adsabs/FOCAL huggingface dataset:
Because of its large mass, the discovery of GW190425 suggests that gravitational-wave analyses can access densities several times above nuclear saturation (see, e.g., Figure 4 in Douchin & Haensel 2001) and probe possible phase transitions inside the core of a neutron star (NS) (Oertel et al. 2017; Essick et al. 2019; Tews et al. 2019). However, binaries comprised of more massive stars are described, for a fixed EoS, by smaller values of the leading-order tidal contribution to the gravitational-wave phasing 





 (Flanagan & Hinderer 2008). These are intrinsically more difficult to measure. For GW190425, this is exacerbated by the fairly low S/N of the event compared to GW170817. Overall, we find that constraints on tides, radius, possible p–g instabilities (Venumadhav et al. 2013; Weinberg et al. 2013; Weinberg 2016; Zhou & Zhang 2017), and the EoS from GW190425 are consistent with those obtained from GW170817 (Abbott et al. 2017b, 2019e). However, GW190425 is less constraining of NS properties, limiting the radius to only below 15 km, 





 to below 1100 and only ruling out phenomenological p–g amplitudes above 1.3 times the 90% upper limit obtained from GW170817 at the same confidence level. The p–g constraints were obtained with a different high-spin prior than the rest of the results (see Appendix F.5) but the difference does not significantly change our conclusions. Spin priors can affect the inference of tidal and EoS parameters, and we note that the low-spin results are generally more constrained. Following Agathos et al. (2020), we estimate the probability of the binary promptly collapsing into a black hole (BH) after merger to be 96%, with the low-spin prior, or 97% with the high-spin prior. Repeating the analyses of Chatziioannou et al. (2017) and Abbott et al. (2019d), we find no evidence of a postmerger signal in the 1 s of data surrounding the time of coalescence. We obtain 90% credible upper limits on the strain amplitude spectral density and the energy spectral density of 





 and 





, respectively, for a frequency of 2.5 kHz. Similar to GW170817, this upper limit is higher than any expected post-merger emission from the binary (Abbott et al. 2019d). More details on all calculations and additional analyses are provided in Appendix F.7.
Citation: (Abbott et al; 2019e
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The surface brightness profile for the mosaicked image of A2199 was then extracted in concentric annuli centred at the cluster centre (RA, Dec.) = (16:28:38.21,  +39:33:02.31). This corresponds to the location of the peak X-ray flux in the cluster. The radial profile of the surface brightness is shown in the upper panel of Fig. 2. In the lower panel of this figure, we present the radial profile of the azimuthally averaged electron density of A2199. The profile is recovered from the deprojection of the median surface brightness profile using the onion peeling technique (Ettori et al. 2010), and assuming that the ICM plasma is spherical symmetry. To convert from surface brightness to density, we use the following widely used approach (Eckert et al. 2012; Tchernin et al. 2016; Ghirardini et al. 2018; Ghirardini et al. 2019; Walker et al. 2020). Using xspec and the response files for XMM–Newton, the conversion factor between APEC normalization and X-ray count rate in the 0.7–1.2 keV band is found. In the 0.7–1.2 keV band, this is largely independent of the temperature of the gas, so this allows a direct conversion from the deprojected X-ray surface brightness profile to a deprojected profile of APEC normalization. The APEC normalization is related to the gas density by the equation:
(1)$$\begin{eqnarray*}
{\rm Norm} = \frac{10^{-14}}{4 \pi [d_\mathrm{A}(1+z)]^2 }\int n_\mathrm{ e} n_\mathrm{H} \mathrm{d}V,
\end{eqnarray*}$$where the electron and ion number densities are ne and nH, respectively (for a fully ionized plasma these are related by ne = 1.17nH, Asplund et al. 2009), the angular diameter distance to the cluster is dA, and z is the cluster redshift. The deprojected APEC normalizations are then converted to deprojected density in the usual fashion, assuming spherical symmetry and a constant density in each shell, by calculating the projected volumes, V, of each shell in the 2D annuli. When performing this conversion, we used a column density of 0.08 × 1022 cm−2 (from Kalberla et al. 2005), and using the abundance tables of Asplund et al. (2009).
