adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.490.2890J (acknowledgments)
ACKNOWLEDGEMENTS First and foremost, we would like to record our sincere gratitude to Achim Weiss for his guidance and input. His valuable insights and our fruitful discussions have greatly contributed to this paper. We would like to thank Zazralt Magic for providing the Stagger grid as well as James Kuszlewicz and Earl Bellinger for their useful discussions. Part of the research leading to the presented results has received funding from the European Research Council under the European Community’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no 338251 (StellarAges). Software: Calculations were performed using the hephaestus pipeline (Angelou, in prepreparation) making use of the garstec (Weiss Schlattl 2008 ; Jørgensen et al. 2018 ) stellar evolution code and the adipls pulsation package 0.3 (Christensen-Dalsgaard 2008 ). Analysis in this manuscript was performed with anaconda 3.6.8 and python 3.6.8 packages NumPy 1.15.0 (Van Der Walt, Colbert Varoquaux 2011 ), scipy 1.2.1 (Jones et al. 2001 ), pandas 0.23.3 (McKinney et al. 2010 ), emcee 2.2.1 (Foreman-Mackey et al. 2013 ), matplotlib (Hunter 2007 ), corner 2.0.1 (Foreman-Mackey 2016 ), wquantiles 0.5 (Sabater 2015 ), and sobol (Burkardt Chisari 2011 ).
Paper: 2018ApJ...856...36T (acknowledgments)
We wish to thank Trevor Dorn-Wallenstein, David Kann, Locke Patton, Patricia Schady, and Paula Szkody for their valuable advice and feedback on this work. We also wish to thank the anonymous referee for invaluable feedback that has greatly improved the quality of this manuscript. This paper was based on observations (Program ID GS-2016B-FT-7) obtained at the Gemini South Observatory (processed using the Gemini IRAF package) as part of the Gemini Fast Turnaround program. We thank the entire support staff of the Gemini Observatory for their efforts and assistance, with particular thanks to Kristin Chiboucas, Mischa Schirmer, Rene Rutten, and Morten Anderson. Gemini is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).
Paper: 2016MNRAS.460.4403R (fulltext)
has been observed. Detection of radio flare during the HIMS of GX 339−4 (2002 outburst) and the first and second flares in V404 Cyg, indicate similar characteristics. Since the source MAXI J1836−194 is not observed to have transited to a SIMS or HSS (Ferrigno et al. 2012 ; Russell, Soria Miller-Jones 2014 ), the system of jet ejection for such sources which have ‘failed outbursts’ seems to be different as compared to other BH sources. Although Russell et al. ( 2013 ) suggests the presence of a compact jet, the fact that QPOs are not observed suggests of a probable transient jet ejection event. A deeper look into the properties of the companions of these BHs suggests them to be of late F, G, K or M type (Sanchez-Fernandez et al. 1999 ; Hynes et al. 2003 ) which are in general magnetically active (Linsky 1985 ), with field strength around 1 kilogauss. This suggests that the models which specify the role of magnetic fields in formation of jets by evacuation of the Comptonized corona (see Section 4 and Nandi et al. 2001 ) are applicable for these sources, wherein the magnetic field from the companion flows along-with the matter into the accretion disc. This field probably gets amplified during the rising phase of the outburst (i.e. the LHS and HIMS) and finally collapses to push out the matter from the corona (Nandi et al. 2001 ; Fender et al. 2004 , 2009 ) forming jets/flares, as the source enters the SIMS. The time-scale required for amplification of the field is equivalent to the rising time of the source upto the end of the HIMS when the jet ejection occurs. A typical BH source with a fast rise and exponential decay light curve requires around 10 d to reach the transition point from HIMS to SIMS. For the sources studied in this paper which have a typical fast rise-time (XTE J1859+226, H 1743−322, XTE J1748−288, GRO J1655−40, XTE J1550−564), the time-scale required for the field amplification is found to vary from 5 to 15 d. In these sources, we find that the peak radio flux is higher and varies between 100 and 600 mJy, except the 2009 outburst of H 1743−322 and 2005 outburst of GRO J1655−40 which have very less radio flux during the moment of ejection (5.7 and 1.6 mJy, respectively) and also while in the peak. For the sources which have a slow rise towards the X-ray peak require more time to reach the transition point i.e. they take larger time-scale to amplify the magnetic field. As an example XTE J1752−223 requires 88 d, 48 d is taken by GX 339−4 during its 2002 outburst and 104 d for GX 339−4 during its 2010 outburst. For these sources, the peak radio flux is found to vary from 18 to 55 mJy. Fender et al. ( 2004 ) has performed detailed study on the estimation of the jet power based on the characteristics of the radio flare, like its rise time and flux density (see also Fender Munoz-Darias 2016 ). It is also possible to have a quantitative estimation of the kinetic jet power based on the X-ray characteristics of the source. Recently Aktar,
