adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019ApJ...871..197D (fulltext)
it with the stellar mass derived using the optical colors. The H α and NUV emission were used to derive the SFR in the disk. We then discuss the importance of NGC 4701 for understanding the morphological classification of late-type dwarf galaxies and accretion-driven star formation in extended H i disks. Throughout the paper we will assume the distance of NGC 4701 to be 17.1 Mpc. 2. The Bulgeless Spiral Galaxy NGC 4701 NGC 4701 was studied as part of a follow-up H i study of bulgeless disk galaxies (Das et al. 2012 ). It is a nearby spiral galaxy that has often been classified as a blue dwarf galaxy (Vanzi et al. 2009 ) on account of its bright, star-forming disk and small size. It has a small, stellar disk of diameter 8.3 kpc in the K band but in the B band the disk appears far more extended and has a diameter of 13.7 kpc (Table 1 and Figure 1 ). The inner disk has a very compact bright nucleus that is due to nuclear star clusters (Georgiev Böker 2014 ); such clusters have been observed in many bulgeless galaxies (Walcher et al. 2005 ). The nucleus has a bright, slightly off-center hard X-ray source (Lemons et al. 2015 ) that may be due to an active galactic nucleus (AGN; Desroches Ho 2009 ). The disk is very rich in H i gas and has a flux of S ν = 58.2 Jy km s −1 (Popping Braun 2011 ), which corresponds to a mass of M (H i ) = 4 × 10 9 M ⊙ . The H i spectral line width indicates that the disk is possibly extended. The molecular hydrogen gas has a double-horned structure about the nucleus (Vanzi et al. 2009 ) and has a flux of 2.90 K km s −1 (Böker et al. 2003 ) or 13.92 Jy km s −1 . At a distance of 17.10 Mpc (Tully et al. 2009 ), this corresponds to a molecular gas mass of M (H 2 ) = 4.48 × 10 7 M ⊙ . The molecular gas appears to be centrally concentrated, with a total width of ∼150 to 170 km s −1 and a rotation velocity ∼100 km s −1 (Popping Braun 2011 ). Figure 1. HCT optical images of NGC 4701. Clockwise from the top left are the B-, V-, I -, and R- band images. The dashed ellipse in white is the R 25 radius of the galaxy in the B band and is 108′′. The V -band emission extends out to 1/2 R 25 and the B -band extends to 2/3 R 25 approximately. Table 1 Parameters of NGC 4701 Notes. The parameters are from the NASA Extragalactic Database (NED). a The inclination was calculated from the galaxy major and minor axis ratios in the optical band i.e., inc = Cos −1 (179/216). b Tully Fisher distance (Tully et al. 2009 ). 3. H <sc>i</sc> Observations and Data Analysis 3.1. Observations and Moment Maps The H i observations of NGC 4701 were carried out with the GMRT during 2009 November. The baseband bandwidth used was 8 MHz for the H i 21 cm line observations, giving a velocity resolution of 13.6 km s −1 . Further details on the observations are given in Table 2 . To reduce the data the Astronomical Image Processing System ( AIPS ) software package was used. The flux densities are on the scale of mJy (Baars et al. 1977 ), with flux density
Paper: 2016ApJ...831..170W (acknowledgments)
The authors thank The Pennsylvania State University, NASA Astrobiology Institute (NNA09DA76A), and the Penn State Astrobiology Research Center for their support. Portions of this research were conducted with Advanced CyberInfrastructure computational resources provided by The Institute for CyberScience at The Pennsylvania State University ( http://ics.psu.edu ). Special thanks go to Prof. Eric Ford for directing us to Dimitri Veras’ work on including Galactic tides in Mercury . In addition, we thank the anonymous referee for thorough and helpful comments that contributed to the content and clarity of this work.
