adsabs/FOCAL huggingface dataset:
In the single cloud simulations presented in Paper I and Paper II, the system was treated in isolation, i.e. with no external forces acting upon it. In reality, such a binary would be placed deep in the potential well of a galaxy, where stars and dark matter exert their gravitational influence. To mimic the presence of the galactic spheroid, we include an external potential with a Hernquist profile (Hernquist 1990), which can be written as
(1)
\begin{eqnarray*}
\rho (r) = \frac{M_*}{2\pi}\frac{a_*}{r}\frac{1}{(r+a_*)^3},
\end{eqnarray*}
and an enclosed mass given by
(2)
\begin{eqnarray*}
m(r) = M_*\frac{r^2}{(r+a_*)^2},
\end{eqnarray*}
where M* and a* are scaling constants that represent the total mass of the spheroid and the size of core, respectively. Based on a typical MBH–Mbulge relation (Magorrian et al. 1998) and a radius-to-stellar-mass relation (Dabringhausen, Hilker & Kroupa 2008), we choose MH = 4.78 × 102M0 and rH = 3.24 × 102a0, thus implying
(3)
\begin{eqnarray*}
m(a_0) \approx 5\times 10^{-3} M_0.
\end{eqnarray*}
As a consequence, this external force represents only a small perturbation to the dynamics of the interaction that is still dominated by the binary’s gravitational potential. Moreover, because this external potential is spherically symmetric, orbits experience precession only, where energy and angular momentum are conserved. In principle, this precession could enhance stream collisions, prompting more gas onto the binary, although the time-scales are too long with respect to the frequency of cloud infall, which is the dominant effect in our models. Based on this, we do not expect the oscillations induced by this potential to have a secular effect in the overall evolution of the system during the stages modelled. In practice, this potential maintains the binary close to the centre of the reference frame by applying a restoring force when it drifts away due to the interaction with the incoming material. It is important to mention that the gas also feels this external force.
Citation: Dabringhausen, Hilker & Kroupa 2008
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For the new observations described in Sect. 3, the spectra are renormalised by applying a linear fit to two wavelength regions, 6455–6559 Å and 6567–6580 Å, on either side of the Hα line. The value for pEW (Hα) is measured over the wavelength range 6560–6565 Å. The selected wavelength range is sufficiently narrow to exclude nearby spectral lines and sufficiently broad to measure the Hα line of a fast rotating star. The value of pEW(Hα) is calculated from

(1)

${\rm{pEW}(H\alpha)} = \int^{\lambda_2}_{\lambda_1}
\left(1-\frac{F(\lambda)}{F_{\rm{pc}}}\right){\rm{d}}\lambda,$pEW(Hα)= ∫ λ1λ2 1-F(λ)Fpc dλ, 


where Fpc is the average of the median flux in the pseudo-continuum in the ranges [6545:6559] and [6567:6580], λ1  = 6560Å, λ2  = 6565Å, and the error is determined with the method of Vollmann & Eversberg (2006), which is applied as follows:

(2)

$\sigma_{\rm{pEW}} = \frac{\mathrm\Delta \lambda -
\rm{pEW(H\alpha)}}{\rm{S/N}} \sqrt{1 + \frac{F_{\rm{pc}}}{F_{1,2}}},$σpEW=Δλ-pEW(Hα)S∕N1+  Fpc   F1,2, 

where Δλ = λ2 − λ1 and F1,2  is the mean flux in the wavelength range between λ1 and λ2. For Hα active stars, i.e. where pEW(Hα) is negative, the normalised Hα luminosity can be expressed as

(3)

$\log \left(\frac{L_{{\rm{H}}\alpha}}{L_{\rm{bol}}}\right) = \log \chi
+ \log (-{\rm{pEW}}({\rm{H}}\alpha)),$logLHαLbol = logχ+ log(-pEW(Hα)), 

