adsabs/FOCAL huggingface dataset:
In Fig. 6, we plot the [C/O] ratios dependence on [O/H] for the different stellar populations. This figure serves to evaluate the balance between the two different elements directly with the evolution of one of them, which in this case has a well-known, single production site. Here, we chose to only show the ratios with the oxygen abundances from the 6158 Å indicator as it was shown to present less dispersion and be moretrustworthy (Bertran de Lis et al. 2015). Nevertheless, for completeness, we present the figure with the forbidden oxygen line in the appendix (Fig. A.1). Previous works in the literature have shown an increase of [C/O] ratios as [O/H] increases (e.g. Bensby & Feltzing 2006; Nissen et al. 2014; Amarsi et al. 2019), but our ratios present a quite large dispersion that together with the shorter range in [O/H] prevents us from seeing a clear behaviour. If we focus on the results with the 6158 Å line, the [C/O] ratios present a general flat trend (see the upper panel of Fig. 6 with the running mean for each population), as [O/H] increases to then clearly decrease at [O/H] ≳ 0 dex, both for thin-disk and hαmr stars. To better evaluate the significance of this apparent trend, we applied a weighted least squares fit to the [C/O] values of thin disk and hαmr stars at [O/H] ≳ 0 dex. We then used the values of the slopes and the associated uncertainties to assess the significance of the fits. The p-values come from the F-statistics that tests the null hypothesis that the data can be modelled accurately by setting the regression coefficients to zero. The resulting p-values are 3.3 e−2 and 1.6 e−2 for the thin disk and hαmr stars, meaning that the correlations are significant. This trend is in agreement with the previously mentioned turning point of [C/O] at [O/H] ~ 0.0 dex (Carigi et al. 2005). However, this is in contrast with the flattening at super-solar [O/H] presented by Nissen et al. (2014) or the increasing trend found by Franchini et al. (2021) which might be caused by the use of different oxygen indicators. On the other hand, the [C/O] ratios for thick-disk stars present no trend but show a clear offset in its running mean with respect to the thin disk as also reported by Amarsi et al. (2019). This separation between the thick and thin disk, also observed for other elements, supports the different formation episodes of both populations (Chiappini et al. 2001; Amarsi et al. 2019).
Citation: Bensby & Feltzing 2006
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HATLAS12-00 had already been identified as a candidate gravitationally lensed galaxy as a result of its high submm flux (i.e. F500 > 100 mJy), red Herschel colours and the lack of a bright optical or radio counterpart (see e.g. Negrello et al. 2010 for a discussion of the selection of lens candidates in H-ATLAS and other Herschel surveys). This source was therefore observed spectroscopically in the submm. A CO spectroscopic redshift of 3.26 was first suggested by Z-spec (Bradford et al. 2004) observations, then subsequently confirmed by observations by the CARMA interferometer (Leeuw et al., in preparation) and the Zpectrometer instrument (Harris et al. 2007) on the Greenbank Telescope (Harris et al. 2012; see also Fu et al. 2012). Additional followup observations in the optical, near-IR, submm and other wavelengths were targeted at the lensed z = 3.26 source and the foreground objects responsible for the lensing, resulting in detailed analyses of this lensing system by Fu et al. (2012) and Bussmann et al. (2013). Their conclusions are that the z = 3.26 source HATLAS12-00 is subject to gravitational lensing, with a magnification of 9.6 ± 0.5 in both the submm continuum and CO, and 16.7 ± 0.8 in the K′ band, by two foreground galaxies, one at a spectroscopically determined redshift of 1.22, and another with photometry suggesting that it lies at a similar redshift. The submm photometry of HATLAS12-00 at 890 μm acquired with the Submillimeter Array (SMA) as part of this programme (Fu et al. 2012; Bussmann et al. 2013) is fully consistent with the 870 μm and 850 μm fluxes derived for this source from the LABOCA and SCUBA2 data to be presented here. The spectral energy distribution (SED) of the lensed source, after correcting for the lensing amplification, is well matched by the optically thick SED model for Arp220 from Rangwala et al. (2011), with a lensing-corrected far-IR luminosity of 1.2 ± 0.2 × 1013 L⊙, and an implied star formation rate of 1400 ± 300  M⊙ yr−1. In many ways the unlensed properties of this object match those of the broader population of bright submm selected galaxies first discovered by the SCUBA submm imager (see e.g. Chapman et al. 2005; Clements et al. 2008; Michałowski, Hjorth & Watson 2010). The unlensed 870 μm flux of this object would be ∼7.7 mJy.