Citation: Eckert et al. 2012
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Another interesting type of transient to compare DES17X1boj and DES16E2bjy with are the SN impostors. As shown in Fig. 3, SN2009ip has a short phase of re-brightening around the same phase as the secondary peak of the DES-SN transients, and its peak brightness (MV = −17.7; see e.g. Fraser et al. 2013) is similar to DES16E2bjy. However, several other features distinguish our double-peaked DES-SN transients from the SN impostors. While SN2009ip does show re-brightening, its light-curve evolution is clearly different from the DES transients. Additionally, other impostor candidates such as SN2015bh (see e.g. Elias-Rosa et al. 2016) and SN2016bdu (Pastorello et al. 2018) have very similar light curves with SN2009ip, but do not exhibit rebrightening. Furthermore, our photometric data also constrain the long-term variability of DES17X1boj to a level below what was seen in SN2009ip (Pastorello et al. 2013) and SN2016bdu (Pastorello et al. 2018) in the years before the brightest event (MV in range −13 to −14). For the more distant event DES16E2bjy, such outbursts would have been below our detection threshold. Regarding the spectroscopic data, the impostors exhibit strong, narrow H and He lines around peak brightness (see e.g. Fraser et al. 2013; Mauerhan et al. 2013; Pastorello et al. 2013). No such features are seen in either of the DES transients (see Figs 6 and 9), but it is possible that the lines are hidden in the noise.To investigate this, we estimated the limiting equivalent width (EW) for a Gaussian-shaped narrow H α line with $v$FWHM = 500  km s−1 in our spectra. H lines with similar widths are often seen in both SN impostors (Smith et al. 2011) and in SNe IIn (Taddia et al. 2013) where $v$FWHM ∼ 100−1000  km s−1 are typically measured. For the given configuration, we found limits of EW ≲ 5 Å for DES17X1boj and EW ≲ 14 Å for DES16E2bjy. In the case of SNe IIn, the line strengths are typically measured in several tens to hundreds of Ångstroms (EW≳ 40 Å; Smith, Mauerhan & Prieto 2014), and thus it is unlikely that narrow H α lines are hiding in the spectra. Due to both photometric and spectroscopic differences, it is unlikely that DES17X1boj and DES16E2bjy are events similar to SN impostors.
Citation: Pastorello et al. 2018
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The presumed WD cooling age is ≳5 Gyr. If it has a low mass, this age limit can be larger since after the Roche lobe detachment a proto-WD goes through the contraction phase until it reaches its cooling track (Istrate et al. 2014, 2016). The duration of this phase increases as the mass of the proto-WD decreases, and may last as long as ∼2 Gyr. The J0740 characteristic age of 3.75 Gyr (Table 1) is smaller than the WD age estimate. However, the observed pulsar period derivative and consequently its characteristic age can be biased by kinematic effects, i.e. the effects of the pulsar proper motion (Shklovskii effect; Shklovskii 1970), the acceleration towards the Galactic plane and the acceleration due to differential Galactic rotation (Nice & Taylor 1995). Using the J0740 proper motion value from Table 1, the Sun’s Galactocentric velocity and the distance (240 km s−1 and 8.34 kpc, respectively; Reid et al. 2014), we calculated these corrections to the pulsar period derivative: $\dot{P}_{\rm S}=3.0\times 10^{-21}$, $\dot{P}_{\rm G,\perp }=-1.6\times 10^{-22}$, $\dot{P}_{\rm G,p}=3.8\times 10^{-23}$ for the minimum and $\dot{P}_{\rm S}=6.9\times 10^{-21}$, $\dot{P}_{\rm G,\perp }=-2.2\times 10^{-22}$, $\dot{P}_{\rm G,p}=8.9\times 10^{-23}$ for the maximum pulsar distance estimates. The corresponding intrinsic characteristic ages are τi ∼ 5 and ∼8.5 Gyr, which are compatible with the cooling age.8 Thus, the considered binary system indeed can be very old and the presumed WD can be ultracool. This is not a unique situation. There are other examples of the objects with similar characteristics. One of them is the WD companion of PSR J0751+1807 (Bassa et al. 2006). Its colours (see Figs 2 and 3) indicate that the WD has a pure helium or mixed H/He atmosphere with a temperature T ∼ 3500–4300 K. Other examples are isolated ultracool white dwarfs WD J1102 (Hall et al. 2008; Kilic et al. 2012) and WD 0346+246 (Oppenheimer et al. 2001). These WDs have temperatures of about 3650 and 3300 K, respectively, and are best explained by the mixed atmosphere models (Gianninas et al. 2015).
