adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016A&A...587A..13L (acknowledgments)
We are grateful to Włodek Kluźniak for helpful comments. We thank Maciek Wielgus for his help with PDs and Fig. 6 . The anonymous referee’s report was very helpful. This research was supported by the Polish NCN grants UMO-2013/08/A/ST9/00795 and DEC-2012/04/A/ST9/00083. J.P.L. was supported in part by a grant from the French Space Agency CNES. R.S.S.V. was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), grants 2010/00487-9, 2013/01001-0 and 2015/10577-9. R.S.S.V. is grateful for the hospitality at Harvard-Smithsonian Center for Astrophysics and at Nicolaus Copernicus Astronomical Center. A.S. acknowledges support for this work by NASA through Einstein Postdoctoral Fellowship number PF4-150126 awarded by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for NASA under contract NAS8-03060. A.S. acknowledges computational support from NSF via XSEDE resources (grant TG-AST080026N), and from NASA via the High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.
Paper: 2019MNRAS.483L..93L (acknowledgments)
ACKNOWLEDGEMENTS We thank Vikram Ravi for useful discussions. We also thank the referee for comments which improved the clarity of the presentation. This research benefited from interactions at the ZTF Theory Network Meeting, funded by the Gordon and Betty Moore Foundation through Grant GBMF5076. WL was supported by the David and Ellen Lee Fellowship at Caltech.
Paper: 2017A&A...607A.116E (fulltext)
ULIRGs. They find the presence of molecular outflows with mass outflow rates of several 100 yr, which are similar or larger than the star formation rates in these systems. For the ULIRGs that we study in this paper, we derive outflow rates of molecular gas that are a factor of a few lower than the star formation rates (Sect. 4.1 ). Therefore, our H results appear at odds with the CO results from Cicone et al. (2014) . Of course, the H 2.12 m line only traces a small fraction of the total molecular gas mass, and its strength is subject to the local gas temperature and excitation (see, e.g., Rigopoulou et al. 2002 ). Complementary CO or mid-IR H observations of our sample sources are needed to further investigate the hot-to-cold molecular gas mass ratio. Some of the most spectacular molecular gas outflows in ULIRGs have been detected with the Herschel Space Observatory in the OH line (e.g., Sturm et al. 2011 ; Spoon et al. 2013 ; Veilleux et al. 2013 ; González-Alfonso et al. 2017 ). The outflow velocities that we observe in the H line with SINFONI are within the range of the OH outflows detected with Herschel. However, the mass outflow rates derived from OH measurements by Sturm et al. (2011) and González-Alfonso et al. (2017) are nearly ubiquitously 100 yr. Our SINFONI data suggest also here that either molecular outflow rates in nearby ULIRGs are much more moderate than predicted based on OH studies, or that our assumed hot-to-cold gas mass ratio for H outflows in ULIRGs is too large. Alternatively, the OH studies may trace faster outflows that originate closer to the galaxy core, with higher and smaller . González-Alfonso et al. (2017) indeed found evidence for higher maximum outflow velocities seen in OH compared to CO in several nearby ULIRGs. According to González-Alfonso et al. (2017) , this could suggest that OH and CO trace outflows in different regions of the galaxy. After all, they argue that as the outflowing gas expands and breaks up into clumps, it will “cover a decreasing fraction of the far-IR continuum”. Unlike the CO, the OH molecules are radiatively excited, and hence “produce lower absorption and emission” the further out the gas flows ( González-Alfonso et al. 2017 ). This scenario may also explain the fact that the molecular mass outflow rates that we derive from H appear on average lower than those based on OH studies. Our results suggest that consensus has yet to be reached on how effective molecular gas outflows are in influencing the star formation properties of nearby ULIRGs. We argue that detailed 3D-imaging of the different gas phases is a valuable tool to help determine the evolutionary role of multi-phase gas outflow in the evolution of these IR-luminous galaxies. 5. Conclusions We presented the detection and characterization of massive outflows of hot molecular gas in three out of four nearby ULIRGs. We imaged the molecular outflows at sub-kpc resolution with VLT-SINFONI, using the H 1–0 S(1) 2.12 m line. We
Paper: 2017ApJ...834...57M (acknowledgments)
We thank the anonymous referee for very constructive feedback and comments that helped to improve the paper significanty. We thank Rosine Lallement for providing us with the extinction map of the solar neighborhood. This work was supported by the program Physique et Chimie du Milieu Interstellaire (PCMI) funded by the Conseil National de la Recherche Scientifique (CNRS) and the Centre National d’Etudes Spatiales (CNES) of France. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. N.W.M. was supported in part by the Natural Sciences and Engineering Council of Canada.