Citation: Fu et al. 2012
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Citation: Fu et al. 2012
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Citation: Harris et al. 2012
Citation function: Similarities; Similarities; Similarities; Similarities
Citation: Fu et al. (2012)
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Star formation is an inefficient process, as evidenced by observed gas depletion times,1 which are two orders of magnitude above the dynamical time, both in galaxies (e.g. Leroy et al. 2017; Utomo et al. 2018), and in individual giant molecular clouds (GMCs) (e.g. Krumholz & Tan 2007; Evans, Heiderman & Vutisalchavakul 2014; Heyer et al. 2016; Pokhrel et al. 2020; Hu et al. 2022). Theoretical models explain this inefficiency through a combination of mechanisms that provide support against gravitational collapse, including turbulence, magnetic fields, stellar feedback, and dynamical stabilization (Krumholz & McKee 2005; Ostriker, McKee & Leroy 2010; Federrath & Klessen 2012; Krumholz, Klein & McKee 2012b; Federrath 2013b; Padoan et al. 2014; Federrath 2015; Burkhart 2018; Meidt et al. 2018; Krumholz & Federrath 2019; Evans, Kim & Ostriker 2022). Recent progress in both theory and observations have highlighted the pivotal role that feedback, especially due to massive (main-sequence) stars, plays in star/star-cluster formation (Krumholz et al. 2014; Krumholz, McKee & Bland-Hawthorn 2019), and the lifecycle of GMCs (see Chevance et al. 2020, 2022a for reviews). This massive-star feedback has been suggested to be largely responsible for limiting the integrated star formation efficiency (ϵ*) to low values in typical environments, where ϵ* is given by
(1)$$\begin{eqnarray}
\epsilon _* = \frac{M_{*}}{M_{\mathrm{gas}}},
\end{eqnarray}$$which quantifies the net efficiency of star formation over the lifetime of a GMC, i.e. the ratio of the final stellar mass M* and the available gas mass in the parent molecular cloud Mgas. Feedback achieves this by (i) disrupting GMCs in order ∼ unity dynamical time-scales, through the momentum and energy carried by feedback processes (e.g. Grudić et al. 2018), and (ii) driving turbulent motions that could further provide support against collapse (e.g. Mac Low & Klessen 2004; Krumholz, Matzner & McKee 2006; Elmegreen 2009; Gritschneder et al. 2009; Federrath et al. 2010; Wibking, Thompson & Krumholz 2018; Gallegos-Garcia et al. 2020; Menon, Federrath & Kuiper 2020; Menon et al. 2021).
Citation: Krumholz & McKee 2005
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Citation: Meidt et al. 2018
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The radio versus optical DCF peaks at non-zero lags (τdelay) with the optical emissions leading the radio emissions, implying that the radio and optical emission regions are not cospatial with the optical/IR emission region being closer to the base of the jet. This is consistent with the observation that optical emission regions are smaller than radio emission regions (Table 8). These observations are in accordance with standard shock-in-jet models where higher frequencies are emitted closer to the shock front while lower frequencies are produced from larger volumes that extend farther away from the shock (e.g., Marscher & Gear 1985; Marscher et al. 2008). This could also be understood as a manifestation of the position offset of optically thick features that can be interpreted as a frequency-dependent shift of the self-absorbed core of the jet (e.g., Lobanov 1998; Pushkarev et al. 2012). The linear separation of the V and 37 GHz emission region can be estimated using the relation (Pushkarev et al. 2010; Lisakov et al. 2017):
10





