adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016A&A...585A..17A (fulltext)
ratio with a different method that is not affected by the neglected terms in the Poisson equation and accounts for the DM close to the disk. The influence of the DM component on the stellar mass-to-light ratios of the DiskMass Survey galaxies was previously investigated by Swaters et al. (2014) . There, the correction for DM followed the strategy of Bottema (1993) , which depends on the estimated DM density in the mid-plane, which is not ideal. It also relies on an incomplete estimation of the stars+DM surface density from Eq. ( 6 ). They found that accounting for DM reduced their original average mass-to-light ratio from 0.3 to a stellar mass-to-light ratio of 0.24, but expect a larger decrease if a more rigorous approach was applied. The approach used here is to compute the expected contribution to the stellar velocity dispersion from the DM halo gravity and the disk gravity, respectively. This is done using the Jeans equation, Eq. ( 4 ). We note that the contribution of the gravitational field generated by each matter type to the stellar velocity dispersion is modulated by the vertical range of the old disk stars, , in Eq. ( 4 ). Fig. 2 Vertical gravitational field modulated by the vertical stellar density profile as a function of the height above the disk at . The solid lines correspond to UGC 3091 and the dashed lines to UGC 3140. The red lines reflect the stellar gravitational field, the black lines reflect the DM, and the blue lines are the sum of the black and red lines. Although the stars typically outweigh the DM in the mid-plane, the vertical component of the DM gravitational field can often reach parity at about one scale height. Obviously, this will be even more severe when the stellar mass-to-light ratio is low. This is illustrated in Fig. 2 , which shows the weighted vertical force for the stellar disk and DM halo components. For the stellar contribution, the from M13a is used (and hence is most often sub-maximal) and the DM halo is the pseudo-isothermal sphere fitted by M13a to the rotation curve (see their Table 6, Cols. 4 and 5). This is given for one of the more DM-dominated galaxies, UGC 3091, and one of the most disk-dominated galaxies, UGC 3140. In Fig. 3 the contribution to the stellar vertical velocity dispersion profile from the DM gravitational field is compared with the stellar contribution. They are computed using the DM and stellar vertical gravitational field profile as the input to Eq. ( 4 ), respectively. For UGC 3091, the DM gravitational field dominates the induced stellar vertical velocity dispersion at all radii, and thus should certainly not be ignored. We recall that the DiskMass strategy was to measure the stellar mass-to-light ratio by assuming a negligible contribution of the DM gravitational field to the velocity dispersion. On the other hand, for UGC 3140 the DM gravitational field contribution to the stellar velocity dispersion is irrelevant at most radii. Fig. 3 Contribution from different
Paper: 2016ApJ...831..152L (fulltext)
may be that star formation is more burst-like (e.g., higher specific SFR; Schreiber et al. 2015 ) at higher z . Intense short-duration starburst episodes may be capable of clearing sightlines through the local ISM, resulting in increased ionizing escape during periods of lower activity, giving rise to the trend in Figure 8 . 5. SUMMARY We present intermediate-resolution absorption-line spectroscopy for four new gravitationally lensed sources, which, together with our earlier work (Jones et al. 2013 ), provides a total sample of seven star-forming galaxies in the redshift interval 4 z 5. Our S/N in all cases is adequate to sample the depth of absorption in low-ionization species, which can act as a valuable indicator of the covering fraction of neutral hydrogen. We describe two methods to convert this covering fraction into estimates of the fraction of LyC photons that are capable of reaching the IGM and undertake a critical analysis of possible uncertainties in our results. Our enlarged sample strengthens the trends discovered in our earlier work. In particular, we find the following: 1. The amount of absorbing gas varies significantly from galaxy to galaxy across our sample. However, only two systems are consistent with a complete coverage of low-ionization gas. The median observed covering fraction is 66%. Following a correction for reddening based on a dust-in-cloud model, we infer a median absolute escape fraction of LyC photons of 19% ± 6%. 2. We discuss various uncertainties in this estimate, including the possibility that the stellar radiation has different covering fractions depending on its ionizing capability, as well as scattered photons that could fill in the absorption-line profiles, mimicking a reduced covering fraction. We demonstrate that, even in the extreme case, these issues would only lower the escape fraction to no less than 11%, a value in broad agreement with independent estimates based on recombination studies of the IGM probed by QSO absorption lines. Further study of low-ion absorption lines in nearby galaxies with recent LyC detections will help determine the degree to which covering fractions may overestimate f esc . 3. For one of our lensed sources, MS 1358, we demonstrate that the low-ionization gas is clearly spatially inhomogeneous, with covering fractions ranging from 40% to 100% across various star-forming clumps. Although our sample generally strengthens the correlation we found earlier whereby the escape fraction increases with the equivalent width of Ly α emission, the scatter increases when we consider trends in the individual star-forming clumps in MS 1358, consistent with recent numerical simulations. As the escape fraction is anticorrelated with the local SFR, this suggests a time delay between a burst and the emergence of leaking LyC photons. 4. Overall, our observations indicate significant variations in the escape fraction, both from galaxy to galaxy and spatially within an individual galaxy.