Paper: 2017ApJ...837L..11C (fulltext)
be determined by scaling the weighted frequency. The quantities c S (), c A (), and c T () are the sound speed, Alfvén speed, and tube speed, respectively, and γ , k B , T 0 , μ , m H , B 0 , μ B , and ρ 0 are the specific heat ratio, Boltzmann’s constant, temperature, mean molecular weight, hydrogen atomic mass, magnetic field strength, magnetic permeability, and density, respectively. The subscript 0 indicates the equilibrium quantity. The () is the buoyancy frequency, where g = 0.274 km s −2 . The parameters Λ p () and Λ ρ () are the pressure and density scale heights, respectively. The prime indicates the derivative with respect to the vertical direction. As we assume the uniform vertical field in a non-isothermal stratified medium, and , giving . Hence the expression for the angular cutoff frequency is reduced towhere . Equation ( 2 ) describes umbral oscillations in the photosphere, accounting for the finite β effects. Equation ( 2 ) shows that f cutoff is directly related to Λ p and Λ ρ , which all can be determined from observations. In other words, and Λ ρ = γ Λ p . Thus, Equation ( 2 ) becomes a function of X . The sound speed c S is estimated from the plasma temperature. The temperature is obtained from the ratio of HMI continuum intensity to the quiet Sun’s, by applying the Planck function (Mathew et al. 2004 ). In other words, we solve the equation , where I , h , c , λ , k B , , and are the intensity ratio, Planck’s constant, speed of light, wavelength of Fe i line continuum (6172.1 Å), Boltzmann’s constant, the temperature at a given position, and the temperature of the quiet Sun (6000 K), respectively. Using μ = 1.3 and γ = 5/3, we obtain the sound speed as km s −1 . We look for a positive solution for X of Equation ( 2 ) by changing the scaling of in the range below 1.0. We found that positive solutions for all pixels inside the umbra exist when the scaling is in 0.5–0.55. Thus we take 0.55 as the upper limit of the scaling. The solution allows us to calculate the Alfvén speed, using the expressions ), the plasma- β , as , and the mass density as for each pixel of the umbra. The magnetic field strength B 0 is obtained as the de-projected HMI magnetogram, which may correspond to the magnetic field slightly above the height of continuum formation (Norton et al. 2006 ). Slightly different values of equilibrium quantities do not give us significantly different results. For example, when δT 0 = ±100 K, and are less than 50 m s −1 , and is less than 0.02 for the given sunspot. When we choose δλ = −2 Å, the absolute values of deviation of speeds and plasma- β are less than 0.1 m s −1 and 10 −4 , respectively. 3. Results We illustrate the application of the developed method to a sunspot located near the disk center, observed during 00:00–01:00 UT on 2014 August 28, in NOAA 12149. The center of a sunspot is tracked synodically, accounting for the effect of the solar differential rotation. We used the differential rotation law, in μ rad
Paper: 2019ApJ...877..101S (acknowledgments)
We are deeply grateful to Patrick Boehnke for his contributions to the CHILI measurements and for helpful discussions. The manuscript benefited significantly from very detailed and constructive comments by an anonymous reviewer. We also acknowledge Roberto Gallino for his adept remarks. We thank Elmar Gröner for technical support on the NanoSIMS. This work was supported by NASA (grants NNX15AF78G, 80NSSC17K0250, and 80NSSC17K0251 to A.M.D.). LLNL-JRNL-768104.