where log χ is given as a function of the effective temperature (e.g. Reiners & Basri 2008). Lines with Hα in absorption have positive pEW(Hα) values and lines with Hα in emission have negative pEW(Hα) values. The minimum level of emission in Hα that we are sensitive to is pEW(Hα) ≤−0.5Å, which is the definition for an active star in this work and is indicated by the term Hα active. This detection threshold was determined by visually inspecting the spectra and is consistent with values obtained by Newton et al. (2017) and West et al. (2015). The values derived from the new observations are tabulated in Table A.2.
Citation: Vollmann & Eversberg (2006)
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In this work, we consider four different galaxy models from Smirnov & Sotnikova (2018). Full details of the simulations can be found in that work and we refer an interested reader to it. Here, we briefly describe some important aspects of the simulations. Initially, each model consists of an axisymmetric exponential disc:
(11)$$\begin{eqnarray}
\rho (R,z) = \frac{M_\mathrm{d}}{4\pi R_\mathrm{d}^2 z_\mathrm{d}} \exp \left(-\frac{R}{R_\mathrm{d}}\right) \operatorname{sech}^2\left(\frac{z}{z_\mathrm{d}}\right) \, ,
\end{eqnarray}$$where Md is the total mass of the disc, Rd is the disc scale length, and zd is the disc scale height, plus spherically symmetric dark halo of NFW-type (Navarro, Frenk & White 1996). The halo is characterized by the ratio Mh(r  4Rd)/Md, where Mh(r  4Rd) is the dark halo mass inside the sphere with a radius of 4Rd. One model also includes a Hernquist type bulge (Hernquist 1990):
(12)$$\begin{eqnarray}
\rho _\mathrm{b}(r) = \frac{M_\mathrm{b}\, r_\mathrm{b}}{2\pi \, r\, (r_\mathrm{b} + r)^3} \, ,
\end{eqnarray}$$where rb is the scale parameter and Mb is the total bulge mass. Disc and halo components are represented by several millions of particles (see Table 1). Bulge particle number is chosen such that the mass of one particle from the bulge is equal to the mass of one particle from the disc. Some important physical parameters of the models are specified in Table 1. The initial equilibrium state of each multicomponent model was prepared via script mkgalaxy (McMillan & Dehnen 2007) from the toolbox for N-body simulation NEMO (Teuben 1995). Evolution of the models was followed for about 8 Gyr using the fastest N-body code for one CPU gyrfalcON (Dehnen 2002). Each model gives rise to a bar after 1−2 Gyr from the beginning of the simulation. Each bar gradually thickens in the vertical direction (clear buckling events can occur depending on the model) and takes a B/PS shape if seen side-on. Fig. 1 shows the end-state of the bulgeless model with μ = 1.5 and Q(2Rd) = 1.2. This model is our fiducial or ‘main’ model. On the example of this model, we consider below how various projection effects affect the extracted parameters of the B/PS bulge. For each of the models, we prepared a set of Flexible Image Transport System (FITS) images obtained from the corresponding density distribution of disc/bulge particles. Such images can then be decomposed using a usual decomposition procedure analogous to that used for images of real galaxies.
Citation: Navarro, Frenk & White 1996
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In order to establish the completeness and purity of the RR Lyrae stars confirmed by the SOS Cep&RRL pipeline and to estimate the number of new discoveries by Gaia, we performed a deep and careful comparison with the literature. As a first step, the catalogue of 140 784 confirmed sources was cross-matched against all major catalogues of known RR Lyrae stars that are available. We primarily used the OGLE catalogues for RR Lyrae stars (version IV of the survey, Soszyński et al. 2014, 2016), but we also used RR Lyrae stars by CTRS (Drake et al. 2013a,b, 2014, 2017; Torrealba et al. 2015), ASAS (Pojmanski 1997; Richards et al. 2012), ASAS-SN (Jayasinghe et al. 2018), ATLAS (Tonry et al. 2018), IOMC (Alfonso-Garzón et al. 2012), LINEAR (Palaversa et al. 2013), NSVS (Kinemuchi et al. 2006), Pann-Stars (PS1 Sesar et al. 2017), and from the works based on Kepler/K2 (Debosscher et al. 2011; Nemec et al. 2011; Molnár et al. 2015a,b, 2016) and on the Simbad database (Wenger et al. 2000). These cross-matches returned a list of 88 578 known RR Lyrae stars in our sample of 140 784 stars. The SOS Cep&RRL confirmed RR Lyrae stars were also cross-matched against catalogues of candidate RR Lyrae stars discovered by the VVV survey (Gran et al. 2016; Minniti et al. 2017; D. Minniti, priv. comm.) in the MW disc and bulge. This returned 319 VVV cross-identified sources in the MW disc and 222 in the MW bulge. We thus confirm these VVV candidates. For known RR Lyrae stars in GCs, the main reference was the catalogue of Clement et al. (2001), which was updated to the latest literature as described in Garofalo et al. (in prep.). For variables in dSphs, we used the following references: Kaluzny et al. (1995), Clementini et al. (2005), Kinemuchi et al. (2008), Dall’Ora et al. (2012) and Garofalo et al. (2013). These latter cross-matches returned a list of 1986 further known RR Lyrae stars. At the end of this cross-match procedure, of the 140 784 RR Lyrae stars that are confirmed by the SOS Cep&RRL pipeline, 90 564 were shown to be known previously, and 50 220 are new discoveries by Gaia.
Citation: Torrealba et al. 2015
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Citation: Minniti et al. 2017
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In Figure 7, we find a trend between 





 and SFR over about 3 orders of magnitude in far-IR luminosity/SFR. The solid line shows the best-fit (a logarithmic linear least-squares bisector fit) correlation for the whole sample of QSOs, with a power law of 





