adsabs/FOCAL huggingface dataset:
Observations of cold molecular gas are more promising since any activity from the AGN (radiation, outflows, or jets) will have an impact on the molecular gas reservoir first, and then on the SFR, which previous studies have focused on. The molecular gas provides an instantaneous measure of the raw fuel from which stars form and can be used as a more direct tracer of potential feedback effects. Over the last decade, large observational efforts have been devoted to map the molecular gas reservoir of galaxies (e.g., Daddi et al. 2010a; García-Burillo et al. 2012; Bauermeister et al. 2013; Bothwell et al. 2013; Tacconi et al. 2013, 2018; Genzel et al. 2015; Silverman et al. 2015; Decarli et al. 2016; Cicone et al. 2017; Saintonge et al. 2017; Fluetsch et al. 2019; Freundlich et al. 2019). These studies are largely based on observations of carbon monoxide (CO) rotational emission lines, used as a tracer of cold molecular hydrogen H2 (the ground-state rotational transition in particular traces the total molecular gas best), but there are also many studies based on dust emission (e.g., Tacconi et al. 2018 and references therein). The main targets of such CO campaigns have primarily been inactive1 galaxies that mostly lie on the main sequence of star-forming galaxies (e.g., Noeske et al. 2007; Schreiber et al. 2015), where the majority of the cosmic star-formation activity occurs. The fundamental relation between SFR and the molecular gas content of galaxies, the Schmidt-Kennicutt relation, provides precious information about how efficiently galaxies turn their gas into stars (Schmidt 1959; Kennicutt 1989). This star-formation law is usually presented in terms of surface densities, therefore requiring spatially resolved measurements of galaxies. However, in high-redshift studies, an integrated form of this relation with global measurements of the SFR and molecular mass is normally used (e.g., Carilli & Walter 2013; Sargent et al. 2014).
Citation: Freundlich et al. 2019
Citation function: Background; Background
The electronic computations were performed using the molpro (Molpro 2015, http://www.molpro.net) package. In a preliminary work, we used the complete active space self-consistent field (Knowles & Werner 1985; Werner & Knowles 1985) to examine the electronic wavefunction of the HNCO–He complex. These computations showed that this wavefunction is dominantly described by a unique electron configuration (with a weight ≥0.93) over the grid used for the generation of this PES. This justifies hence the use of monoconfigurational ab initio methods. Accordingly, we applied the recently established methodology by Hochlaf and co-workers for mapping multidimensional PESs of weakly bound molecular systems with high accuracy and relatively low computational cost (Lique, Klos & Hochlaf 2010; Halvick et al. 2011; Ajili et al. 2013; Mathivon, Linguerri & Hochlaf 2013; Kalugina et al. 2014; Mogren Al Mogren et al. 2014). Briefly, these electronic computations were carried out using the explicitly correlated coupled cluster method with single, double and perturbative treatment of triple excitations (CCSD(T)-F12) (Adler, Knizia & Werner 2007; Knizia, Adler & Werner 2009) in connection with the augmented correlation-consistent aug-cc-pVTZ basis set of Dunning and co-workers (Dunning 1989; Kendall, Dunning & Harrison 1992). In addition, molpro default choices for the density fitting and resolution of identity basis sets have been applied (Yousaf & Peterson 2008). Benchmarks by Hochlaf and co-workers (Lique et al. 2010; Halvick et al. 2011; Ajili et al. 2013; Mathivon et al. 2013; Kalugina et al. 2014; Mogren Al Mogren et al. 2014) showed that results obtained from this highly correlated approach are close to those deduced using standard coupled cluster techniques extrapolated to the complete basis set (CBS) limit, whereas a strong reduction in CPU time and disc occupancy are observed. For illustration, we performed CCSD(T)/aug-cc-pVXZ calculations (X = D, T, Q, 5) on the HNCO—He cluster. Then the energies were extrapolated to the CBS limit. The comparison between CCSD(T)-F12/aug-cc-pVTZ and CBS calculations is given in Table 1. It shows that the CCSD(T)-F12/aug-cc-pVTZ results are off by 4 per cent (at the maximum) with those deduced from CBS extrapolation. We compare also our results with those done using the CCSD(T)/aug-cc-pV5Z approach. We can clearly see that the CCSD(T)-F12/aug-cc-pVTZ approach offers a good agreement with the CCSD(T)/aug-cc-pV5Z calculations with a very reduced computational cost.