Paper: 2019ApJ...870...85M (acknowledgments)
Support for this work was provided by NASA through Chandra Award Numbers GO6-17112A and GO6-17112B issued by the Chandra X-ray Observatory Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of the National Aeronautics Space Administration under contract NAS8-03060. Additional support was provided by NASA through grants from the Space Telescope Science Institute (HST-GO-13578, HST-GO-14352), which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. The South Pole Telescope is supported by the National Science Foundation through grant PLR-1248097. Partial support is also provided by the NSF Physics Frontier Center grant PHY-1125897 to the Kavli Institute of Cosmological Physics at the University of Chicago, the Kavli Foundation and the Gordon and Betty Moore Foundation grant GBMF 947. S.W.A. and A.B.M. acknowledge additional support from the U.S. Department of Energy under contract number DE-AC02-76SF00515. J.H.L. is supported by NSERC through the discovery grant and Canada Research Chair programs. W.F. acknowledges support from NASA contract NAS-08060 and the Smithsonian Institution. The Munich group acknowledges the support by the DFG Cluster of Excellence “Origin and Structure of the Universe”, the Ludwig-Maximilians-Universität (LMU-Munich), and the Transregio program TR33 “The Dark Universe.” T.S. acknowledges support from the German Federal Ministry of Economics and Technology (BMWi) provided through DLR under projects 50 OR 1210, 50 OR 1407, and 50 OR 1610. The Melbourne group acknowledges support from the Australian Research Council’s Discovery Projects funding scheme (DP150103208). B.B. is supported by the Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359 with the U.S. Department of Energy.
Paper: 2021ApJ...913...85H (fulltext)
polarized emission in the OMC-1 region was obtained as part of the BISTRO large program (project code M16BL004; Ward-Thompson et al. 2017 ) and the POL-2 commissioning project (project code M15BEC02, Friberg et al. 2016 , 2018 ; P. Bastien et al. 2021, in preparation). In the BISTRO program, the OMC-1 region was observed 21 times between 2016 January 11 and 24, in Band 1 or Band 2 weather conditions, τ 225 GHz 0.05 or 0.05 ≤ τ 225 GHz 0.08, where τ 225 GHz is the atmospheric opacity at 225 GHz. The total on-source time is 14 hr. These data were first published by Ward-Thompson et al. ( 2017 ). We excluded one of these data sets because the observation was incomplete. A further set of 15 observations of the OMC-1 region was made between 2017 December 8 and 2018 January 10, as part of the POL-2 450 μ m commissioning campaign. As part of the effort to characterize the instrumental polarization at 450 μ m, these observations were made without the JCMT Gore Tex in place. Most of these observations were obtained in Band 1 weather condition ( τ 225 GHz 0.05) with a total on-source time of 7.9 hr. We publish these observations of the commissioning campaign and the polarization data of the two projects at 450 μ m for the first time. A total of 35 data sets at 450 and 850 μ m from these two projects were used in this paper. We combined all 35 data sets of the OMC-1 region and reduced them using the pol2map routine in the Sub-Millimetre User Reduction Facility (SMURF) package of the Starlink software (Jenness et al. 2013 ) with the latest Instrumental Polarization (IP) model, “2019 August.” 41 41 https://www.eaobservatory.org/jcmt/2019/08/new-ip-models-for-pol2-data/ There are three main stages of the POL-2 data reduction process. Polarized light is represented by the Stokes parameters, I , Q , and U . First, the raw time-series data are converted into Stokes I , Q , and U time streams using the calcqu command. Then, the makemap routine is used to make an initial reference Stokes I map from each data set, gridded onto 4′′ pixels. A coadded total intensity map is created from all of these initial Stokes I maps. Next, pol2map generates two “masks,” named ASTMASK and PCAMASK, from the coadded total intensity map. The ASTMASK is a fixed signal-to-noise-based mask, which is used to define regions of astrophysical emission in the coadded total intensity map. The PCAMASK defines source regions in order to exclude the regions containing emission when making a background model with makemap . See Mairs et al. ( 2015 ) for a detailed discussion of the role of masking in SCUBA-2 data reduction. pol2map makes an improved Stokes I map of each data set by using these fixed masks, increasing the number of principal component analysis (PCA) components over the first reduction, and using the skyloop implementation of makemap , wherein each iteration of the mapmaker is performed on each of the observations in turn, rather than each observation being reduced consecutively.