Paper: 2016MNRAS.457.3801P (acknowledgments)
We are thankful to Dan Harris for providing us with the M87 NRAO radio data, flux measurements and many insightful comments on the manuscript. AP acknowledges M. Krause, E. Churazov, and R. Sunyaev for discussions. SM is grateful to the University of Texas in Austin for its support, through a Tinsley Centennial Visiting Professorship. AP acknowledges financial support from the Spanish 2011 Severo Ochoa Program SEV-2011-0187, and the hospitality of the CAST group of the Ludwig Maximilians University of München (LMU) and the Max-Planck Institute für extraterrestrische Physik where most of this work was done. Based on VLT 4.B-0404(A), 76.B-0493(A), ALMA 2011.0.00754.5, NRAO AH 822, 862, 885, Chandra 3088.
Paper: 2015MNRAS.448..814I (acknowledgments)
We thank the Planck collaboration for making available the calibration sample in the SZ cluster data base ( http://szcluster-db.ias.u-psud.fr ). We thank the referee for helpful comments. HI would like to thank D. Applegate for a helpful discussion. HI acknowledges support from European Research Council grant MIRG-CT-208994 and Philip Leverhulme Prize PLP-2011-003. JN acknowledges a PUT 246 grant from Estonian Research Council. RJM is supported by a Royal Society University Research Fellowship. THR acknowledges support from the German Research Association (DFG) through Heisenberg grant RE 1462/5 and through the Transregional Collaborative Research Centre TRR33 ‘The Dark Universe’ (project B18). GS and THR acknowledge DFG grant RE 1462/6. This research has made use of the SZ-Cluster Database operated by the Integrated Data and Operation Center (IDOC) at the Institut d'Astrophysique Spatiale (IAS) under contract with CNES and CNRS.
Paper: 2017MNRAS.465..997C (fulltext)
). Moreover, due to the compactness, compact radio sources trace sightlines towards central denser regions of radial density profiles of the H i disc (Pihlström et al. 2003 ). This could be the other reason for the low detection rate in extended radio sources. Available very-long-baseline interferometry (VLBI) images for some of the compact LERG radio sources with H i absorption detection suggest that these have sizes on the scale of pc. However, we lack complete information on all sources. In HERGs, in addition to clouds in the ISM, a dusty torus in an AGN could give rise to H i absorption if the compact radio source is of a scale similar to or smaller than the torus. Figure 5. Top: log sSFR versus W2−W3. Bottom: log total stellar mass versus log sSFR, for absorption detections (filled symbols) and non-detections (empty symbols). Since H i absorption detections as well as star-formation rates are higher for WISE ‘late-type’ galaxies, it is relevant to enquire about the possible origins of the gas or fuel. It could be the result of a normal process of galaxy evolution, in which star formation started in a dusty gas-rich environment and decreased at later stages due to scarcity of fuel, combined with possible feedback from a radio source. In addition, star formation or AGN activity may get a boost from dust-rich mergers or interactions. In the literature, suggested fuelling mechanisms vary from major mergers or secular processes for HERGs to accretion of halo gas, stellar remnants, winds from evolved stars or minor mergers for LERGs (Ellison et al. 2015 ). Also, LERGs are reported with suppressed star formation in the literature (Gürkan et al. 2015 ; Ellison et al. 2016 ; Pace Salim 2016 ). Although this may be true for a majority of the LERGs in our sample, it does not explain the higher H i gas detection rate and higher rate of star formation in WISE ‘late-type’ LERGs. There have been suggestions for higher rates of mergers for WISE IR-selected AGNs with W1−W2 > 0.8 (Satyapal et al. 2014 ; Ellison et al. 2016 ). However, as can be seen from Fig. 2 , our sample hardly has any AGNs with W1−W2 > 0.8. Also the optical host galaxies