adsabs/FOCAL huggingface dataset:
Solar flares are one of the most spectacular activities in the solar system. Up to 1029–1032 erg magnetic free energy is impulsively released, accompanied by rapid increases of emissions in various wavelengths (Shibata & Magara 2011). It is generally believed that magnetic reconnection plays a key role in the reconfiguration of magnetic field lines and the conversion of magnetic energy into kinetic and thermal energies of plasma (Forbes & Acton 1996; Priest & Forbes 2000). In the context of the standard solar flare model (Carmichael 1964; Sturrock 1966; Hirayama 1974; Kopp & Pneuman 1976), accelerated nonthermal electrons propagate downward and heat the chromosphere, forming bright flare ribbons in the Hα, Ca ii H, ultraviolet (UV), and extreme-ultraviolet (EUV) wavelengths. The flare ribbons have diverse shapes, with two parallel flare ribbons (PFRs) being the most commonplace (Li & Zhang 2015). Sometimes, circular flare ribbons (CFRs) appear accompanied by remote brightenings, which are generally believed to be associated with a magnetic null point (





) and a dome-like spine–fan topology (Masson et al. 2009; Zhang et al. 2012; Pontin et al. 2016). More complex flare ribbons have also been observed (Joshi et al. 2015). Apart from the localized heating, hard X-ray (HXR) emissions are generated via Coulomb collisions (Brown 1971). If open magnetic field lines are involved, it is likely that the nonthermal electrons at speeds of 0.06–0.25c (c is the speed of light) escape from the Sun into interplanetary space and generate type III radio bursts with frequencies ranging from 0.2 to hundreds of MHz (Dulk et al. 1987; Aschwanden et al. 1995; Zhang et al. 2015). Sometimes, the HXR and radio emissions of a flare show quasi-periodic pulsations (QPPs), with their periods ranging from milliseconds (Tan et al. 2010) through a few seconds (Kliem et al. 2000; Asai et al. 2001; Ning et al. 2005; Nakariakov et al. 2010; Hayes et al. 2016) to several minutes (Ofman & Sui 2006; Nakariakov & Melnikov 2009; Sych et al. 2009; Ning 2014). So far, QPPs have been extensively explored using both imaging (Su et al. 2012a, 2012b) and spectral observations (Mariska 2005). Li et al. (2015b) studied the X1.6 flare on 2014 September 10. Four-minute QPPs are evident not only in the HXR, EUV, UV, and radio light curves, but also in the temporal evolutions of the Doppler velocities and line widths of the C i, O iv, Si iv, and Fe xxi lines. Brosius & Daw (2015) studied the M7.3 flare on 2014 April 18. The chromospheric and transition region line emissions show quasi-periodic intensity and velocity fluctuations with periods of ∼3 minutes during the first four peaks and ∼1.5 minutes during the last four peaks.
Citation: Pontin et al. 2016
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Figures 2 and 3 demonstrate that the GW alert system is capable of providing GW alerts before merger, but they do not consider the prospects for detection from an astrophysical source population. We generate a population of simulated BNS signals, henceforth referred to as injections, using the TaylorF2 (Sathyaprakash & Dhurandhar 1991; Blanchet et al. 1995, 2005; Buonanno et al. 2009) waveform model. Both source-frame component masses are drawn from a Gaussian distribution between 1.0 M⊙ m1, m2  2.0 M⊙ with mean mass of 1.33 M⊙ and standard deviation of 0.09 M⊙, modeled after observations of galactic BNSs (Özel & Freire 2016).40

40
Note that if GW190425 is a BNS, then galactic measurements are not representative of neutron star masses.
 The neutron stars in the population are nonspinning, motivated by the low spins of BNSs expected to merge within a Hubble time (Burgay et al. 2003; Zhu et al. 2018). The signals are distributed uniformly in comoving volume up to a redshift of z = 0.2. We consider a network of four GW detectors: LIGO-Hanford, LIGO-Livingston, Virgo, and KAGRA at their projected O4 sensitivities.41

41

https://dcc.ligo.org/LIGO-T2000012/public

 We simulate the results of an early warning matched-filtering pipeline by considering six different discrete frequency cutoffs: 29, 32, 38, 49, 56, and 1024 Hz to analyze signal recovery at (approximately) 58, 44, 28, 14, 10, and 0 s before merger, motivated by Sachdev et al. (2020). We calculate the network S/N of each injection at each frequency cutoff and consider the events that pass an S/N cutoff of 12.0 as “detected.” We then calculate the sky posteriors for each of the detected signals by using BAYESTAR (Singer & Price 2016). We use the most recent BNS local merger rate from Abbott et al. (2020b) of 





 to estimate the number of events detected per year in the detector network. In Figure 4(a) we see that our optimistic scenario predicts 





