (Taylor et al. 2014; Blasi & Amato 2019).
Citation: Kerszberg et al. (2017)
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Citation: Kraus (2018)
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Citation: Kraus 2018
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Citation: Kraus (2018)
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