. The Spearman rank correlation coefficient for this correlation is 0.77 with a high significance (P  10−5) but substantial scatter. Our result is in general agreement with the correlation found between AGN activity and star formation, i.e., 





 (α ∼ 1.1–1.7; see Netzer 2009; Chen et al. 2013; Hickox et al. 2014; Duras et al. 2017; Dai et al. 2018; Izumi et al. 2019 and references therein). As noted in previous works (see e.g., Dai et al. 2018), the variation of slope might be attributed to different sample compositions and/or methods of analysis. However, all of these studies, including our own, reveal a significant trend between the SFR and BH accretion spanning a wide range of luminosity, implying that there may be a direct connection between the AGN and star formation activities over galaxy evolution timescales. In addition, there is evidence that SMBHs have grown in step with their host galaxies since z ∼ 2 (Daddi et al. 2007; Mullaney et al. 2012). The median value of 





/SFR is 6.0 × 10−3 for IR QSOs, consistent with the value derived in Xia et al. (2012). In contrast, the 





/SFR values for high-z QSOs are found to be about a factor of 10 higher (a median of 7.3 × 10−2) than the local IR QSOs. This is consistent with the “overmassive” BH revealed for z > 5 QSOs (Walter et al. 2004; Wang et al. 2010, 2013, 2016), for which a plausible interpretation is likely related to the different efficiency of gas accretion to the central SMBHs, i.e., faster gas consumption in the most massive SMBHs. Similar results have been reported by Hao et al. (2008), who found a trend that the SFR increases with the accretion rate for both low- and high-redshift IR-luminous QSOs, and the relative growth of BHs and their host spheroids may depend on the intensity of QSO activities.
Citation: Netzer 2009
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There are several possible physical processes to reconcile these discrepancies between the models and the observations at z ∼ 10–13. As discussed in Harikane et al. (2021b), less efficient mass quenching and/or lower dust obscuration than assumed in the models can explain the existence of these UV-bright galaxies. Active galactic nucleus (AGN) activity may also boost the UV luminosity in these galaxies. Previous studies indicate that the AGN fraction starts to increase at M
UV ≃ −22 mag (Ono et al. 2018; Stevans et al. 2018; Adams et al. 2020; Harikane et al. 2022; see also Piana et al. 2022). If we assume that the UV luminosities of HD1 and HD2 are solely powered by black holes, the inferred black hole masses are ∼108
M
⊙, assuming accretion at the Eddington rate (Pacucci et al. 2022), in accordance with expectations for high-redshift quasars (see, e.g., Haiman & Menou 2000 and Willott et al. 2010). In addition, note that a ∼108
M
⊙ black hole at z ∼ 12 could be the progenitor of z ∼ 7 quasars, as the growth time to reach a mass of 109–1010
M
⊙, typical of z > 6 quasars detected thus far, is shorter than the cosmic time between z = 12–13 and z = 7, for an Eddington-limited accretion. It is also possible that the observed bright sources at z ∼ 10–13 are galaxies in a short-time starburst phase that is not captured in the models whose outputs are averaged over a time interval (see also Dayal et al. 2013). Finally, a top-heavier IMF would explain the discrepancies by producing more UV photons at the same stellar mass. It is possible that these bright galaxies (especially HD1 and HD2) are merging systems that are not resolved in the ground-based images. However, even if they are major mergers, the UV luminosity will decrease only by a factor of a few, which would not explain the discrepancy at z ∼ 13 (see also discussions in Harikane et al. 2022; Shibuya et al. 2022). In any case, if these bright z ∼ 10–13 galaxies are spectroscopically confirmed, the discrepancies will motivate the exploration of new physical processes that are responsible for driving the formation of these bright galaxies in the early universe.
Citation: Pacucci et al. 2022
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For the distance to the source of HESS J1825−137 of 4 kpc (based on dispersion measure using the models for Galactic electrons by Taylor & Cordes 1993; Cordes & Lazio 2002), the measured angular size of the latter corresponds to the 70 pc linear size of the gamma-ray production region. Although the gamma-ray image deviates from the spherically symmetric shape; below for simplicity we will assume that the radius of the source is 35 pc. The detection of a Hα rim at a distance of 