Citation: Kalugina et al. 2014
Citation function: Similarities; Similarities
The comparisons show that except for GRBs 060707 and 060605, which have a very high vpeak, the LAE-LGRBs fall in the same parameter space as LyC leakers and follow the correlations between the indirect indicators found by Verhamme et al. (2017). Following their study, we can cut these plots into two regions corresponding to strong LyC leakers (fesc(LyC) > 5%, red rectangle) and weak LyC leakers (fesc(LyC)  5%, blue rectangle). All LAE-LGRBs fall in the category of the weak LyC leakers except for GRB 021004, which appears systematically to agree well with the region of the strong leakers. In panel b of Fig. 12, we also superimpose the distribution of [OIII]/[OII] ratio for the GRB sample of Krühler et al. (2015) and GRB 081121 reported here. For the majority of the GRBs, this ratio is about two, with seven cases at O32 > 4. GRB 021004 has a high value of O32 > 10 and is the strongest LAE of our golden sample (with fesc(Lyα) of 60%) in agreement with potential high fesc(LyC). Nevertheless, the Lyα profile of GRB 021004 is a single peak with no residual flux at the Lyα line center. This is not the typical line shape observed for confirmed LyC emitters, which have the tendency to show double- or triple-peak profiles (Verhamme et al. 2017; Rivera-Thorsen et al. 2017; Vanzella et al. 2020). Our shell-model fitting also suggests that the column densities are too high to allow LyC photons to escape. However, this model already predicted a similar HI column density (log(NHI/cm−2) ≈ 19−20) for four green pea galaxies out of the five with detected LyC emission reported in Yang et al. (2017). This suggests that LyC emission can escape through holes in the ISM even if the Lyα photons probe denser neutral gas. The only LAE-LGRB for which LyC leakage has been detected along the LGRB line of sight (




f
esc


(
LyC
)

=
0
.

35

−
0.11


+
0.10




$ f_{\mathrm{esc}}(\rm LyC) = 0.35^{+0.10}_{-0.11} $


) is GRB 191004B (Vielfaure et al. 2020). However, Fig. 12 (panel c) shows that it does not fall in the high escape fraction region, but in the lower left area. The reasons could be that (i) fesc(LyC) is lower at the scale of the galaxy than along the LGRB line of sight, and (ii) the indicators of strong LyC leakage evolves with redshift. As a comparison, the LyC emitters from Fletcher et al. (2019) are found out of the high escape region (red rectangle). They show lower rest-frame EW(Lyα) and higher vpeak than the local LyC emitters, whereas their escape fraction of ionizing photons is significantly higher (fesc(LyC) = 15 − 60%). This could also suggest that strong LyC leakers span a wider parameter space than predicted by the study of local LyC emitters. Overall, it is clear that this type of studies is still limited by the poor statistics, and the current results show the difficulty of characterizing LyC leakage based on these properties alone.