where βapp is the apparent jet speed and θ is the viewing angle. Using a range of 15–100 days for τdelay from Table 6, the maximum linear separation between the emission regions (





) is estimated to be in the range of 4.06 (for Segment 6) to 27.04 pc (for Segment 1) and the corresponding projected separation varies from 0.18 to 1.20 pc using a viewing angle of θ = 13. The resulting angular separation is 0.022–0.151 mas. The simplest jet geometry is that of a conical jet. It cannot, however, explain the change in the separation between emission regions. In a conical jet geometry, the distance of an emission region from the central engine can be calculated using 





 (Abdo et al. 2011) assuming the emission region fills the cross-section of the jet and the opening angle 





. The obtained dce is given in Table 8 and the separation comes out to be 1.4 pc. Thus, the conical jet model also severely underestimates the separation between the emission regions, as it does not take into account the jet collimation. An alternative model is that of an inhomogeneous curved jet, where synchrotron radiation of decreasing frequency is produced in an outer and wider jet region that changes orientation with time. It is possible that the long-term variability behavior of 3C 454.3 during our extended observation is dominated by geometrical effects that also lead to temporal delays between the radio and optical bands.
Citation: Pushkarev et al. 2010
Citation function: Uses
In local galaxies, the ISM conditions are often described by some physical quantities such as ionization parameter (q), gaseous metallicity (Z) and electron density (ne). At high redshift, the ionization parameter is raised by a large flux of ionizing photons in ISM originated from hot O, B stars due to intensive star formation in relatively small galaxies. Previous studies suggest a high ionization parameter of SF galaxies at z > 2 compared to that of local galaxies (Erb et al. 2010; Nakajima et al. 2013; Masters et al. 2014; Nakajima & Ouchi 2014). Secondly, the chemical abundance of SF galaxies at z ∼ 2 is lower by 0.1–0.3 dex for a given stellar mass compared to those at low-z (Erb et al. 2006a; Sanders et al. 2014; Steidel et al. 2014). This leads to more compact and hotter O, B stars due to lower opacity (Ezer & Cameron 1971; Maeder 1987), and thus UV radiation becomes harder and produces more ionizing photons. Thirdly, the strength of collisionally excited emission lines (e.g. [O iii], [N ii]) strongly depends on the electron density. It is closely related to the number of electrons to collide since the excitation potential of this line is ∼1 eV, which is nearly the same as the energy of electrons at the virial temperature (∼104 K) (Dyson & Williams 1980). Due to low excitation potential, the transition of collisionally excited line is reliant on electron density compared to gaseous metallicity. Recent observations have suggested a high electron density (ne > 100 cm−3) in SF galaxies at z ∼ 2 (Newman et al. 2012; Masters et al. 2014; Shirazi, Brinchmann & Rahmati 2014; Wuyts et al. 2014). This value is larger than that of normal SF galaxies at low-z by an order of magnitude, and close to that of interacting galaxies which are seen as (ultra)luminous infrared (IR) galaxies in the present-day Universe (Krabbe et al. 2014). Such a large electron density contributes to the offset of galaxy distributions on the BPT diagram together with other physical parameters (Brinchmann, Pettini & Charlot 2008a). In this way, the cosmic dependence of the BPT diagram can be attributed to such physical parameters which determine ISM conditions.
Citation: Steidel et al. 2014
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A more equitable view of the catalogue is given by considering the distributions of band values across all haloes. In Fig. 14, we quantify the relative probability for a given integrated ($\mathcal {T}_\rm{IGM}^\rm{\,int}$, bottom panels) and maximum ($\mathcal {T}_\rm{IGM}^\rm{\,max}$, top panels) band transmission at each redshift. For reference, we also show the cumulative distribution functions as dashed curves and the median and 1σ summary statistics in the middle panels. It is extremely unlikely to have non-negligible transmission spikes in the blue bands at z ≳ 8, although this is certainly allowed (int) or even common (max) at z ≲ 6. When also considering the central band in rare cases it is plausible to witness multiple-peaked or otherwise complex spectral line profiles (e.g. see the discussions by Byrohl & Gronke 2020; Mason & Gronke 2020; Gronke et al. 2021; Park et al. 2021). This also stresses the need for systemic tracers beyond  Lyα to distinguish IGM signatures and pinpoint the origins of various spectral features. Perhaps more significant is the broad distribution in the red band. The transmission is relatively high after the midpoint of reionization z ≲ 7.67, and roughly follows the global ionized fraction (see Fig. 13). However, as will be shown later the exponential sensitivity on optical depth ($\mathcal {T}_\rm{IGM} = e^{-\tau _\rm{IGM}}$) allows the same galaxy to have both large and small values, i.e. the bimodality is not due to halo mass or environment alone. In fact, there will always be sightlines with very low transmission due to filaments and other self-shielding structures common at high-z. The location and broad nature of the higher transmission peak is redshift dependent, which is an important consideration when using LAEs as probes of reionization. We emphasize that the sharp cutoffs below $\mathcal {T}_\rm{IGM} \approx 1$ are not physical but are due to the global treatment of the long-range damping-wing absorption. For example, at z = 7 the red band values cannot exceed $\mathcal {T}_\rm{IGM} \approx 0.95$ as every sightline on average experiences at least $5{{\ \rm per\ cent}}$ absorption via cosmological integration throughout the remainder of the EoR. Finally, we note that the ultra red band is less susceptible to resonant scattering and halo proximity effects and is therefore a cleaner probe of the global state of the IGM if this can be robustly measured with deep spectroscopy for large numbers of high-z galaxies.