Paper: 2016ApJ...832...77D (fulltext)
in the legend. The silicon line is solid, the oxygen line is dashed (quiet Sun adjustment) and dotted–dashed (active region adjustment). The two events above were not associated with Fe xxi emission. However, in the same raster set there is a flare with Fe xxi emission. We picked the non-flare data because the explosive events in these data are more impressive than in the flare. We have also examined the flare discussed by Polito et al. ( 2016 ). The spectrum for exposure 5 and raster 15 in Figure 7 of Polito et al. ( 2016 ) shows dynamical Si iv activity at apparent footpoints of a loop or loops emitting in Fe xxi . One footpoint region has a strong continuum, and visual inspection of the Si iv spectrum reveals just a small downflow extension to the stationary component. The other footpoint shows a fairly symmetric and highly broadened Si iv line. Thus, the nature of explosive events appears to be highly variable from event to event. The events we have discussed also include visual inspection of the C ii and Mg ii lines observed by IRIS , and these lines show strong dynamical effects. So the events seen at Si iv and O iv temperatures also extend to lower temperatures. 4. DISCUSSION AND CONCLUSIONS The IRIS spectra indicate that explosive events in active regions contain plasma at densities near 10 12 cm −3 flowing outwards at speeds on the order of 100 km s −1 . The early Skylab observations butress the high density explanation. The behavior of density with upflow speed in Figure 9 and Figure 13 can be qualitatively explained by an evaporation scenario. In this scenario the evaporation initially occurs in a high density region near 10 12 cm −3 and flows upwards into an expanding flux tube which causes the density to decrease. The speed decreases as the plasma reaches the top of the loop or loop segment. However, the amount of plasma at the loop top builds up in volume, which results in a higher intensity than at the site of evaporation. Therefore, the intensity in the line profile increases toward zero upflow speed. The mystery problem is the high electron densities. This was encountered by Peter et al. ( 2014 ) in explosive events that appear like Ellerman bombs. Peter et al. ( 2014 ) simply found that the O iv line was so weak relative to the Si iv line that a very high density was implied. So he put the event in the photosphere, which was challenged by Judge ( 2015 ) for many reasons. Judge ( 2015 ) correctly pointed out that the O/Si ratio is not an ideal density diagnostic because of its temperature dependence. However, this issue has been addressed extensively above with the Skylab data, and these data seem to make clear that very small O/Si ratios are due to high electron densities, and perhaps not an FIP effect (e.g., Laming 2015 ) or non-ionization equilibrium effect (e.g., Olluri et al. 2013 ; Dudík et al. 2014 ; Martínez-Sykora et al. 2016 ). However, if a non-ionization equilibrium calculation were applied to all the ions
Paper: 2018ApJ...855..136R (acknowledgments)
This project was enabled by significant assistance from a wide variety of sources. Gautam Upadhya, Aviv R. Cukierman, Merle Reinhardt, George Chapman, William Januszewski, and Ken Sembach provided help with the HST observations. We thank Ryan Foley and Yen-Chen Pan for obtaining spectra of two reference stars with SOAR and Peter Challis for taking a few spectra of stars that were not ultimately used here. We thank Ed Nelan, Matt Lallo, Fritz Benedict, and Barbara McArthur for productive discussions about the behavior of the FGS. We also thank Leo Girardi, Alessandro Bressan, and Paola Marigo for the use of and assistance with their Padova isochrone database, Anne Robin for assistance with the Besancon Galaxy Model, Eddie Schlafly and D. Marshall for input on the extinction along the line of sight to these stars, and Nolan Walborn for useful discussions on the classification of hot stars. We thank Richard Anderson for useful discussions. We thank Scott Engle for observations relating to Cepheid period observations and Richard Gray for help with MK classification. We thank Kris Stanek for additional observations from the ASAS. Support for this work was provided by the National Aeronautics and Space Administration (NASA) through programs GO-12879, 13334, 13335, 13344, 13571, 13678, 13686, 13928, 13929, 14062, 14394, 14648, and 14868 from the Space Telescope Science Institute (STScI), which is operated by AURA, Inc., under NASA contract NAS 5-26555. A.V.F.’s group at UC Berkeley is also grateful for financial assistance from NSF grant AST-1211916, the TABASGO Foundation, the Christopher R. Redlich Fund, and the Miller Institute for Basic Research in Science (UC Berkeley). S.C. and A.G.R. gratefully acknowledge support by the Munich Institute for Astro- and Particle Physics (MIAPP) of the DFG cluster of excellence “Origin and Structure of the Universe.” Research at Lick Observatory is partially supported by a generous gift from Google. This research is based primarily on observations with the NASA/ESA Hubble Space Telescope , obtained at STScI, which is operated by AURA, Inc., under NASA contract NAS 5-26555. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA; the Observatory was made possible by the generous financial support of the W. M. Keck Foundation. This publication makes use of data products from the Wide-field Infrared Survey Explorer ( WISE ), which is a joint project of the University of California (Los Angeles) and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. It has also made use of the SIMBAD database, operated at CDS, Strasbourg, France.