Citation: Krühler et al. (2015)
Citation function: Uses; Uses; Compare/Contrast
As MKT J170456.2–482100 is coincident with a star in a spectroscopic binary, it is possible that the companion star may be a pulsar or pulsating white dwarf, similar to AR Scorpii (Marsh et al. 2016). To investigate this possibility, we performed high-time resolution observations to search for pulsations over a range of periods spanning milliseconds to minutes. We observed the position of MKT J170456.2–482100 on utc 2019 January 30 with the ultra-wide-bandwidth (UWL) receiver deployed on the 64-m Parkes radio telescope in Australia. The output of the receiver is processed by the Medusa Graphics Processing Unit (GPU) cluster which produces 8-bit, full-Stokes filter banks with spectral and temporal resolutions of 1 MHz and 128 μs respectively over the $3328\, \mathrm{MHz}$ band from 0.740 to $4.03\, \mathrm{GHz}$. The data were recorded in psrfits format and processed using PSRCHIVE tools (Hotan, van Straten & Manchester 2004). Since our data were strongly affected by radio frequency interference (RFI) we used the clfd8 package described in (Morello et al. 2019) to perform more sophisticated RFI mitigation. Since radio waves are dispersed by free electrons in the interstellar medium along the line of sight, the data need to be corrected for this dispersion delay before any analyses can be made. This dispersion delay can be quantified by the dispersion measure (DM), which is the integrated free electron column density along the line of sight. We dedispersed the data over a range of trial DMs, $0.0 \le \mathrm{DM} \le 30.0$ pc cm$^{-3}$ in steps of 1 pc cm$^{-3}$ to account for the uncertainty in the distance to TYC 8332-2529-1. The DM range was estimated using various distances to the source (Bailer-Jones et al. 2018), and the NE2001 model (Cordes & Lazio 2002). For each trial DM, the resulting dedispersed time series was searched for long and short-period pulsations using both a Fast Folding Algorithm (FFA) and a Fast Fourier Transform (FFT), respectively.
Citation: Hotan, van Straten & Manchester 2004
Citation function: Uses
The median value of the column density of OH in the first quadrant is 3.9 × 1014 cm-3 and for OH+ it is 0.68 × 1014 cm-3. In the fourth quadrant, the median column densities amount to 1.7 × 1014 cm-3 and 0.55 × 1014 cm-3, respectively. Column densities in excess of 1015 cm-2 (for OH) and above ~1014 cm-2 (for OH+) are rather the exception. The median N(OH) /N(OH+) ratio over all sightlines and velocity components is 3.3. While the formation of OH+ results from cosmic-ray induced reactions involving atomic and molecular hydrogen and atomic oxygen, the bottleneck expected for the formation of OH via ion-neutral chemistry is the availability of H2. The reaction of OH+ with H2 yields H3O+, via the two hydrogen abstraction reactions OH+(H2,H)H2O+(H2,H)H3O+ (see Appendix C). Then the dissociative recombination of H3O+ yields OH and H2O, with a branching ratio of ~74% to 83% in favor of OH (determined by ion storage ring experiments, Jensen et al. 2000; Neau et al. 2000), while less than ~1% forms O i . In the following, we attempt to confirm these predictions, that is, the bottleneck reaction OH+(H2,H)H2O+, and the N(OH) /N(H2O) ratio. As for the former, a strong anticorrespondence between the column densities of OH and OH+might naively be expected, where the availability of H2 tips the scales in favor of OH, while OH+ traces predominantly atomic gas (Hollenbach et al. 2012, further references therein). But even if a clear anticorrelation between OH and OH+ existed, it would be impossible to observe it. On a given sightline several clouds with high and low molecular hydrogen fractions \hbox{$f^{\rm N}_\HH = N(\HH)/(2N(\HH)+N($}fH2N=N(H2)/(2N(H2)+N(H i )) line up. Even across a single diffuse cloud, the N(OH) /N(OH+) ratio is expected to vary substantially, depending on the degree of self-shielding of H2 against the interstellar UV radiation field. To quantify the anticorrelation, we normalized the velocity-specific OH column density with the total OH and OH+ reservoir and obtained an abundance ratio r = Nv(OH)/(Nv(OH) + Nv(OH+) varying from zero (only OH+, no OH) to one, where all the OH+ abundance is exhausted owing to the formation of OH and (see below) water. (The normalization chosen here avoids the divergence of the distribution if OH has no spectral counterpart in OH+.) The resulting distribution (Fig. 12) indeed shows that these extremes are present in the data, although the second case is by an order of magnitude more frequent. We suggest two explanations for this. One reason is that if \hbox{$f^{\rm N}_\HH$}fH2N is too small, OH+ can be efficiently destroyed by the dissociative recombination with free electrons (Appendix C), while the formation of OH+ by the reaction chain H+(O,H)O+(H2,H)OH+ and the secondary, less important path H2+(H2,H)H3+(O,H2)OH+ become less efficient (see Appendix D) because less H2 is available. Another reason is that the fraction \hbox{$f^{\rm N}_\HH$}fH2N is larger in denser gas (cf. Table 3) where column densities are higher and absorption features easier to observe.