do not suggest any significant morphological differences, except for a few cases of disturbed morphology or evidence of interaction with a companion galaxy, e.g. J105327.2+205836. To understand these aspects and clarify any possible evolutionary scenario, we fit a first-order linear function in log sSFR versus WISE colour for LERG detections, non-detections and also for compact and extended LERGs separately. Using the Kendall tau test, we find that there exists a significant correlation (τ = 0.47, p = 4.37 × 10 −10 ) between log sSFR and WISE W2−W3 colour (Fig. 6 ). The left panel of Fig. 6 also shows that compact radio sources (slope: 0.81 ± 0.12) and detections (slope: 0.78 ± 0.16) have similar flatter slopes, while extended sources (slope: 0.98 ± 0.19) and non-detections (slope: 0.96 ± 0.14) have similar and
Paper: 2017ApJ...837...42D (fulltext)
Figure 10 that their N/H ratios are also some of the lowest in the dwarf galaxy sample. However, as shown in Figure 9 , their N/O ratios cover the range of N/O ratio values of all the dwarf galaxies studied. This is consistent with the expectation that nitrogen behaves as a primary element for galaxies with low and moderate metallicities. Details of these 21 dwarf galaxies with extremely low metallicities are listed in Table 3 , including their gas-phase chemical abundances. 6. Conclusions The nucleosynthesis of nitrogen is a vital component of the chemical evolution of galaxies in our universe. We estimate the nitrogen abundance and N/O ratio of dwarf galaxies using the direct T e method and spectroscopic line flux measurements from the SDSS DR7 sample as reprocessed in the MPA-JHU catalog. The 135 galaxies analyzed suggest a slight large-scale environmental dependence of the N/O ratio, where void dwarf galaxies could have a lower N/O ratio than dwarf galaxies in denser environments. Thus, the large-scale () environment might influence the chemical evolution of dwarf galaxies. We find small, statistically insignificant shifts in the mean (or median) N/O ratio for galaxies between the void and denser regions across all blue, star-forming galaxies with . These shifts are somewhat more significant, however, when we look at the entire sample of galaxies. Each magnitude bin is shifted in the same direction, and they are potentially very interesting, as they might indicate delayed star formation histories, more constant SFRs, and larger ratios of dark matter halo mass to stellar mass in void galaxies, as discussed in Section 5 . A larger sample would help test these results. We look to increase the sample and probe a larger magnitude (and mass) range of dwarf galaxies in K. A. Douglass M. S. Vogeley (2017, in preparation). In addition, we look at the relationship between the N/O ratio and other physical characteristics of our dwarf galaxies. In the relation between N/O and O/H, our galaxies all reside on the so-called “nitrogen plateau,” where the N/O ratio is predicted to be constant for low and intermediate metallicities. However, instead of a constant value for these galaxies, we find a negative correlation between the N/O and O/H ratios. Our dwarf galaxies show a positive correlation between stellar mass and the N/O ratio. These dwarf galaxies have some of the lowest N/O ratios for both their color and (s)SFR. Beyond the suggestive large-scale environmental dependence of the N/O ratio, there is no clear large-scale environmental dependence in any of these relationships. The N/O ratios of the extremely metal-poor dwarf galaxies are no different than those of the remaining dwarf galaxy sample, though their N/H abundance is also extremely low. A more detailed study of these 21 extremely metal-poor dwarf galaxies is recommended to confirm their abundance values and discover any characteristics shared by the population. Although SDSS provides
Paper: 2015MNRAS.450..277C (acknowledgments)
Density maps were created with splash , by Price ( 2007 ). We thank the anonymous referee for useful comments that greatly helped us to improve the presentation of the paper. JC acknowledges support from CONICYT-Chile through FONDECYT (1141175), Basal (PFB0609) and Anillo (ACT1101) grants, and the warm hospitality at Leicester. Theoretical astrophysics research in Leicester is supported by an STFC Rolling Grant. QDW acknowledges the support by NASA via the SAO/CXC grant TM3-14006X. This work was performed using the Geryon computers at the Centre for Astro-Engineering UC, funded by Basal PFB-06, QUIMAL 130008 and Fondequip AIC-57.