Citation: Mason & Gronke 2020
Citation function: Background; Motivation
The search for low-mass BHs (MBH ≲ 106 M⊙) in dwarf galaxies is mostly based on the detection of X-ray emission (e.g. Greene & Ho 2007a; Desroches, Greene & Ho 2009; Reines et al. 2011; Dong et al. 2012; Schramm et al. 2013; Baldassare et al. 2015, 2017; Lemons et al. 2015; Secrest et al. 2015; Pardo et al. 2016; Chen et al. 2017), in some cases spatially coincident with jet radio emission (e.g. Reines et al. 2014; Nucita et al. 2017), or the use of standard virial techniques to estimate the BH mass (e.g. Barth et al. 2004; Greene & Ho 2004, 2007b; Peterson et al. 2005; Reines, Greene & Geha 2013; La Franca et al. 2015; Bentz et al. 2016; Onori et al. 2017; Liu et al. 2018; Chilingarian et al. 2018; see Mezcua 2017 for a review). Additional searches in the infrared (IR) regime have yielded a few more candidates (e.g. Satyapal et al. 2007, 2008, 2009, 2014; Sartori et al. 2015; Marleau et al. 2017). Most of these samples are however incomplete, very local (z  0.3), skewed towards high Eddington ratios, or skewed towards type-1 active galactic nucleus (AGN) in the case of optical searches (e.g. Greene & Ho 2004, 2007b; Reines et al. 2013) which can hamper the detection of BHs lighter than 105 M⊙ if the size of the broad-line region is controlled by BH mass (e.g. Chakravorty, Elvis & Ferland 2014). Baldassare et al. (2015) found an AGN with MBH ∼ 5 × 104 M⊙ estimated using the virial technique, Yuan et al. (2014) performed a study of four low Eddington ratio sources, and Pardo et al. (2016) searched for AGN in dwarf galaxies out to z  1. Yet, these studies include very few sources. To circumvent the biases mentioned above, in Mezcua et al. (2016) we performed an X-ray stacking analysis of ∼50 000 dwarf galaxies selected in the COSMOS field making use of the recently completed Chandra COSMOS-Legacy survey (Civano et al. 2016). We found that a population of IMBHs with X-ray luminosities ∼1039−1040 erg s−1 does exist in dwarf galaxies out to z = 1.5 and that their detection beyond the local Universe is most likely hampered by their low luminosity and mild obscuration unless deep surveys like the Chandra COSMOS-Legacy are used.
Citation: Marleau et al. 2017
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The question is, which of these proposed merger channels dominate the merger rate? Are several channels operating with a possible dependence on redshift? Or are the majority of GW sources formed through a still unknown mechanism? Several studies show that one can distinguish at least classes of channels, such as isolated binaries and dynamically induced mergers, by considering the observed distribution of merger masses (Zevin et al. 2017) or the relative spin orientation of the merging objects (Rodriguez et al. 2016c), as well as the orbital eccentricity at some reference GW frequency (Gültekin et al. 2006; Samsing et al. 2014; Samsing & Ramirez-Ruiz 2017; Samsing & Ilan 2018; Samsing et al. 2018b; Samsing 2018; Samsing et al. 2018a; Samsing & D’Orazio 2018; Rodriguez et al. 2018; Zevin et al. 2019; Samsing et al. 2019a, 2020). Other “indirect” probes have also been suggested, such as stellar tidal disruptions (e.g., Samsing et al. 2019b; Lopez et al. 2019; Kremer et al. 2019b). In this picture, it is now largely believed that dynamically assembled mergers are likely to have mass rations near one (e.g., Rodriguez et al. 2018), random relative spin orientations (e.g., Rodriguez et al. 2016c), and a nonnegligible fraction of mergers with measurable eccentricity in LISA (Samsing & D’Orazio 2018; Kremer et al. 2019c), DECIGO/Tian-Qin (e.g., Chen & Amaro-Seoane 2017; Samsing et al. 2020), and LIGO (Samsing 2018). This is in contrast to isolated binary mergers, which likely have correlated spins (e.g., Kalogera 2000), a bimodal distribution for the effective spin parameter (Zaldarriaga et al. 2018; Hotokezaka & Piran 2017; Piran & Piran 2020), larger mass ratios, and which merge on orbits with eccentricities indistinguishable from ~0 near LISA and LIGO. This picture is rather clean when comparing mergers forming in highly dynamical systems, such as globular clusters (GCs) and GNs, to completely isolated field binary mergers; however, it becomes less clean when considering, e.g., the proposed subpopulation of field binaries that undergo secular interactions with nearby single or binary objects (e.g., Naoz et al. 2013; Naoz 2016; Toonen et al. 2016; Antonini et al. 2017; Silsbee & Tremaine 2017; Liu & Lai 2018; Rodriguez & Antonini 2018; Randall & Xianyu 2018a; Antonini et al. 2018; Liu & Lai 2019; Fragione & Loeb 2019; Fragione & Kocsis 2019; Hamers & Thompson 2019; Safarzadeh et al. 2020). In this case, secular exchanges of especially angular momentum can drive the binary to merge with random spin orientations (e.g., Liu & Lai 2017) and notable eccentricities (e.g., Randall & Xianyu 2018b; Liu et al. 2019; Fragione & Kocsis 2020), which makes it more challenging to disentangle cluster mergers from field binary mergers.
Citation: Samsing & Ilan 2018
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In this paper, we presented our analysis of the spectral and timing behavior of GRS 1915+105 using the TCAF paradigm. For this purpose, the θ class data of the source as obtained by the LAXPC instrument of AstroSat satellite were used. To the best of our knowledge, this is the first time that the θ class data of AstroSat are analyzed with the TCAF paradigm. In this paradigm, different spectral states as well as the QPOs resulting from resonance oscillation of the Compton cloud arise out of the interplay between two types of accretion rates, namely, the Keplerian disk rate (