Citation: Neau et al. 2000
Citation function: Background
In principle, when ΔνZ>δν, with δν being the observed full width at half maximun (FWHM) of the line, the complete set of information concerning the magnetic field B can be derived. However, for most of the Zeeman detections, the Zeeman splitting ΔνZ turns out to be significantly smaller than δν. Indeed, even if we neglect the non-thermal line broadening due to typical processes occurring in star forming regions such as jets (with velocities up to hundreds of km s-1), outflows, and accreting/rotating disks (typically ≤10 km s-1), already the thermal broadening (even at kinetical temperatures lower than 10 K) is definitely larger than the Zeeman splitting (e.g., Frank et al. 2014). For instance, a typical linewidth of the coldest starless cores is ~0.1 km s-1  (e.g., di Francesco et al. 2007), indeed too broad to allow an observer to unveil the Zeeman effect. The expected B values in star forming regions range from ~100 μG, for low-mass objects (Li et al. 2014), to ~1 mG, as measured in regions hosting high-mass young stars (e.g., Pillai et al. 2016; Momjian & Sarma 2017). If we consider the N,J = 1, 1 ← 0, 1 transition (286.3 GHz), for which the largest Zeeman shift was obtained (Z = 0.87 Hz/μG), and we assume that B varies in the 0.1–1 mG range, we derive ΔνZ≃ values in the 87–870 Hz range, that is, 0.3–3 m s-1. Moving to higher frequencies and considering the SO N,J = 2, 2 ← 1, 2 transition at 309.5 GHz, we derive ΔνZ ≃ 61−610 Hz, that is, 0.06−0.59 m s-1. In conclusion, in such cases, only information about the LoS component of B, B∥, is obtained. In fact, the Stokes parameter Q and U spectra are usually too weak to be detected. The analysis is therefore limited to the Stokes V spectrum, which has the shape of the first derivative of the Stokes I spectrum and is proportional to (ΔνZ/δν)2 × B∥. According to Crutcher et al. (1993), Crutcher (2012), and Uchida et al. (2001), the standard procedure is to fit dI/dν to the observed V spectrum, with B∥ being the free parameter to be determined from the strength of the V spectrum. Furthermore, the direction (toward or away from the observer) of B∥ is obtained. Therefore, accurate laboratory (either experimental or theoretical) determination of the g factors might provide the opportunity to complete the missing information.
Citation: Momjian & Sarma 2017
Citation function: Uses; Uses
We introduce the quantity ξ to represent a scaled product of equilibrium temperature (Teq) and surface gravity (g):
(14)$$\begin{eqnarray}
\xi = \left(\frac{T_{\text{eq}}}{1000~\text{K}}\right)\left(\frac{g}{g_{\rm J}}\right) ~,
\end{eqnarray}$$where gJ is the surface gravity of Jupiter. The calculated ξ values are listed in Table 4, along with the equilibrium temperature, surface gravity, and scale height for each planet. Fig. 6 shows the relative height of sodium for all 10 planets against ξ. The weight-combined results are shown in dark-blue, together with the unweighted results (light-blue) and literature values using the same HARPS/HARPS-N data (grey). The salmon-coloured points show recent results from other high-resolution spectrographs: WASP-69b with CARMENES (Khalafinejad et al. 2021), WASP-76b with ESPRESSO (Tabernero et al. 2021) and GRACES (Deibert et al. 2021), and WASP-121b with ESPRESSO (Borsa et al. 2021). We find that hNa is well described by an exponential trend of the form
(15)$$\begin{eqnarray}
h_{\lambda } = a\text{e}^{-b\xi } + c ~.