Paper: 2019ApJ...887..175T (acknowledgments)
We thank Huib T. Intema for help with the TGSS ADR1 catalog masks and survey details. Prabhakar Tiwari acknowledges the support by the PIFI (Project No. 2019PM0007) program of the Chinese Academy of Sciences and the NSFC grants 11720101004 and 11673025, and the National Key Basic Research and Development Program of China (No. 2018YFA0404503). The work of Pankaj Jain is supported by a grant from the Science and Engineering Research Board (SERB), Government of India.
Paper: 2017MNRAS.469..339S (acknowledgments)
Acknowledgments Georgia Southern University provided start-up funds in support of this work. Additionally, Prof. T. Daniel Crawford of Virginia Tech provided some computer hardware necessary to complete some of this work. The authors are grateful for the support from both.
Paper: 2018MNRAS.473.2124G (acknowledgments)
Acknowledgements We would like to thank Andrew Cunningham, Patrick Hennebelle, Shu-Ichiro Inutsuka, Ralf Klessen, Pak Shing Li, Zhi-Yun Li, and Andrew Myers for helpful discussions. We particularly thank Kengo Tomida for pointing out that the angular momentum lost in the growth of sink particles could significantly affect disc formation in numerical simulations and for providing valuable references. Helpful comments by the referee are gratefully acknowledged. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 (WJG and RIK). Support for this work was provided by NASA through Astrophysics Theory Program (ATP) grant NNX-13AB84G (RIK and CFM) and Theoretical and Computational Astrophysics Network (TCAN) grant NNX-14AB52G (CFM and RIK) and the NSF through grant AST-1211729 (CFM and RIK). Supercomputing support was provided by NASA, through a grant from the ATP, from Lawrence Livermore National Laboratory, and from NERSC. The figures and analysis presented here were created using the yt analysis package (Turk et al. 2011 ).
Paper: 2016MNRAS.462.4435T (acknowledgments)
This study is based on observations obtained in Rozhen Observatory, European Southern Observatory program 074.D-0114 and Asiago Observatory. We acknowledge with thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research. This research has made use of the NASA's Astrophysics Data System, and the SIMBAD astronomical data base, operated by CDS at Strasbourg, France. Some of the data presented in this paper were obtained from the Mikulski Archive for Space Telescopes (MAST). STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. Support for MAST for non- HST data is provided by the NASA Office of Space Science via grant NNX09AF08G and by other grants and contracts. We are thankful to U. Munari who made available the Asiago spectra of AG Peg obtained in 2002. We are grateful to the anonymous referee for valuable comments and suggestions. TVT is very grateful to Svet Zhekov for the many useful discussions and Sz. Zywica for some help with English.
Paper: 2016ApJ...823..120N (acknowledgments)
We acknowledge the support by the INFN project TAsP (Theoretical Astroparticle Physics Project). M.G. would like to thank the Max Planck Institute for Astronomy (Heidelberg), where part of this work wsa performed, and Luigi Mancini for hospitality. We also thank the anonymous referee for the constructive comments.