Paper: 2015A&A...575A..13F (acknowledgments)
We would like to thank the members of the Fermi LAT Collaboration – David Thompson, Denis Bastieri, Jeremy Perkins, and Filippo D’Ammando – for a critical review of the manuscript. Part of the Swift observations have been supported by the contract ASI-INAF I/004/11/0. The Metsähovi team acknowledges the support from the Academy of Finland to our observing projects (numbers 212656, 210338, 121148, and others) Y.Y.K. and M.M.L. are partly supported by the Russian Foundation for Basic Research (project 13-02-12103). Y.Y.K. is also supported by the Dynasty Foundation. B.M.P. is supported by the NSF through grant AST-1008882. This research has made use of data from the MOJAVE database that is maintained by the MOJAVE team (Lister et al. 2009 ; 2013 ). The MOJAVE program is supported under NASA Fermi grant NNX12AO87G. J.L.R. acknowledges support from NASA through Fermi Guest Investigator grant NNX13AO79G. This research has made use of data and/or software provided by the High Energy Astrophysics Science Archive Research Center (HEASARC), which is a service of the Astrophysics Science Division at NASA/GSFC and the High Energy Astrophysics Division of the Smithsonian Astrophysical Observatory. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This research has made use of the XRT Data Analysis Software (XRTDAS) developed under the responsibility of the ASI Science Data Center (ASDC), Italy. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the US Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University.
Paper: 2018MNRAS.473.1719L (acknowledgments)
Acknowledgements The author wishes to thank Phuc H. Nguyen for his assiduous and comprehensive assistance in carrying out the calculations, and for providing beneficial feedback regarding this work. The helpful and encouraging comments provided by Abraham Loeb, Ed Turner, Steinn Sigurdsson and Lakshminarayanan Mahadevan are acknowledged. The author is also grateful to the referee for an insightful and detailed review of the paper. This work benefited from the support provided by the University of Texas at Austin, Princeton University and Harvard University.
Paper: 2019ApJ...884..159B (fulltext)
dust and PAH flux might be illumination of nearby cloud material by DoAr 21, rather than material associated with the system in a circumbinary disk distribution. Our results agree that heating of ambient local cloud material is a possible origin for the H 2 seen around DoAr 21. 4.4.4. GG Tau A GG Tau A is a subarcsecond triple system in the Taurus–Aurigae association (ensemble average distance of 140 pc; Table 7 ). It is composed of the M0 primary star GG Tau Aa and the nearly equal-mass Ab1+Ab2 binary (White et al. 1999 ; Di Folco et al. 2014 ). GG Tau A is famous for its spectacular and massive circumsystem ring of material that encompasses the three stars. A distribution of dust has been seen near the north of the stars in the scattered light maps of GG Tau A, revealing that material exists at locations that should be dynamically cleared in this complex multiple system (Krist et al. 2002 ; Duchêne et al. 2004 ). The GG Tau system also includes GG Tau Ba and Bb at a ∼10′′ projected separation to the south (White et al. 1999 ). Thus, GG Tau is a very young quintuple-star system. The GG Tau Bb component has a very late spectral type, making it a likely brown dwarf. The v = 1–0 S (1) line emission was measured in GG Tau A by Bary et al. ( 2003 ) with a flux of 6.9 × 10 −15 erg cm −2 s −1 . They interpreted the mission as arising from gas in the inner disks from one or more of the stars. Beck et al. ( 2012 ) presented the H 2 maps from Figure 4 of this study and showed that the extended H 2 emission is strongest from the northeastern region ∼40 au away from the stars. Since the time of that publication, improved maps of the dust and CO gas from ALMA have revealed that the region of brightest H 2 is colocated with the CO streamer connecting the outer circumsystem disk and the inner distribution of dust (Dutrey et al. 2016 ). This H 2 emission may be excited through stellar heating from the young stars, though the 1700 K LTE gas temperature measured from the H 2 line ratios is high for this distance from the stars. Beck et al. ( 2012 ) postulated that the streamers of gas in H 2 could be excited through shocks associated with infalling accreting material in this dynamically complex young triple. 4.4.5. GM Aur GM Aur is a spectral type K5 star at 158.9 pc distance in the Taurus–Aurigae association (Espaillat et al. 2011 ). It is a system in transition from the CTTS phase with a dense inner disk to the more evolved and X-ray-luminous WTTS phase. GM Aur has a ∼35 au cavity in the optically thick dust in the inner disk, though modeling of its SED and strong mass accretion suggest that gas and small particles persist within this cavity region. The hot inner H 2 disk gas was detected in the UV electronic transitions (France et al. 2012 ), with an emission profile showing an origin within the inner disk region. Our high-resolution spectrum presented in Figure 2 reveals the v = 1–0 S (1) H 2 line emission measured in GM Aur. This served as the basis