 GCN will be received 1 s before merger per year, while our pessimistic scenario predicts 





 GCN will be received 1 s before merger per year considering the higher end of the BNS rate. Figure 4(b) predicts that ∼9 events will be detected per year, out of which ∼20% (∼1.3%) will be detected 10 s (60 s) before merger. Further, ∼3% of the detectable events (∼1 BNS every 3–4 yr) will be detected 10 s prior to merger and have a localization less than 100 deg2 at O4 sensitivities. This highlights the need for continued latency improvements in advance of O4 to maximize the potential of capturing prompt emission.
Citation: Özel & Freire 2016
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The semiforbidden [C iii] λ1907 + C iii] λ1909 doublet (hereafter C iii] λ1909 or C iii]) is one of the strongest nebular emission line features observed in the rest-frame ultraviolet (rest-UV) spectrum of low-metallicity, 12+log(O/H) ≤ 8.4 (Z  0.5 Z⊙) star-forming galaxies (SFGs) both locally (Garnett et al. 1995; Rigby et al. 2015; Berg et al. 2016, 2019; Senchyna et al. 2017, 2019) and at high redshifts (Fosbury et al. 2003; Erb et al. 2010; Bayliss et al. 2014; Stark et al. 2014, 2015a, 2017; de Barros et al. 2016; Vanzella et al. 2016; Amorín et al. 2017; Laporte et al. 2017; Maseda et al. 2017; Berg et al. 2018; Hutchison et al. 2019; Le Fèvre et al. 2019). The C iii] emission line is frequently observed in gravitationally lensed SFGs at z > 2–6 as the strongest line after Lyα λ1216 emission. Since the Lyα emission at z > 6 is expected to be severely quenched by the increasingly neutral intergalactic medium (IGM), C iii] is emerging as an alternative redshift indicator for galaxies in the reionization era (Stark et al. 2015a, 2017; Ding et al. 2017). At z > 6, the rest-UV spectrum of galaxies is redshifted to the near-infrared (NIR) wavelengths and is accessible to the spectrographs on upcoming facilities (such as the James Webb Space Telescope (JWST) and the >20 m class Extremely Large Telescopes), which will address the key goal of identifying the sources of reionization. In recent years, there has been considerable effort to develop spectral diagnostics involving the C iii] emission line and other UV spectral features (e.g., C iv λλ1548, 1550, He ii λ1640, and O iii] λλ1661, 1666 (hereafter O iii] λ1663 or O iii])) that can be used to understand the nature of the reionizers, their hard ionizing continua, and the physical conditions in their ISM (Feltre et al. 2016; Gutkin et al. 2016; Jaskot & Ravindranath 2016, hereafter JR16; Byler et al. 2018; Nakajima et al. 2018b). The C iii] emission observed at high redshifts is mostly from strongly lensed low-metallicity (0.5 Z⊙), low-mass (1010 M⊙) galaxies with high specific star formation rates (SSFRs ≳ 2 Gyr−1), and their C iii] equivalent widths (EWs) show a broad range: EW(C iii]) ∼ 3–25 Å (Fosbury et al. 2003; Erb et al. 2010; Bayliss et al. 2014; Stark et al. 2014; de Barros et al. 2016; Vanzella et al. 2016; Berg et al. 2018). The composite rest-UV spectra of Lyman-break galaxies at z ∼ 3 (Shapley et al. 2003) and SFGs at z = 1–2.5 (Steidel et al. 2016; Amorín et al. 2017) also reveal the C iii] λ1909 and O iii] λ1663 nebular lines at subsolar metallicities.
Citation: Le Fèvre et al. 2019
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While the properties of the SLSN hosts themselves are of interest, they are most diagnostic when compared to other classes of extragalactic transient whose progenitors are better understood. To this end, we employ a comparison sample of LGRB and CCSN3 host galaxies. In principle, CCSNe should trace all core-collapse events, although the mass function means they will be dominated by stars at the lower mass end (∼8 M⊙ to ∼25 M⊙). There also remains a possibility that some very massive stars can undergo core collapse without yielding a LSNe (e.g. Smartt 2009; Ugliano et al. 2012; Kochanek 2014) such that CCSNe samples might only provide a census of lower mass core collapsing stars (e.g. 8  M*  20 M⊙). Indeed, constraints from explosion parameters have shown the majority of CCSNe to be consistent with lower mass progenitors, as opposed to more massive Wolf–Rayet stars (Cano 2013; Lyman et al. 2016) GRBs likely represent a population with rather larger initial masses (Larsson et al. 2007; Raskin et al. 2008). LGRBs are now known to be associated with the core collapse of massive stars, and broad line SN Ic are near ubiquitously associated with low-z events (where such signatures can be seen; Hjorth et al. 2012). When compared to the hosts of CCSNe they are generally smaller and of lower luminosity, consistent with an origin in galaxies of lower metallicity (Fruchter et al. 2006; Svensson et al. 2010). In relatively local examples, where spatially resolved gas phase metallicities can be obtained, these indeed appear to be lower for GRBs than for CCSNe, even in cases where the luminosity of the galaxy is relatively high (i.e. the GRB host galaxies lie off the mass–metallicity relation; Modjaz et al. 2008; Graham & Fruchter 2013). Hence, comparing the hosts of SLSNe to these events allows us to test the large-scale environments of SLSNe against those of the bulk core-collapse population and a subset which appears to derive largely from massive stars at lower metallicity, although we note that agreement on this matter is not complete (e.g. Podsiadlowski, Joss & Hsu 1992; Eldridge, Izzard & Tout 2008; Smartt 2009; Drout et al. 2011). By exploiting both LGRB and CCSN host samples we can ascertain if there is a strong metallicity dependence in SLSN production, and if this is more or less extreme than that observed in GRB hosts.
Citation: Kochanek 2014
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Citation: Modjaz et al. 2008
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The distribution of optical depth values at 10 au and 1.3 mm (Figure 7, top) has its maximum at 