\end{eqnarray}$$As shown in Fig. 6, we fit this curve to the weight-combined results using the optimize.curve_fit function from scipy. The best-fitting values for the variables are: a = 1.70 ± 1.04, b = 5.04 ± 1.63, and c = 0.113 ± 0.013. The reduced chi-square of the fit across the full sample is $\chi ^2_\nu = 3.7$, much of which is skewed by two planets that deviate from the fit by more than 3σ (WASP-79b and HD 189733 b). The reduced chi-square when excluding these two planets is $\chi ^2_\nu = 1.2$. Since the exponential curve is asymptotic to the value of c, our results suggest that planets with ξ ≳ 1.25 are likely to have an upper limit on hNa of ∼0.113. The sodium features could potentially be muted due to other atmospheric effects, such as high-altitude clouds and hazes in lower temperature planets, or ionization of most of the sodium in extremely irradiated environments. Therefore, results lower than those given by equation (15) are also possible. The underlying physical processes behind this trend are not discussed in this current work, but these results motivate further observations to confirm the trend and theoretical studies to investigate possible physical mechanisms. Further refinement of this curve will be possible with more observations of low-ξ planets.
Citation: Borsa et al. 2021)
Citation function: Uses; Uses
It is important to note that we have not classified our simulated galaxies by morphology itself in this paper, and more detailed analysis of the morphology, including kinematical decomposition, will be made in future work. In Fig. 4, we show the distributions of our morphology indicators, ETGΔs, LTGΔs, ETGΔt, and LTGΔt, with stellar mass. The top panel shows that LTGΔt  dominate at low mass, and ETGΔt, which have experienced a major merger within 1 Gyr, are more numerous above M* ∼ 5 × 1010M⊙; the ETGΔt fraction is ∼45 per cent and ∼85 per cent at M* ∼ 5 × 1010M⊙ and ∼1011M⊙, respectively. Since mergers are strong drivers of morphological change, this implies that our high-mass galaxies are mostly elliptical, which is in good agreement with observational results for ellipticals and S0 galaxies (e.g. Bernardi et al. 2010; Tempel et al. 2011). There is not a perfect correlation between galaxy morphology and tmerge, however, and the details of each individual merger are important. In the lower panel of Fig. 4, galaxies are separated by ΔSFMS. Galaxies that lie close to the SFMS (LTGΔs) are most numerous at lower masses, and constitute a declining fraction of the galaxy population with increasing mass, but the fraction of ETGΔs is not perfectly consistent with observations (e.g. Renzini & Peng 2015, ∼50 per cent and ∼75 per cent at log M* = 10.5 and 11). This means that our AGN feedback is probably not strong enough (see TK15a for more discussion). Our predicted distribution of gradients could be affected by these effects. Our galaxies that are classified as both LTGΔs and ETGΔt should be ellipticals, and their metallicity gradients may be too steep because of the lack of quenching of star formation. Therefore, we think our sample of ETGΔs is better for the comparison with observations of SAURON and ATLAS3D. For low-mass galaxies, the lack of resolution could result in underestimating gradients in general. However, our low-mass LTGΔs and LTGΔt galaxies, it could also overestimate the gradients in the case that the gradients would be measured along small star-forming discs, which are not resolved in our simulations.