Citation: Reid et al. 2014
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Our simulations were run using the AREPO (Springel 2010; Pakmor, Bauer & Springel 2011; Pakmor et al. 2016; Weinberger, Springel & Pakmor 2020) moving-mesh magnetohydrodynamics (MHD) code. The code solves for gravity coupled with MHD. The gravity solver uses the PM-tree method (Barnes & Hut 1986) and the MHD solver uses a non-static unstructured grid formed by performing a Voronoi tesselation of the domain. AREPO has been used to produce simulations of the Universe at a wide range of scales. At the largest scales, we have uniform volume cosmological simulations such as the Illustris (Genel et al. 2014; Vogelsberger et al. 2014a; Nelson et al. 2015; Sijacki et al. 2015) and Illustris-TNG  (Marinacci et al. 2018; Naiman et al. 2018; Nelson et al. 2018; Pillepich et al. 2018b; Springel et al. 2018; Nelson et al. 2019a,b; Pillepich et al. 2019) suites. These simulations have box sizes ranging from ∼50 to ∼300 Mpc and baryonic mass resolutions ranging from ∼105 to 107 M⊙. They have been largely successful in producing galaxy and SMBH populations consistent with observations, in Illustris (Vogelsberger et al. 2014b; Sales et al. 2015; Sijacki et al. 2015) and in TNG (Genel et al. 2018; Weinberger et al. 2018; Pillepich et al. 2018b; Donnari et al. 2019; Rodriguez-Gomez et al. 2019; Torrey et al. 2019; Habouzit et al. 2021; Übler et al. 2021). At the smallest scales, we have cosmological zoom simulation suites such as AURIGA (Grand et al. 2017) for individual milky-type galaxies, and HESTIA (High-resolutions Environmental Simulations of The Immediate Area) (Libeskind et al. 2020) for the Local Group. These simulations have been successful in reproducing observational results for the internal structures of galaxies  (Blázquez-Calero et al. 2020; Cautun et al. 2020; Grand et al. 2020). All these developments make AREPO an ideal tool for the development of black hole models, which require a reliable modelling of the necessary physics over a large dynamic range.
Citation: Vogelsberger et al. 2014a
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In addition, broad-band polarization observations provide essential information about the pulsar radio emission mechanism, beam geometry, and the Galactic magneto-ionic ISM. Pulsars are among the most highly polarized radio sources known (e.g. Lyne & Smith 1968; Gould & Lyne 1998), and the polarization varies with observing frequency (e.g. Manchester, Taylor & Huguenin 1973; Johnston et al. 2008; Dai et al. 2015), providing insight into the magnetospheric emission and propagation mechanisms. In addition, the linear polarization P.A.s across pulse phase can constrain the beam size and inclination angles, with respect to the pulsar’s rotation axis and our line of sight (LoS). For example, the rotating vector model (RVM) predicts a smooth ‘S’-shape, due to the projected vectors of the magnetic field lines as they sweep across our LoS (e.g. Radhakrishnan & Cooke 1969; Lyne & Manchester 1988; Johnston et al. 2007). Many pulsars show more complex P.A. curves, particularly discontinuities with rapid jumps of ≈90°, which suggests the presence of two orthogonal polarization modes (OPM; e.g. Manchester 1975; Backer, Rankin & Campbell 1976). Furthermore, circular polarization across the pulse is observed to either remain in the same hand or change sense (e.g. Radhakrishnan & Rankin 1990), which may be intrinsic to the emission mechanism or due to propagation effects (e.g. Han et al. 1998; Kennett & Melrose 1998). Additional diagnostics of magnetospheric effects have also been investigated, including variations in Faraday rotation measure (RM) and circular polarization across the pulse (e.g. Ramachandran et al. 2004; Karastergiou 2009; Noutsos et al. 2009; Ilie, Johnston & Weltevrede 2019). Although pulsars were discovered over 50 yr ago (Hewish et al. 1968), it is clear that current understanding and models of the emission mechanism are far from replicating this wide range of observed behaviour, as well as additional emission phenomena such as nulling and mode changing.