Paper: 2015MNRAS.450L..61H (acknowledgments)
We would like to thank Farhan Feroz for numerous helpful discussions during the inception of the polychord algorithm.
Paper: 2017MNRAS.468.4675D (acknowledgments)
Acknowledgments TAD acknowledges support from a Science and Technology Facilities Council Ernest Rutherford Fellowship, and thanks F. van de Voort for useful discussions and comments on early versions of this manuscript. MB was supported by the consolidated grants Astrophysics at Oxford ST/H002456/1 and ST/K00106X/1 from the UK Research Council. MC acknowledges support from a Royal Society University Research Fellowship. This paper makes use of the following ALMA data: ADS/JAO.ALMA#2015.1.00598.S. 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. This paper also makes use of observations made with the NASA/ESA Hubble Space Telescope , and obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESA) and the Canadian Astronomy Data Centre (CADC/NRC/CSA). 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.
Paper: 2016MNRAS.457..320S (fulltext)
galaxies which already had a dynamical detection of their black hole mass. We modelled their one-dimensional surface brightness profiles with a combination of analytic functions, using one function per galaxy component. Spheroid luminosities were converted into stellar masses using individual, but almost constant mass-to-light ratios (∼0.6; Meidt et al. 2014 ). Figure 5. Black hole mass plotted against spheroid stellar mass for 45 + 3 early-type galaxies (from Savorgnan et al. 2015 ). The black solid line is the bisector linear regression for all galaxies except Mrk 1216, NGC 1271, and NGC 1277. The dashed lines mark the 1σ and 3σ deviations, where σ (0.51 dex) is the total rms scatter about the correlation in the black hole mass direction. The red symbols mark five galaxies that were claimed to be extreme outliers in this diagram: four intermediate-scale disc galaxies (Mrk 1216, NGC 1271, NGC 1277, and NGC 1332) and one elliptical galaxy (NGC 4291). All five reside well within a 3σ deviation from the correlation when using their correct spheroid mass. For NGC 1277, we show the previously reported spheroid stellar mass (van den Bosch et al. 2012 ) in grey. The green colour is used to show the location of four additional intermediate-scale disc galaxies mentioned in Section 2 . In Fig. 5 , we show the galaxies Mrk 1216, NGC 1271, and NGC 1277, which were not a part of the original sample of 45 early-type galaxies. For the galaxy NGC 1271, we use the black hole mass measurement and the stellar mass-to-light ratio obtained by Walsh et al. ( 2015b ). For the galaxy NGC 1277, we use the black hole mass measurement obtained by Walsh et al. ( 2015a ) and the stellar mass-to-light ratio obtained by Martín-Navarro et al. ( 2015 ). Note that for NGC 1277, we recover a spheroid stellar mass of 2.7 × 10 11 M ⊙ , in agreement with the value of ≈ 1-2 × 10 11 M ⊙ obtained by Emsellem ( 2013 ) from his multi-Gaussian expansion models. 5 For the galaxy Mrk 1216, we use the upper limit on the black hole mass and the stellar mass-to-light ratio obtained by Yldrm et al. ( 2015 ). For the first time, Fig. 5 reveals that when the four intermediate-scale disc galaxies Mrk 1216, NGC 1271, NGC 1277, NGC 1332, and the elliptical galaxy NGC 4291 are properly modelled, they no longer appear as extreme outliers above the (black hole mass)–(spheroid stellar mass) correlation for early-type galaxies, i.e. they all reside well within a 3σ deviation from the correlation. 4 ORIGIN OF COMPACT MASSIVE GALAXIES Acknowledging the correct structure of galaxies with intermediate-scale discs is important to properly understand their origin. According to the current paradigm of cosmological structure evolution, the genesis of massive early-type galaxies is characterized by two distinct phases: ‘ in situ ’ and ‘ ex situ ’. The first phase takes place in a young Universe (within its first 4 Gyr), when cold gas inflows produced short and intense bursts of star formation that created