 from the pulsar PSR J1826-1334 has been interpreted as a signature of the progenitor SNR (see Stupar et al. 2008; Voisin et al. 2016). As illustrated in Figure 4, in the case of an ISM density gradient, the measured radius does not coincide with the radius, Rsnr . If the pulsar is still located inside the SNR then the SNR radius cannot be significantly smaller than the observed distance: 





. Thus, with a factor of two uncertainty one can estimate the radius based on Sedov’s solution:
40





where 





 are the density, the hydrogen number density, and the proton mass, respectively. Thus, the SNR shell can be located at the distance of 





 pc, provided that the following condition is fulfilled:
41





where the numerical value corresponds to 





. The ejecta energy at SN type II is constrained by 





, while the age of the source is limited by 





 (for 





). Thus, Sedov’s solution is consistent with the observed size of the SNR when 





. Note that de Jager & Djannati-Ataï (2009) derived a somewhat smaller upper limit for 





 assuming the braking index n = 2. This upper limit seems to be below the typical density of the interstellar gas in the Galactic Plane. Moreover, Voisin et al. (2016) reported the presence of several molecular clouds in the small angular proximity to the nebula with an average number density 





 and characteristic size 





. It is likely that one of these clouds is responsible for the anisotropic expansion of the nebula, thus it should be located close to the nebula. The gas density in molecular clouds is expected to follow the King’s profile:
42





Thus, the density to the south of the pulsar can hardly be as low as it is required by Sedov’s solution. Instead, it should be comparable to the upper limit of 





 obtained by Voisin et al. (2016).
Citation: Stupar et al. 2008
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In some cases, the precursor emission has a nonthermal spectrum, especially GRB111117510 and GRB160804180 with ΔBIC ≳ 6. These cases may be explained by the NS magnetospheric interaction model (assuming that the sources are nearby). For NS mergers with the surface magnetic field 





 for the primary NS, the typical spectrum may be approximately described by a synchrotron radiation spectrum of a photon index around −2/3 peaking at ∼MeV, because of the effect of synchrotron-pair cascades (Wang et al. 2018a, 2018b). Such a model can well explain the photon indices and peak energies of the nonthermal precursor bursts, e.g., GRB111117510, GRB140209313, and GRB160804180 (Wang et al. 2018b). The precursor emission time for this magnetospheric interaction model roughly coincides with the gravitational-wave radiation chirp signal time. So the waiting time between the precursor and the main burst should correspond to the time delay between the GW signal and the SGRB signal. This timescale consists of three parts (Zhang 2019): the time (





) for the jet to be launched by the central engine, the time (Δtbo) for the jet to propagate through and break out from the circumburst medium, and the time (ΔtGRB) for the jet to reach the energy dissipation radius (e.g., the photospheric radius or the internal shock radius). The last term is 





, while the first two terms depend on the jet-launch models. According to the Table 1 in Zhang (2019), for most models, 





 = 0.01–1 s. Consequently, one would also expect 





 ∼ 





. An exception is the SMNS/SNS magnetic model, in which a uniform-rotation-supported supramassive NS (SMNS) is formed after the NS merger, which subsequently becomes a stable NS (SNS). In this model, the waiting time is dominated by the term 





, which is mainly contributed by the time needed to clean the environment to launch a relativistic jet (Metzger et al. 2011; Zhang 2019). In this case, one expects 





 ≫ 





. In our sample, we find most events satisfy 





 ∼ 





, except GRB191221802, which has 





/





 ≈ 52 and 





 s. We also notice that for GRB090510016, Troja et al. (2010) found two precursors in the Swift data, but only the second precursor can be found in Fermi data (consistent with our results). Its first precursor is found to be of 





/





 ≈ 40 and 





 ≈ 12 s, while its second precursor in our analysis is consistent with the photospheric radiation of the fireball. Therefore, its first precursor with a long waiting time (





/





 ≫ 1) could originate from NS magnetospheric interaction, and such long waiting times are caused by the jet-launch mechanism in the SMNS/SNS magnetic model. In conclusion, according to this model, an SNS engine might have been formed after the merger in events with 