Citation: Lyne & Manchester 1988
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The left-hand panel of Fig. 3 shows the scatter plot of b1 and mass, coloured by $1+\delta _{5\,h^{-1}\,{\rm Mpc}}$. There is an obvious correlation visible, with a largely vertical trend in which b1 increases monotonically with $\delta _{5\,h^{-1}\,{\rm Mpc}}$. The symbols with errors show the median bias as a function of mass, in four bins of $\delta _{5\,h^{-1}\,{\rm Mpc}}$ and averaged over 10 realizations of the default box. It is clear that, at fixed $\delta _{5\,h^{-1}\,{\rm Mpc}}$, the trend of bias with halo mass is weak. This trend is consistent with previous results in the literature, which have shown that large-scale bias is more strongly correlated with halo-centric overdensity than it is with halo mass (see e.g. Abbas & Sheth 2007; Shi & Sheth 2018). The right-hand panel of the figure explores this further, showing the Spearman rank correlation coefficient between b1 and δR as a function of halo mass, for R = 2, 3, 5 h−1 Mpc. We see that the strength of the correlation is only a weak function of mass for each smoothing scale, but monotically increases with R. This increase with R is not surprising, since our estimator for b1 itself is ultimately measuring a large-scale halo-centric overdensity, so that b1 and δR are measuring essentially the same quantity for large R. To appreciate this point better, Fig. 4 shows a visualization of the haloes in a subvolume of our high-resolution box, with haloes shown as circles whose radii scale with R200b and whose colour scales with halo bias b1 as indicated by the colour bar. The panels focus on massive (top) and low mass haloes (bottom). We discuss some connections between halo-by-halo bias and gravitational redshift measurements (see e.g. Wojtak, Hansen & Hjorth 2011; Croft 2013; Alam et al. 2017) in Appendix D. In Appendix B1, we present analytical arguments that explain the size of the scatter in b1 at fixed mass and also qualitatively reproduce the trends seen in Fig. 3.
Citation: Shi & Sheth 2018
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Like normal elliptical galaxies, the analysis of the stellar populations in the inner regions of BCGs indicates that the bulk of their stars was formed rapidly in a very intense starburst at redshift z > 2 (Renzini 2006). However, despite sharing similar morphologies with normal massive ellipticals, in addition to red colours, old and metal-rich stellar populations and alpha-enhancements (Brough et al. 2008; Loubser et al. 2009; Donahue et al. 2010; Loubser & Sánchez-Blázquez 2012; Barbosa et al. 2016; Edwards et al. 2020), BCGs constitute a special category of objects with peculiar star formation histories (SFHs) seen from both observations (Tran et al. 2008; Barbosa et al. 2016) and models (Dubinski 1998; De Lucia & Blaizot 2007). The evolution of BCGs is significantly affected by their surrounding environments. Due to their central positions in the gravitational potential well of their host clusters, central cluster galaxies accrete stars and gas from satellite galaxies that orbit around them and fall in, developing extended light profiles. The more representative SFHs of their dominant stellar population include components from in situ star formation, and from the interaction with other galaxies and with the intracluster medium, where the outer regions in BCGs are continually assembling mass through minor mergers (Cooke et al. 2019). The stellar populations of a large sample of observed BCGs have been recently studied in Edwards et al. (2020), from the galaxy core into the intracluster light (ICL) out to 4 effective radii, finding old stellar populations of ∼13 Gyr and high metallicities [Fe/H] ∼0.3 in the galaxy cores, whereas the average age in the ICL is estimated to be slightly younger, ∼9.2 Gyr with lower metallicities −0.4  [Fe/H]  0.2 at 40 kpc. This broadly supports the idea of two-phase galaxy formation, with the BCG cores and inner regions formed faster and earlier than the outer regions that have formed more recently, or have accreted mass afterwards through galaxy mergers and thereby also increasing in size (Oser et al. 2010; Kubo et al. 2017; Cooke et al. 2019).