Paper: 2017MNRAS.466..320H (acknowledgments)
Acknowledgments The project was supported partially by Polish National Science Center grants DEC-2011/01/N/ST9/06000 and DEC-2012/07/B/ST9/04412. We thank Nathan Leigh for very insightful comments and suggestions which helped us to significantly improve the text of the paper.
Paper: 2016ApJ...833..229L (fulltext)
the turbulence-regulated star formation model of Krumholz McKee ( 2005 ) to allow time-variable ff in the prescription of Feldmann Gnedin ( 2011 ), we find that ff ∝ t 2 is most consistent with our data. We conclude that star formation is dynamic on the GMC-scale. 10 10 The time-varying ff may arise from the evolution of star-forming clumps embedded in each GMC. Our study concerns the properties of star formation in clouds that have already formed or in the process of forming stars. By construction, we have limited our analysis to 191 SFC-GMC complexes out of 5469. We found 1014 clouds unmatched to SFCs that have the potential to form star clusters (see Section 6.5 ). We surmise that most (5469-1014-191 = 4264; 78% by number) of the GMCs are gravitationally unbound and will never form massive star clusters. It is possible that some locally dense clumps within an unbound GMC form stars (see e.g., Dobbs et al. 2011 ). These clumps likely give birth to lower mass star clusters that our star formation tracers are not sensitive to. Throughout our analysis, we used free–free emission as a proxy for stellar mass. A more direct measurement would be to count YSOs. For known massive clusters, we find a generally good agreement in the measured stellar mass between free–free emission and YSO counts (see Figure 2 ). A more complete comparison may be possible using all-sky YSO catalogs (e.g., Marton et al. 2016 ). This is an important and natural avenue for future improvement. 8.1. Comments on Stellar Feedback If the rate of star formation in the most massive (10 6 M ⊙ and higher) GMCs does accelerate, the process of star formation must halt before ≳ 0.1, roughly the largest value we see in such clouds. Stellar feedback—in the form of stellar winds, radiation pressure, protostellar jets, and supernovae—from massive star clusters can disrupt the natal cloud and inhibit future star formation. The idea that stellar feedback destroys GMCs was proposed long ago by Larson ( 1981 ). Galactic-scale numerical simulations (e.g., Hopkins et al. 2011 and Faucher-Giguère et al. 2013 ) find that the effects of stellar feedback are necessary for regulating star formation rates to the Kennicutt-Schmidt value. Turbulence in the ISM alone cannot slow the rate of star formation. The existence of large expanding bubbles—a few to ∼100 pc wide—associated with regions bright in free–free emission is evidence for the effects of stellar feedback from young clusters (referred to as SFCs by Rahman Murray 2010 and Lee et al. 2012 ). These massive young clusters, which power most of the free–free emission in the Milky Way, are identified by clear cavities in the 8 μ m emission. The clusters are found in massive GMCs, but the star clusters are not enshrouded in molecular gas—they are instead in regions of ionized gas, which are enshrouded in molecular gas. In some cases, the massive stars may still be accreting gas from their natal protostellar disks, but the disks are not accreting gas
Paper: 2016A&A...591A..70K (fulltext)
from one epoch to the other, the polarised intensity distribution does not change significantly. The departure from axisymmetry is stronger in January 2015 but the location of the maxima and minima of the polarised flux does not change much between the two epochs. We divided the image in octants to facilitate our analysis and to minimise errors introduced by asymmetries of the dust envelope. Octant 1 is limited by the north and north-east directions and the numeration follows clock-wise. The value of the polarised intensity changes considerably for the different octants. In Table 2 we list the fraction of the polarised light measured per octant per filter. The ratio between the intensity from the octants with maximum and minimum polarised intensity is roughly 2.3 for and cntH in the first epoch and 3.7 for cntH in the second epoch. Table 2 Fraction of the polarised flux arising from the different octants for the image in and in cntH. 3. Analysis and modelling of the polarised light We now focus on our modelling efforts to derive the density radial profile of the grains that produce the scattered light. 