Paper: 2017A&A...601A.120B (acknowledgments)
B.D. thanks the University of Exeter for support through a Ph.D. studentship. N.J.M. and J.G.’s contributions were in part funded by a Leverhulme Trust Research Project Grant, and in part by a University of Exeter College of Engineering, Mathematics and Physical Sciences studentship. We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, a strategic partnership between the Met Office and the Natural Environment Research Council. This work also used the University of Exeter Supercomputer, a DiRAC Facility jointly funded by STFC, the Large Facilities Capital Fund of BIS and the University of Exeter. We thank an anonymous reviewer for their thorough and insightful comments on the paper, which greatly improved the manuscript.
Paper: 2020A&A...642A.114P (fulltext)
giant branches and computed the difference between the obtained interpolated [Fe/H] values and those given by the respective isochrones ([Fe/H] = −2.0, −1.5, −1.0, −0.5, and 0.0 dex). We repeated this procedure for log(age/yr) = 9.4 and 9.8. By using these theoretical points and the general trend observed in Fig. 11 , we adopted weighted mean [Fe/H] values for each cluster (see Table 1 ). Figure 13 depicts the resulting distribution using the adopted mean metallicities. Fig. 11. Metallicity difference as a function of the star cluster’s age. Filled circles, squares, and triangles correspond to high-resolution spectroscopy, low-resolution spectroscopy, and photometry reference values, respectively. Open magenta diamonds represent metallicity differences derived from theoretical isochrones (see text for details). Fig. 12. Theoretical red giant branches for log(age/yr) = 9.0 (dotted lines) and 10.10 (solid lines); [Fe/H] = −2.0, −1.5, −1.0, −0.5, and 0.0 dex shown with blue, magenta, green, orange, and red, respectively. With the aim of providing an expression for the metallicity correction that covers a wide age range, we added ten LMC old globular clusters studied by Piatti Koch (2018) from Strömgren photometry. We took from that study the star clusters’ ages as well as both reference and Strömgren metallicities, with their respective uncertainties. They are represented in Figs. 11 and 13 with open circles. When performing a least square fit to all the data points, we obtained the following expression: Fig. 13. Same as Fig. 11 for adopted weighted mean [Fe/H] values. The solid line represents the least squared fit obtained (see text for details). with a standard deviation, a correlation factor, and an F-test coefficient of 0.05, 0.98, and 0.97, respectively. Strömgren metallicities calculated from Eq. ( 4 ) should be corrected by an amount equal to −Δ[Fe/H]. 5. Summary Based on our previous knowledge that metallicities derived from standard giant branches in several photometric systems are affected by the age-metallicity degeneracy for star clusters younger than the old globular clusters, and bearing in mind the fundamental role that metallicities play in our understanding of the formation and chemical evolution processes at different universe scales, we decided to investigate metallicities for the Strömgren v b y bandpasses. Until now, it has been straightforward to compute [Fe/H] values from the Strömgren reddening free ( v − y ) 0 and m 1 0 indices, the latter being a metallicity-sensitive index. In general, they have been used for the study of globular cluster metallicity distributions (e.g., Calamida et al. 2014 ; Frank et al. 2015 ) to unveil multiple stellar populations (e.g., Carretta et al. 2011 ; Massari et al. 2016 ) rather than estimate the metal content of intermediate-age star clusters. In order to probe whether such an age dependency also affects the Strömgren metallicities, we made use of unexploited publicly available
Paper: 2018ApJ...860..101Z (acknowledgments)
We thank the anonymous referee for comments. We would also like to thank Andy Gould for comments on an earlier version of the manuscript. This paper includes data collected by the Kepler mission. Funding for the Kepler mission is provided by the NASA Science Mission directorate. This paper also uses data from the LAMOST survey. Guoshoujing Telescope (the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, LAMOST) is a National Major Scientific Project built by the Chinese Academy of Sciences. Funding for the project has been provided by the National Development and Reform Commission. LAMOST is operated and managed by the National Astronomical Observatories, Chinese Academy of Sciences. C.P. acknowledges support from the Jeffrey L. Bishop Fellowship and from the Gruber Foundation Fellowship. S.D. acknowledges Project 11573003 supported by National Natural Science Foundation of China (NSFC).