Citation: Dubinski 1998
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Studies of SMGs over the past few tens of years have provided valuable insights into their properties. These include the redshift distribution (e.g. Chapman et al. 2005; Aretxaga et al. 2007; Wardlow et al. 2011; Yun et al. 2012; Smolčić et al. 2012; Simpson et al. 2014, 2017; Zavala et al. 2014; Miettinen et al. 2015a; Chen et al. 2016a; Strandet et al. 2016; Danielson et al. 2017; Brisbin et al. 2017), spatial clustering and environment (e.g. Ivison et al. 2000; Blain et al. 2004; Aravena et al. 2010; Hickox et al. 2012; Miller et al. 2015; Chen et al. 2016b; Wilkinson et al. 2017; Smolčić et al. 2017), merger incidence (e.g. Conselice et al. 2003), and circumgalactic medium (Fu et al. 2016). Regarding the intrinsic physical characteristics of SMGs, the properties studied so far include the sizes and morphologies (e.g. Swinbank et al. 2010; Menéndez-Delmestre et al. 2013; Aguirre et al. 2013; Targett et al. 2013; Chen et al. 2015; Simpson et al. 2015; Ikarashi et al. 2015; Miettinen et al. 2015b, 2017b,c; Hodge et al. 2016), panchromatic spectral energy distributions (SEDs; e.g. Michałowski et al. 2010; Magnelli et al. 2012; Swinbank et al. 2014; da Cunha et al. 2015; Miettinen et al. 2017a), stellar masses (e.g. Dye et al. 2008; Hainline et al. 2011; Michałowski et al. 2012; Targett et al. 2013), gas masses (e.g. Greve et al. 2005; Tacconi et al. 2006, 2008; Engel et al. 2010; Ivison et al. 2011; Riechers et al. 2011; Bothwell et al. 2013; Huynh et al. 2017), gas kinematics (e.g. Alaghband-Zadeh et al. 2012; Hodge et al. 2012; Carilli & Walter 2013; Olivares et al. 2016), and active galactic nucleus (AGN) incidence (Alexander et al. 2003, 2005; Laird et al. 2010; Johnson et al. 2013; Wang et al. 2013). The role played by SMGs in a broader context of galaxy formation and evolution has also been investigated through models (e.g. Baugh et al. 2005; Fontanot et al. 2007; Davé et al. 2010; González et al. 2011; Hayward et al. 2013) and observational approach (e.g. Swinbank et al. 2006; Toft et al. 2014; Simpson et al. 2014).
Citation: Conselice et al. 2003
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For the magnetic field configurations considered in this work, the polarization angle can only change exactly by Δϕ = 90○ and a gradual change of the PA is not possible. There are tantalizing hints of a 90○ change in the PA in some of the GRBs, as discussed above, but the results are not yet conclusive. The result presented by Sharma et al. (2019) where the PA changes by 90○ twice over the emission is again very exciting as such a change over a single pulse can only occur for the Btor field configuration. The only difficulty, according to the modelling done here, is that both 90○ changes occur in the decaying tail of the pulse when high latitude emission dominates the flux. In the measurement presented by Sharma et al. (2019), the PA shows a change close to the peak of the emission. Another scenario in which a 90○ PA change can be obtained includes contribution from multiple pulses and when the LOS is close to the edge of the jet, such that θobs ≈ θj, along with a change in bulk Γ between the pulses which would change ξj = (Γθj)2. Alternatively, such a change in the PA can be obtained due to magnetic reconnection, e.g. in the ICMART model (Zhang & Yan 2011), where the local magnetic field orientation, which is orthogonal to the wave vector of the emitted photon, itself changes by 90○ as the field lines are destroyed and reconnected in the emission region (Deng et al. 2016). To obtain a change in the PA other than Δϕ = 90○ or to get a gradually changing PA the condition for axisymmetry must be relaxed and the magnetic field configuration or orientation in the emission region must change. One possibility is that if the different pulses that contribute to the emission arise in a ‘mini-jet’ within the outflow (e.g. Shaviv & Dar 1995; Lyutikov & Blandford 2003; Kumar & Narayan 2009; Lazar, Nakar & Piran 2009; Narayan & Kumar 2009; Zhang & Yan 2011). In this case, the different directions of the mini-jets or bright patches w.r.t. the LOS (e.g. Granot & Königl 2003; Nakar & Oren 2004) would cause the PA to also be different between the pulses even for a field that is locally symmetric w.r.t the local radial direction (e.g. B⊥ or B∥) as well as for fields that are axisymmetric w.r.t to the centre of each mini-jet (e.g. a local Btor for each mini-jet). Finally, broadly similar result would follow from an ordered field within each mini-jet (Bord) which are incoherent between different mini-jets. Time-resolved measurement in such a case would naturally yield a time-varying PA. Alternatively, as shown by Granot & Königl (2003) for GRB afterglow polarization, a combination of an ordered field component (e.g. Bord) and a random field, like B⊥, can give rise to a time-varying PA between different pulses that, e.g. arise from internal shocks. The ordered field component here would be that advected from the central engine and the random field component can be argued to be shock-generated. Notice that the ordered field component should not be axisymmetric in order for the PA to smoothly vary.
Citation: Zhang & Yan 2011
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