log


τ


1.3

mm
,
10

au


=
−
0.25


 (corresponding to 






τ


1.3

mm
,
10

au


∼
0.5


), and a secondary peak at 




log


τ


1.3

mm
,
10

au


=
−
1


. We note that the shape of this distribution is determined mostly by Taurus, given the lack of sufficient long-wavelength data for most objects in Chamaeleon I and Ophiuchus, and the distributions in these regions appear to be broader than the one in Taurus (again, this interpretation is limited by the small number statistics in these regions). For comparison, reasonable assumptions about the dust opacity and surface density based on observations of the solar system bodies yield 






τ


1

mm


=
1


 at ∼10 au for the Minimum Mass Solar Nebula (Davis 2005), suggesting that several of the modeled protoplanetary disks may have optical depth profiles (and hence possibly surface densities) similar to that of the parental disk of the solar system. In the case of β, values smaller than the one measured for the ISM (∼1.6–2; see Draine 2006 and references therein) imply some degree of grain growth. Almost the entirety of the Taurus and Ophiuchus distributions (and part of Chamaeleon I) are constrained within that value, in correspondence with the observational result discussed in Section 3.3. As with 






α


mm




, Chamaeleon I shows a different behavior (an excess of high β values) that will be discussed further on. We note that the distributions of β should be considered with caution, not only due to the aforementioned caveats, but also because degenerate cases have been removed from the analysis. Because these occur when 




α
=
2


, this procedure inevitably discards objects with 




β
∼
0


. There is a tentative bimodality in both distributions, especially in the case of β, with a tentative secondary peak occurring at ∼1.4–1.5. Given the limited size of the modeled sample and simplicity of the models used, we do not investigate this issue in detail here. However, we speculate that, if real, it may hint at a quick transition from micron-sized grains (large β values) to mm/cm-sized dust (smaller β).
Citation: Davis 2005
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Analytical expressions for the IP and OP spectra obtained by IR–MAIRS are theorized by Itoh et al. (2009) and Shioya et al. (2019). In short, Shioya et al. showed both experimentally and theoretically that the IP spectrum (A
IP) quantitatively corresponds to the normal-incidence transmission spectrum, 



Athinθ=0

 (see the Appendix for details; Shioya et al. 2019).
5



AIP=Athinθ=0=8πdaλln102n2k2xy.


A
OP is expressed similarly to A
IP, while the TO energy-loss function is replaced with a longitudinal optic (LO) energy-loss function: i.e., (2n
2
k
2z
)/(



n22

 + k
2z

2)2 (Shioya et al. 2019; Hama et al. 2020).
6



AOP=8πdaHλln10(2n2k2z)n22+k2z22,

where H is a substrate-specific correction factor (0.33 for Si) that accounts for the intensity ratio of the electric fields at the optical interface along the surface-parallel and surface-perpendicular directions (Shioya et al. 2019). Because amorphous H2O vapor-deposited at 80–100 K has values of k
2 that are approximately 2 orders of magnitude smaller than n
2 (k
2 ≪n
2) at 3750–3650 cm−1 in the bulk (Mastrapa et al. 2009), Equation (6) simplifies to
7



AOP≈8πdaHλln10(2n2k2z)n24.