m







d




) and the sub-Keplerian halo rate (








m







h




). In the sub-Keplerian flow, shocks are formed when the Rankine–Hugoniot conditions are satisfied (Chakrabarti 1989, 1996; Chakrabarti & Das 2004). If the Keplerian disk rate increases, it increases the soft-seed photons, and the post-shock region (CENBOL, which acts as a “Compton cloud”) is cooled down rapidly, causing the shock to proceed toward the black hole. This has indeed been obtained in our spectral analysis. In the process, both the compressional heating timescale and the cooling timescale of the CENBOL decrease and become comparable (Chakrabarti et al. 2015), triggering shock oscillations that manifest as QPOs in the light curve. We first obtained the state of the system by estimating the photon index using the phabs*(diskbb+power-law) model. Throughout our analysis, the photon index (Γ) was found to be above 2.4, indicating that the source was either in the soft-intermediate state (SIMS) or in the soft state (SS). In the case of both orbits, Γ monotonically increases with the increase in photon flux, implying the transition from SS to SIMS. In the first orbit, Γ made an excursion from 2.5 to 3.0 during the 400 s span of spectral analysis, indicating the transition of the source from SIMS to SS. The gradual enhancement of the disk accretion rate and the consequent decline of the shock location were also obtained from the TCAF model fitting. The shock location moves from 39rs to 17rs, while the disk accretion rate increases from 0.77 to 0.84 








M







Edd




. A similar trend was followed in the second orbit as well (Table 2). In the two orbits (02345 and 02346) we have analyzed, within a span of 400–500 s, the total flux changes by a factor of 3–5. The corresponding shock velocity is ∼2200 and 900 m s−1, respectively. This is significantly higher than the shock velocity obtained earlier in the case of transient sources, which lie within 10–20 m s−1 (Chakrabarti et al. 2008; Nandi et al. 2012; Debnath et al. 2013). This suggests the possibility that the local modulation of the accretion rate is due to feedback from the outflow (Chakrabarti & Manickam 2000; Chakrabarti & Nandi 2000). All these results indicate that GRS 1915+105 went through repeated microflares when it was in θ class.
Citation: Chakrabarti 1989
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