Paper: 2016ApJS..224...30Y (fulltext)
2–8 minutes. Figure 2. Same as Figure 1 , but P 0 = 80 s and σ 0 = 30 s. Green dashed lines label the prominent quasi-periodic oscillations in the range of 2–8 minutes. The cone-of-influence is cross-hatched; within it the spectrum should be considered unreliable. 3. NUMERICAL EXPERIMENTS In order to explore how stochastic transients affect the upper atmosphere, we create a set of numerical experiments and investigate how the power spectrum is altered observationally throughout its propagation in a stratified atmosphere. We do not attempt to model realistic transients at photospheric temperature and density, but only demonstrate what response could be observed if this sort of perturbation was triggered in the lower atmosphere. 3.1. Empirical Model of the Atmosphere Figure 3 plots the one-dimensional model of the atmosphere used in this study. Below z = 2.22 , we implemented the mid-age sunspot umbra model of Maltby et al. ( 1986 ); close to the bottom boundary ( z 1.2 ), we set a constant temperature (6471 ). Above z = 2.22 , we adapted the C7 model of Avrett Loeser ( 2008 ); near the upper boundary (), we set a constant temperature of 1.3 . This kind of model of temperature has been used in a number of previous studies, e.g., Heggland et al. ( 2007 ), Botha et al. ( 2011 ), and Snow et al. ( 2015 ). Figure 3. Empirical model of the atmosphere used in this study; the inset enlarges the temperature profile at z 2.5 . In hydrostatic equilibrium, the pressure is obtained by integrating the gravitational force ρg , where p , ρ , and T are the plasma pressure, density, and temperature, respectively, is the gravitational acceleration at the surface of the Sun, k B is the Boltzmann constant, and m p is the mass of a proton. We choose a base density of at z = 0 , so at coronal height the density is of the order of , see Figure 3 . In one-dimensional MHD simulation, the magnetic field decouples from hydrodynamic equilibrium; we used B = 10 , in line with the z -axis, in our simulations. The plasma parameters were normalized by choosing a set of three to be constant: the length L 0 = 1.0 , the density , and the magnetic field strength B 0 = 10 . Then the normalization factor for the velocity is , the time t 0 = 31.7 s, the gravitational constant , and the temperature T 0 = 0.06 . So the variables become dimensionless by using , , , , , , , etc., where symbols with a hat are dimensionless variables. 3.2. Magnetohydrodynamic Simulation We used the AMRVAC package (Keppens et al. 2012 ; Porth et al. 2014 ) to solve the ideal MHD equations with the finite-volume method: where is the fluid velocity, the magnetic field vector, the solar gravity vector, the unit tensor, the total energy density, the total pressure, γ the adiabatic index, and μ 0 the magnetic permeability of free space. The AMRVAC code was configured to solve Equations ( 6 )–( 10 ) in Cartesian coordinates [ x , y , z ]. The physical quantities were assumed to be invariant along the x - and
Paper: 2015ApJ...815...32K (acknowledgments)
The authors would like to thank Elliott Horch, Steve Howell, and Suvrath Mahadevan for several useful discussions. Thanks are also due to the anonymous referee whose helpful comments improved the manuscript. D.H. acknowledges support by the Australian Research Council's Discovery Projects funding scheme (project number DE140101364) and by NASA under Grant NNX14AB92G issued through the Kepler Participating Scientist Program. E.V.Q. is supported by a NASA Senior Fellowship at the Ames Research Center, administered by Oak Ridge Associated Universities through a contract with NASA. This work made use of the Digitized Sky Survey (DSS) hosted by the Mikulski Archive for Space Telescopes (MAST). This work was supported by a NASA Keck PI Data Award, administered by the NASA Exoplanet Science Institute. Data presented herein were obtained at the W. M. Keck Observatory from telescope time allocated to the National Aeronautics and Space Administration through the agencys scientific partnership with the California Institute of Technology and the University of California. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna Kea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain.