From Equations (5) and (7), k
2xy
 and k
2z
 are derived as
8



k2xy=AIPλln1016πdan2



9



k2z=n24HAOPλln1016πdan2.

Therefore, optically isotropic k
2 and σ can be obtained from A
IP and A
OP even for a thin sample (Shioya et al. 2020):
10



k2=2k2xy+k2z3=2AIP+n24HAOP3λln1016πdan2



11



σ=4πdk2λN=4πdλN2AIP+n24HAOP3λln1016πdan2=2AIP+n24HAOP3ln104an2N.

The band strength β (cm molecule−1) can be also obtained by integrating 



σ(ν˜)

 at 



ν˜=

 3710–3680 cm−1.
12



β=∫σν˜dν˜=23∫AIPν˜dν˜+n24H3∫AOPν˜dν˜ln104an2N,

where 



AIPν˜

 and 



AOPν˜

 is the IP and OP absorbance at a given wavenumber (



ν˜

), respectively. This study uses n
1 = 1 for vacuum, n
2 = 1.26 for amorphous water at 90 K (Kofman et al. 2019), and n
3=3.41 for Si (Tasumi 2014; Shioya et al. 2019). Hence, a = 0.290 and 



n24


H = 0.832. Seven independent measurements for amorphous water formed after 32 minutes of exposure at 90 K gave A
IP  = 0 [



∫AIPν˜dν˜=0

 (cm−1)] and 



n24HAOP

 = 6.2 ± 0.4 × 10−5 at 3696 cm−1 [



n24H∫AOPν˜dν˜

 = 8.4 ± 0.4 × 10−4 (cm−1)], considering amorphous water formed on both sides of the Si substrate. Therefore, σ is derived as 1.0 ± 0.2 × 10−18 cm2 at 3696 cm−1 from Equation (11) by adopting N = 3.3 ± 0.6 × 1013 molecules cm−2. β is also derived as 1.4 ± 0.3 × 10−17 cm molecule−1 at 



ν̃

 = 3710–3680 cm−1 from Equation (12).
Citation: Hama et al. 2020
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To investigate this further, we performed an additional test where we froze the slopes for both the fossils and groups to 3.0 and only fit the normalisation for both samples. The value of 3.0 for the slope was chosen as generally most groups and clusters can be described well by this particular slope, after factoring in selection effects. The fossils now have a normalisation of 0.38 ± 0.11 and the groups sample have a normalisation of 0.22 ± 0.13. We now proceeded to remove the influence of selection effects on the normalisation of the scaling relation for both samples by generating mock samples of objects as in Bharadwaj et al. (2015) by varying the input normalisations. For each mock sample, the slope was always fixed to 3 and the intrinsic scatter was fixed to the observed values. Flux and luminosity cuts were applied to both the 400d sample and the groups sample to match the true sample of objects. For the 400d fossil sample, the selection criteria were taken from Voevodkin et al. (2010), and can be described as follows: a lower flux cut of 1.4 ×  10-13 erg / s / cm2, an upper redshift cut of 0.2, and a lower luminosity cut of 1043 erg/s. Here, fluxes and luminosities are in the ROSAT (0.5–2.0 keV) band. After performing the bias corrections, the fossils scaling relation has a normalisation of 0.30 ± 0.10 vs. 0.0078 ± 0.13 for the groups, indicating that the large normalisations seem to persist even after accounting for selection effects. Despite a nearly 2.3σ higher normalisation for fossils with respect to non-fossils, we still only treat this finding as an indication because on top of the statistical uncertainties in both quantities (which is large currently for the 400d fossils), there could also be an additional systematic uncertainty introduced due to differences in the luminosity determination in the different parent catalogues. Secondly, the archival nature of this subsample of 400d objects is biased towards systems lacking a SCC (Table 2) and, assuming that the remaining systems are SCC, then adding these objects could potentially increase the normalisation for the scaling relation, and the difference between the fossils and the groups sample would be higher than what we demonstrate here. We plan to explore this in greater detail in a future study of fossils scaling relations.
Citation: Voevodkin et al. (2010)
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In this work, we focus on constraining the variability of the fine-structure constant, α ≡ e2/ℏc, which represents the coupling strength of the electromagnetic force. In the last 15 years, there have been many attempts to measure this constant in absorption systems along the lines of sight to distant quasars. The approach called the ‘Many Multiplet’ (MM) method, pioneered by Dzuba, Flambaum & Webb (1999) and Webb et al. (1999), compares the relative velocity spacing between different metal ion transitions and relates it to possible variation in α. For example, considering just a single transition, variation in α is related to the velocity shift Δvi of a transition