/





 ≫ 1, e.g., GRB090510016 and GRB191221802.
Citation: Zhang 2019
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Citation: Zhang (2019)
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Citation: Zhang 2019
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For the first time, we detected [C ii] 158-μm emission from a GRB host galaxy at z > 2. This is the second detection of [C ii] 158-μm emission among known GRB host galaxies, following GRB 980425 (Michałowski et al. 2016). The [C ii] 158-μm fine structure line is the dominant cooling line of the cool interstellar medium, arising from photodissociation regions (PDR) on molecular cloud surfaces. It is one of the brightest emission lines from star-forming galaxies from FIR to metre wavelengths, almost unaffected by dust extinction. [C ii] 158-μm luminosity, L[C II], has been discussed as an indicator of SFR (e.g. Stacey et al. 2010). If L[C II] scales linearly with SFR, the ratio to FIR luminosity, L[C II]/LFIR, is expected to be constant, since LFIR is a linear function of SFR (e.g. Kennicutt 1998a). However, LC II/LFIR is not constant, but declines with increasing LFIR, known as the ‘[C ii] deficit’ (e.g. Luhman et al. 1998, 2003; Malhotra et al. 2001; Sargsyan et al. 2012; Díaz-Santos et al. 2013, 2017; Spilker et al. 2016). The [C ii] deficit persists when including high-z galaxies (e.g. Stacey et al. 2010; Wang et al. 2013; Rawle et al. 2014). In Fig. 5, we compare the [C ii] deficit in the GRB 080207 host and other star-forming galaxies. Two GRB hosts are shown by stars: GRB 080207 (orange star) and 980425 (blue star). The comparison sample is compiled from the literature up to z ∼ 3 (Malhotra et al. 2001; Cormier et al. 2010, 2014; Ivison et al. 2010; Stacey et al. 2010; Sargsyan et al. 2012; Farrah et al. 2013; Magdis et al. 2014; Brisbin et al. 2015; Gullberg et al. 2015; Schaerer et al. 2015). Active galactic nuclei are separated from star-forming galaxies based on either (i) the explicit description in the literature or (ii) EWPAH 6.2μm  0.1 (Sargsyan et al. 2012). As reported by previous studies (e.g. Maiolino et al. 2009; Stacey et al. 2010), high-z galaxies are located at a different place from local galaxies in the L[C II]/LFIR–LFIR plane.
Citation: Sargsyan et al. 2012
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Citation: Sargsyan et al. 2012
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Citation: Sargsyan et al. 2012
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Jiang et al. (1975) estimated the infrared band strength of CO ice deposited at high pressure compared to modern setups: their deposition rate of 0.5 to 2 μm requires a pressure about 16 to 66 times higher than typical experiments performed at 1 × 10−6 mbar during deposition. To obtain this band strength, Jiang et al. (1975) also adopted a literature value of the CO ice density measured at a relatively high temperature, 30 K (Vegard 1930). According to Luna et al. (2022) and this work, the CO ice density depends on the temperature and pressure during deposition, and therefore, the value of the CO infrared band strength in Jiang et al. (1975) needs a revision. We propose to use $\mathcal {A}(\rm CO)$  = (8.7 ± 0.5) × 10−18 cm  molecule−1 for future column density estimations. This value is valid in the experimental range from 11 to 28 K deposition temperatures investigated in this work, for which no variations of the integrated absorbance area and sticking probability were found (Cazaux et al. 2017). The CO ice column density values reported in previous experimental and observational papers might thus be underestimated, they would be about 23  per cent lower than the actual value. Most of the CO ice column densities reported in the literature adopted a band strength of $\mathcal {A}(\rm CO)$  = 1.1 × 10−17 cm  molecule−1 (Jiang et al. 1975), they would need to be multiplied by a factor of 1.3 for correction. An example is the number of monolayers on the surface, or just beneath the surface of the ice, involved in the photodesorption of CO, i.e. N  = 5 × 1015 molecules cm−2 or about 5 monolayers (ML) where 1 ML  = 1 × 1015 molecules cm−2 (Muñoz Caro et al. 2010; Fayolle et al. 2011; Chen et al. 2014). After correction, this becomes 6.5 ML. Considering our average density value of CO ice deposited at 11 K, 0.837 g cm−3, and equation (24), it is found that the thickness of one monolayer is 0.56 nm, and 3.36 nm for the top 6.5 ML of ice. The UV photons emitted by the MDHL that are absorbed deeper than 3.36 nm would not lead us to photodesorption of CO molecules.
Citation: Cazaux et al. 2017
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