3.1. Modelling approach We calculated spherically symmetric models using the continuum radiative-transfer code MCMax ( Min et al. 2009 ). The code calculates the direction-dependent scattering of radiation by dust grains and outputs images of the Stokes parameters. We convolved the Q and U images produced by the models with the PSF images. This typically caused a decrease by a factor of 1.5 of the output integrated polarised flux. This is because in the Q and U images the negative and positive lobes from a symmetrical envelope can overlap when the resolution is lowered. This leads to polarised signal in the images to cancel out. The poorer the angular resolution, the larger is the effect. The convolved Q and U images were then combined to obtain the polarised intensity for each model. We calculated the radial profile of the polarised intensity from the observations for each octant and compared these profiles independently to the models. We considered two different envelope structures: with dust grains distributed in a thin halo with constant density (model with no outflow), and with a dust density gradient given by , being the inner radius of the dust envelope and . We varied between 1.2 and 2.0 for both envelope structures and the halo thicknesses between 0.25 and 1.5 for the thin-halo scenario, where mas ( Norris et al. 2012 ). We use amorphous MgSiO grains with the optical constants obtained by Jäger et al. (2003) , as this dust species is one of the main candidates for driving the winds of oxygen-rich AGB stars (see, e.g., Bladh Höfner 2012 ). We have also experimented with optical constants for MgSiO and AlO, as discussed in Sect. 4.1.2 . To calculate the absorption opacities and the direction-dependent scattering properties, we approximate the actual size distribution of particle sizes by a distribution of hollow spheres ( Min et al.
Paper: 2016ApJ...817..145S (fulltext)
in the standard manner for mid-infrared ground-based imaging observations, including dark subtractions and flat fielding. The flux calibration of V1280 Sco was achieved using measurements of the two standard stars listed in Cohen et al. ( 1999 ): λ Sgr for N8.8, N11.7, and Q18.8, and μ Cep for Q24.5. The aperture size for the photometry was set to be 2′′ in radius. For the NL spectroscopy of V1280 Sco on Day 150, a slit width of 033 was used. As in the case of the imaging observations, only the secondary mirror chopping was performed at a frequency of ∼0.5 Hz with a 10′′ throw in the north–south direction. The position angle (PA) of the slit was set to 0° so that images at both chopping positions would fall on the slit. Spectra collected at both chopping positions were co-added, resulting in the total on-source integration time of 20 s for NL spectroscopy (see Table 2 ). The data reduction was performed in the standard manner for mid-infrared ground-based spectroscopic observations, including dark subtraction, flat fielding using domeflat, wavelength calibration using atmospheric lines, and distortion correction. Finally, a one-dimensional spectrum of V1280 Sco was extracted. Atmospheric absorption in the extracted spectrum was corrected by division by the spectrum of a standard star, λ Sgr, whose absolute spectrum is provided in Cohen et al. ( 1999 ). The absolute flux calibration including the correction for slit efficiency was performed by simply scaling the flux level of the obtained spectrum to match the photometric data in the 8.8 and 11.7 μ m bands. Table 2 Summary of Spectroscopic Observations Note. a The epochs of the observations with Subaru/COMICS, Gemini-S/T-ReCS, and AKARI /IRC in days after the discovery. 2.2. Gemini-S/T-ReCS data Mid-infrared imaging and spectroscopic observations of V1280 Sco on Days 1272, 1616, and 1947 were carried out at the Gemini-South observatory under the Subaru/Gemini Time Exchange Programmes GS-2010B-C-7 on 2010 August 1, GS-2011B-C-4 on 2011 July 10, and GS-2012A-C-5 on 2012 June 6. For the imaging portion, five medium-band filters, Si-1, Si-3, Si-5, Qa, and Qb, were used. The center wavelength, λ c , and bandwidth, Δ λ , are summarized in Table 1 . The pixel scale of the T-ReCS detector was 009 and the FOV was 288 × 216. Both chopping and nodding were performed to cancel out the high background radiation and the chopping residual pattern. The chopping was performed at a frequency of ∼3 Hz with a 15′′ throw in the north–south direction. The on-source integration time is summarized in Table 1 . The mireduce task included in the Gemini IRAF package ( https://www.gemini.edu/node/10795 ) was used to produce final co-added, chop-subtracted, and nod-subtracted data from the raw data files. The flux calibration was accomplished by observing the Cohen standard star HD 151680 (Cohen et al. 1999 ). The aperture size for the photometry was set to be 2′′ in radius. A slit width of 035 was used for the N-band