(1)

\begin{equation}
\Delta \alpha /\alpha \equiv \frac{\alpha _{\rm obs}-\alpha _{\rm lab}}{\alpha _{\rm lab}}\approx \frac{-\Delta v_i}{2c}\frac{\omega _i}{q_i},
\end{equation}

where c is the speed of light, qi is sensitivity of the transition to α-variation, calculated from many body-relativistic corrections to the energy levels of ions and ωi is its wavenumber measured in the laboratory. There have been two MM method studies of large absorber samples: the Keck High Resolution Echelle Spectrometer (HIRES/Keck) sample of 143 absorption systems (Webb et al. 1999, 2001; Murphy et al. 2001a, 2004; Murphy, Webb & Flambaum 2003b) and the Ultraviolet and Visual Echelle Spectrograph on the Very Large Telescope (UVES/VLT) sample of 154 absorption systems (Webb et al. 2011; King et al. 2012). These studies reported weighted mean values of Δα/α = −5.7 ± 1.1 parts per million (ppm) and 2.29 ± 0.95 ppm, respectively. Webb et al. (2011) and King et al. (2012) also combined both samples and found a 4.1σ statistical preference for a dipole-like variation in α across the sky. Contrary to these studies, several other attempts to measure α from individual absorbers (Quast, Reimers & Levshakov 2004; Levshakov et al. 2005, 2006, 2007; Chand et al. 2006) or smaller samples of absorption systems (Chand et al. 2004; Srianand et al. 2004) reported Δα/α consistent with zero. However, these analyses contained shortcomings that produced biased values and/or considerably underestimated error bars (Murphy, Webb & Flambaum 2007a, 2008b; cf. Srianand et al., 2007). For example, a reanalysis, including remodelling of the Chand et al. (2004) spectra by Wilczynska et al. (2015), yielded a weighted mean of Δα/α = 2.2 ± 2.3 ppm which, given the distribution of the 18 quasars across the sky, was not inconsistent with the evidence for dipole-like α-variation.
Citation: Webb et al. (1999)
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Citation: Webb et al. 1999
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Even when imaged into 40 km s−1 channels, CO(2−1) absorption is apparent in NGC 4374 and IC 4296 against their strong nuclear continuum sources. While extragalactic CO absorption is not frequently observed due to low equivalent widths, ALMA’s high angular resolution and sensitivity allow its detection against some nearby active nuclei (e.g., Davis et al. 2014; Rangwala et al. 2015). To better characterize the central absorption features, we also imaged their visibility data (without continuum subtraction) into cubes with 1.28 km s−1 channels. The primary absorption in IC 4296 is consistent with the galaxy’s assumed systemic velocity (Table 1), although there may be a small secondary absorption feature ∼15 km s−1 redward of 





. The CO(1−2) transition seen in the nucleus of NGC 4374, however, is redshifted by ∼100 km s−1 from the 





 value derived using stellar kinematics (Emsellem et al. 2004) and by ∼50 km s−1 with respect to the best-fitting 





 from ionized gas dynamical modeling (e.g., Walsh et al. 2010). The absorption lines in these two galaxies have narrow widths (≲7 km s−1 FWHM) that are only slightly smaller than the minimum line widths in our CO-bright subsample. Maximum absorption depths are (−3.26 ± 0.74) and (−5.25 ± 0.35) K with integrated absorption intensities 





 of (19.4 ± 2.5) and (44.3 ± 1.4) K km s−1 for NGC 4374 and IC 4296, respectively. From these 





 measurements, we estimate corresponding H2 column densities 





 of 





 and 





 cm−2 after assuming an absorption depth ratio CO(1−2)/CO(0−1) ≈ 0.6 (based on 13CO absorption line ratios; e.g., see Eckart et al. 1990) and a CO-to-H2 conversion factor 





 corresponding to 





 M pc−2 (K km s−1)−1 (see Section 3.1.2; Sandstrom et al. 2013). These 





 estimates are much more uncertain than indicated by the formal associated uncertainties, since the 





 and CO(1−2)/CO(1−0) values carry large systematic uncertainties, and faint nuclear CO emission may somewhat dilute these equivalent widths.
Citation: Emsellem et al. 2004
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