Citation: Tempel et al. 2011
Citation function: Similarities
Observations of splits in the MS and at the eMSTO of young and (at least) moderately massive Magellanic Cloud star clusters have demonstrated the presence of complex stellar populations, suggestive of variations in their stellar rotation properties (Milone et al. 2018a). The effects of stellar rotation on stellar populations have been observed in Galactic open clusters as well (Marino et al. 2018b). Nearly all of these young star clusters are sufficiently massive to host MPs among their MS stars. For example, NGC 1755, a young cluster with a mass of ∼104 M⊙ (Milone et al. 2016) or NGC 419, another young massive cluster with an age of 1.72 Gyr and a mass of ∼104 M⊙, are comparably massive with respect to other star clusters that show clear evidence of MPs (Martocchia et al. 2018a). Thus, clusters with minimum masses of order 104 M⊙ tend to show evidence of MPs. However, at present such a mass threshold has yet to be explained theoretically. If we assume that mass is an important driver of MP formation, then NGC 411 should also have shown clear evidence of chemical abundance variations among its RGB stars. However, we have found no such evidence in NGC 411, which challenges the idea that mass may be the only or even the main driver of MP formation. The similarity of the observed RGB width in NGC 411 with that expected for an SSP suggests an absence of significant chemical abundance variations. In fact, for NGC 411, NGC 1718, and NGC 2213 we derive maximum possible helium-abundance variations of δY = 0.003 ± 0.001(Y = 0.300), 0.002 ± 0.001(Y = 0.350), and 0.004 ± 0.002(Y = 0.300), respectively. We determined an upper limit to the nitrogen-abundance variation in NGC 411 of Δ[N/Fe] = 0.3 dex, although the available data did not allow us to determine useful upper limits for our other sample clusters. Combined with similar results for NGC 419, NGC 1806, and NGC 1846 (Martocchia et al. 2017), our result is indeed inconsistent with mass being the primary driver of MP formation, although it seems likely that a sizeable minimum mass is still required.
Citation: Martocchia et al. 2018a
Citation function: Differences
In this work we aim to explore the presence and properties of LSBGs in the environment of the NGC 1052 group of galaxies. This region is of particular interest in light of the “exotic” properties that recent works claim for some LSBGs found in this region. For instance, van Dokkum et al. (2018a) in [KKS2000] 04 (more commonly known as NGC 1052-DF2) and van Dokkum et al. (2019a) in NGC 1052-DF4 claimed the similarity between the observed baryonic matter and the dynamic matter obtained by the radial velocity dispersion of their GCs and also the stellar component (Emsellem et al. 2019; Danieli et al. 2019). This observational evidence would imply an extreme and unexpected deficit (even lack) of dark matter in these LSBGs. Taking into account that their metallicity content follows the usual stellar mass–metallicity relation for dwarf galaxies (Fensch et al. 2019; Ruiz-Lara et al. 2019), the possibility that they are tidal dwarf galaxies – galaxies formed by strong interactions with recycled material from massive host galaxies, high in metals, and intrinsically born with a lack of dark matter (see e.g., Duc 2012; Román et al. 2021) – is ruled out. The properties of these LSBGs have been the subject of much debate (see e.g., Martin et al. 2018; Ogiya 2018; Famaey et al. 2018; Kroupa et al. 2018; Lewis et al. 2020; Haslbauer et al. 2019; Müller et al. 2019; Nusser 2019; Montes et al. 2020, 2021). One hypothesis put forward by Trujillo et al. (2019) is that these LSBGs “lacking dark matter” could be at a closer distance than initially estimated by van Dokkum et al. (2018a, 2019a). This would not only make the stellar mass smaller (leaving room for a higher M/L fraction and therefore recovering a certain amount of dark matter, alleviating its strong deficit) but would also resolve the other anomalies that these LSBGs have related to their globular cluster luminosity function (GCLF) (e.g., Shen et al. 2021a), something considered a universal property of any galactic population, including LSBGs (e.g., Jordán et al. 2007; Villegas et al. 2010; Rejkuba 2012; Amorisco et al. 2018; Prole et al. 2019b). However, the distance to these galaxies is still the subject of intense debate (van Dokkum et al. 2018b, 2019b; Blakeslee & Cantiello 2018; Monelli & Trujillo 2019; Danieli et al. 2020; Shen et al. 2021b; Zonoozi et al. 2021) and there is currently no broad consensus on these distance values, with the remaining debated range of distances being approximately 12–22 Mpc.
Citation: Duc 2012
Citation function: Differences; Differences