Paper: 2020ApJS..250....1T (fulltext)
The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.13. TXS 0506+056, bin = 7 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.14. TXS 0506+056, bin = 10 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation functions of the fits’ residuals; the dashed lines enclose the 95% confidence region. Figure 17.15. TXS 0506+056, bin = 14 days Results of the ARMA fitting. The blue line in the middle column is the PSD of the best-fit ARMA model, surrounded by a light blue 68% confidence band. The horizontal dashed line is the Poisson noise level inferred from the data. The vertical dashed line marks the break frequency, corresponding to T break,L from Table 6 , and the width of the gray rectangle symbolizes its standard error. The red line is the Fourier PSD, smoothed with a five-point moving average, to show the relation between the ARMA and Fourier features. The left column displays the ΔBIC scores of the ARMA( p , q ) fits. The right column contains the correlation and partial correlation
Paper: 2021MNRAS.500.2127L (fulltext)
(dark matter + baryonic gas, excluding stars). We show the following simulation projects: Technicolor Dawn (Finlator et al. 2018 ), GIMIC (Crain et al. 2009 ), EAGLE (Crain et al. 2015 ; Schaye et al. 2015 ), CROC (Gnedin 2014 ), CoDa (Ocvirk et al. 2016 ), Illustris (Vogelsberger et al. 2014 ), Renaissance (Barrow et al. 2017 ), the Katz et al. ( 2017 ) simulations, SPHINX (Rosdahl et al. 2018 ), and bluetides (Feng et al. 2016 ). We also show FLARES with the total resimulated high-resolution volume, as well as a vertical line showing the representative volume, given by that of the parent box. There is a strong negative correlation for periodic volumes between the volume that can be simulated and the resolution that can be achieved. The resimulation approach, with appropriate weighting, allows us to extend the volume axis significantly. In this paper, we introduce FLARES, zoom resimulations during the EoR using the eagle model. 2 The eagle project (Crain et al. 2009 ; Schaye et al. 2015 ) is a suite of smoothed particle hydrodynamics (SPH) simulations, calibrated to reproduce the stellar mass function and sizes of galaxies in the local Universe. EAGLE has been shown to be in good agreement with a large number of observables not used in the calibration (e.g. Lagos et al. 2015 ; Trayford et al. 2015 , 2017 ; Bahé et al. 2016 ; Crain et al. 2017 ; Furlong et al. 2017 ). This includes predictions at high redshift: Furlong et al. ( 2015 ) found reasonably good agreement with observationally inferred distribution functions of stellar mass and SFR out to z = 7. Unfortunately, there are very few galaxies in the fiducial EAGLE volume during the EoR. This is particularly the case for the most massive objects, which predominantly reside in protocluster environments, the progenitors of today’s collapsed clusters (Chiang et al. 2017 ; Lovell, Thomas Wilkins 2018 ). FLARES allows us to significantly increase the number of galaxies simulated during the EoR with EAGLE. It also allows us to test the already incredibly successful EAGLE model in a new regime of extreme, high- z environments, whilst still resolving hydrodynamic processes at resolution, and provide predictions for a number of key upcoming observatories. In this, the first FLARES paper, we introduce the resimulation method, our suite of zoom simulations, and present our first predictions for the distribution of galaxies by stellar mass and SFR using the composite approach. This is the first in a series of papers studying the galaxy properties in the FLARES sample; in Paper II we forward-model the full spectrophotometric properties, and predict the UV luminosity function and its high redshift evolution (Vijayan et al. 2020 ). In future papers, we plan to study the passive and starbursting galaxy population in FLARES, as well as the evolution of galaxy sizes and environmental bias. We assume a Planck year 1 cosmology (Ω 0 = 0.307, Ω Λ = 0.693, h = 0.6777, Planck Collaboration I 2014 ) and a