Paper: 2018A&A...609A..63V (fulltext)
which indicates the importance of non-equilibrium chemistry in the inner wind. Moreover, as the initial HCN abundance of R Dor and IK Tau lie within a factor of 2 of each other, quite similar physical and chemical conditions are likely present in their inner winds independent of mass-loss rate. The factor of 2 difference might be due to the lower mass-loss rate of R Dor or different pulsation characteristics. Fig. 8 Black: integrated line strengths of HCN modelled using a Gaussian abundance profile characterised by = with respect to H and cm. Overplotted are the integrated line strengths measured with APEX (red circles), SEST (blue circles), and HIFI (purple circles). The error bars for the resolved molecular lines correspond to an absolute error of 20%. Fig. 9 Range in abundance profiles found for HCN throughout the CSE. The molecular transitions probe the region marked between dashed vertical lines. 6. Conclusions We have constrained the radial abundance profile of SiO and HCN in the stellar wind of the low mass-loss M-type AGB star R Dor using a non-LTE extended atmosphere model that accounts for the interaction between gas and dust. Our analysis used the integrated line intensity and line profile shapes of a set of lines obtained with both ground- and space-based instruments. For SiO, we used 42 molecular transitions, of which 16 are spectrally resolved. The molecular data are sensitive to the region between approximately 5 and 100 . The initial abundance of SiO lies between and with respect to H. The abundance profile is constant up to , after which it follows a Gaussian profile with an e-folding radius between cm. The decline in SiO abundance near 60 might be due to condensation onto dust grains or photodissociation. We are unable to unambiguously determine the mechanism at work. For HCN, we used five resolved molecular transitions. The molecular data are sensitive to the region between approximately 7 and 40 . The initial abundance of HCN lies between and with respect to H. The abundance profile is a Gaussian profile centred on the star with an e-folding radius between cm. The initial abundances found are higher than those reported in previous studies (with the exception of the study by Khouri 2014 , for SiO). This might be due to our inclusion of higher- molecular lines. Compared to results for IK Tau, a high mass-loss rate M-type AGB star, the onset of photodissociation occurs closer to the star for both SiO and HCN. This can be explained by their difference in mass-loss rate. The R Dor initial abundance of SiO is also higher than those found for IK Tau. This might be due to different pulsation characteristics of the central stars and/or a difference in dust condensation physics. It is not connected to a differing sensitivity to non-equilibrium chemistry in the inner wind, as this molecule is unaffected by such processes ( Cherchneff 2006 ). For both stars, we find roughly similar HCN abundances, though both are five orders of
Paper: 2015ApJ...808..121T (acknowledgments)
We acknowledge the anonymous referee for many useful suggetions. We are grateful to the ASTE team for making the observations possible. We thank M. Béthermin and I. Shimizu for making the model number counts available. The study is partially supported by KAKENHI (No. 25103503). Y.S. and K.T. are supported by the JSPS Research Fellowship for Young Scientists (Nos. 09J05537 and 09J00159, respectively). This work is based on observations and archival data made with the following telescopes and facilities. The ASTE telescope is operated by National Astronomical Observatory of Japan. The Australia Telescope Compact Array is part of the Australia Telescope National Facility, which is funded by the Commonwealth of Australia for operation as a National Facility managed by CSIRO. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA. NRAO is a facility of the NSF operated under cooperative agreement by Associated Universities, Inc. The 45 m radio telescope and the Nobeyama Millimeter Array are operated by Nobeyama Radio Observatory, a branch of National Astronomical Observatory of Japan. The Submillimeter Array is a joint project between the Smithsonian Astrophysical Observatory and the Academia Sinica Institute of Astronomy and Astrophysics and is funded by the Smithsonian Institution and the Academia Sinica. The Spitzer Space Telescope is operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. The Subaru Telescope is operated by National Astronomical Observatory of Japan. The United Kingdom Infrared Telescope is operated by the Joint Astronomy Centre on behalf of the Science and Technology Facilities Council of the U.K. This publication makes use of data products from the 2MASS, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. Facilities: ASTE (AzTEC) , ATCA , Herschel (SPIRE) , VLA , NoMA , Nobeyama 45 m (T100, BEARS) , SMA , Spitzer ( IRAC , MIPS ), Subaru (MOIRCS) , UKIRT (WFCAM) , WISE .
Paper: 2020MNRAS.492.3622L (acknowledgments)
ACKNOWLEDGEMENTS We acknowledge the use of public data from the Fermi data archive. This work is supported by the National Natural Science Foundation of China (grant nos 11922301, 11603006, 11851304 and 11533003), the Guangxi Science Foundation (grant nos 2017GXNSFFA198008, 2018GXNSFDA281033, AD17129006 and 2018GXNSFGA281007), and also by the One-Hundred-Talents Program of Guangxi colleges, the Bagui Young Scholars Program (LHJ), and special funding for Guangxi distinguished professors (Bagui Yingcai Bagui Xuezhe).
Paper: 2016ApJ...831...16L (acknowledgments)
We gratefully acknowledge the ALMA, IRAM, CARMA, and MOPRA facilities and thank the M33 and MAGMA teams for making their data public. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2011.0.00876.S, ADS/JAO.ALMA#2012.00650. ALMA is a partnership of ESO (representing its member states), NSF (USA) and NINS (Japan), together with NRC (Canada), NSC and ASIAA (Taiwan), and KASI (Republic of Korea), in cooperation with the Republic of Chile. The Joint ALMA Observatory is operated by ESO, AUI/NRAO, and NAOJ. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. Based on observations carried out with the IRAM 30 m telescope. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain). A.E. acknowledges partial support from grants PFB #06, FONDECYT #1130458, and ACT #1101. A.H. acknowledges support from the Centre National d’Etudes Spatiales (CNES). A.U. acknowledges support from Spanish MINECO grants AYA2012-32295 and FIS2012-32096. J.M.D.K. gratefully acknowledges financial support in the form of a Gliese Fellowship and an Emmy Noether Research Group from the Deutsche Forschungsgemeinschaft (DFG), grant number KR4801/1-1. J.P. thanks the CNRS/INSU program PCMI for support. M.Q. and S.E.M. acknowledge funding from the Deutsche Forschungsgemeinschaft (DFG) via grants SCHI 536/7-2, SCHI 536/5-1, and SCHI 536/7-1 as part of the priority program SPP 1573 “ISM-SPP: Physics of the Interstellar Medium.” M.Q., S.E.M., and E.S. acknowledge financial support to the DAGAL network from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme FP7/2007-2013/ under REA grant agreement number PITN-GA-2011-289313. E.R. is supported by a Discovery Grant from NSERC of Canada. G.B. is supported by CONICYT/FONDECYT, Programa de Iniciacion, Folio 11150220.
Paper: 2015ApJ...810...18T (acknowledgments)
We are grateful for the referee for constructive comments that have helped us to improve our paper. This work is supported in part by a Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (JSPS; No. 27-2450 for D.T.) and by a Grant-in-Aid for Scientific Research (25287062) of the Ministry of Education, Culture, Sports, Science and Technology in Japan.