adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.483.1737K (fulltext)
al. ( 2014 ) also suspected the existence of tidal tails for NGC 3201, as they found some unbound stars located a few arc minutes outside of the cluster radius. Recently, Anguiano et al. ( 2016 ) reported the presence of tidal debris for the cluster. Their results were based on spectroscopic measurements from RAVE data. NGC 5024 has five extra-tidal RR Lyrae stars mostly concentrated in a region which is at a distance of three times the tidal radius from the centre of the cluster. The presence of these extra-tidal RR Lyrae stars may be an indication of more extra-tidal population which may also belong to the cluster. Beccari et al. ( 2008 ) found that in the case of NGC 5024, the model with lower concentration ( c = 1.45) and large core radius ( r c = 26 arcsec) best reproduced the observed surface density profile in the inner portion of the cluster but this model deviates from observations in the outer region of the cluster. This type of deviation is a signature of the stars that are tidally stripping away from the cluster (Combes et al. 1999 ; Johnston, Sigurdsson Hernquist 1999 ; Leon et al. 2000 ). Kunder et al. ( 2018 ) reported eight extra-tidal RR Lyrae stars belonging to the Galactic globular cluster NGC 6441 but we did not find any in this study. This is due to three reasons: (1) some of the stars reported by them were not observed in Gaia DR2 (OGLE BLG-RRLYR-3774, OGLE BLG-RRLYR-30603, OGLE BLG-RRLYR-30792, OGLE BLG-RRLYR-3168, OGLE BLG-RRLYR-31080); (2) star reported was not marked as variable by Gaia survey [OGLE BLG-RRLYR-30513 ( Gaia DR2 4039957151898674048)] and (3) stars were reported as RRab variable stars by Gaia survey but were not present in Gaia DR2 RR Lyrae catalogue [catalogue: gaiadr2.vari_rrlyrae; stars: OGLE BLG-RRLYR-3613 ( Gaia DR2 4039958564974057984)], [OGLE BLG-RRLYR-30928 ( Gaia DR2 4039978695412672768)]. Minniti et al. ( 2018 ) recently reported the presence of tidal tails in the cluster NGC 6266. These were not found in our analysis due to the fact that they used additional near-IR VVVX survey observations along with Gaia DR2 data. 5 CONCLUSIONS We searched for extra-tidal RR Lyrae stars in 56 Galactic globular clusters based on the available literature data. Gaia DR2 data for RR Lyrae stars from the catalogue of Clementini et al. ( 2018 ) were used along with data from MPV14 and V18 to assign cluster membership to each RR Lyrae star. The extra-tidal RR Lyrae stars were selected based on three criteria: position of the cluster and the star in the sky; proper motion of the cluster and the star; and position of the RR Lyrae star on the CMD of the cluster. All the three criteria are necessary and none of them can be neglected while selecting the extra-tidal RR Lyrae stars. Based on these three criteria we found 30 extra-tidal RR Lyrae stars belonging to 11 globular clusters. The majority of these clusters have only a couple of candidates. We also note that some of those extra stars for halo GCs may also be part
Paper: 2019ApJ...871...23K (acknowledgments)
G.S.K. was funded by an appointment to the NASA Postdoctoral Program at Goddard Space Flight Center, administered by USRA through a contract with NASA. M.C. acknowledges support from the Research Council of Norway through its Centres of Excellence scheme, project no. 262622, and through grants of computing time from the Programme for Supercomputing. J.C.A. and A.N.D. acknowledge support from the IRIS mission. IRIS is a NASA small explorer mission developed and operated by LMSAL with mission operations executed at NASA Ames Research Center and major contributions to downlink communications funded by ESA and the Norwegian Space Centre. P.R.Y. acknowledges support from NASA grant NNX15AF25G. We appreciate the open data policies of the Opacity Project and the NIST and CHIANTI atomic database. The authors thank ISSI and ISSI-BJ for the support to the teams “Diagnosing Heating Mechanisms in Solar Flares through Spectroscopic Observations of Flare Ribbons” and “New Diagnostics of Particle Acceleration in Solar Coronal Nanoflares from Chromospheric Observations and Modeling.” Finally, we would like to thank the anonymous referee, whose comments helped to improve this work.
Paper: 2019ApJ...880...25B (acknowledgments)
The feedback on our analysis from an anonymous expert referee significantly improved our manuscript. This work is based on observations taken by the CANDELS Multi-Cycle Treasury Program, the 3D- HST Treasury Program (GO 12177 and 12328), and the z9-CANDELS program (GO 13792) with the NASA/ESA HST , which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. This work also relies on observations made with the Spitzer Space Telescope , which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. Support for this work was provided by NASA through an award issued by JPL/Caltech. This work relies on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under ESO program ID 179.A-2005 and on data products produced by TERAPIX and the Cambridge Astronomy Survey Unit on behalf of the UltraVISTA consortium. Some of the data utilized in this paper were gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile. This paper is also based (in part) on data collected at the Subaru Telescope and retrieved from the HSC data archive system, which is operated by the Subaru Telescope and Astronomy Data Center at the National Astronomical Observatory of Japan. 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 the National Aeronautics and Space Administration. 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 Maunakea has always had within the indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. We acknowledge the support of NASA grants HST -AR-13252, HST -GO-13872, and HST -GO-13792, NWO grant 600.065.140.11N211 (vrij competitie), and TOP grant TOP1.16.057. Facilities: HST (ACS , WFC3) , Spitzer (IRAC) , CFHT , VISTA , Magellan (FourStar) , Subaru (HSC) , Keck:I (MOSFIRE/U142).
Paper: 2020ApJ...891..168W (fulltext)
; Chen et al. 2016 ; Wu et al. 2017b ). For simulations described in the current work, we apply an HRO formulation whereis the magnitude of the angle between N H isocontours (orthogonal to ∇ N H ) and , the simulated polarization pseudovectors. Here, is defined aswhere p = 0.1 is a set constant polarization fraction and χ is the angle in the plane-of-sky derived from the Stokes parameters (see, e.g., Wu et al. 2017b ): The relative orientation angle Φ is then calculated pixel-by-pixel in a column density map. The lowest column density pixels () are ignored, and a gradient threshold for is applied (similar to, e.g., Planck Collaboration et al. 2016 ), to better separate GMC material from diffuse background fields. The remaining pixels are then separated into 25 bins of equal count based on N H . Note that we assume n He = 0.1 n H , yielding a mass of per H. Figure 2 shows column density maps for the noncolliding and colliding models with B = 10, 30, 50 μ G for the density-regulated model. Their respective HROs are also shown for low, medium, and high column density bins. Here, φ represents the smaller angle between the polarization-inferred magnetic field and N H isocontours. Thus, histograms peaking at φ = 0° indicate inferred B -fields preferentially aligned parallel to filamentary structures, while peaks at φ = 90° indicate a preferentially perpendicular alignment. Figure 2. First and third rows: column density maps with the normalized plane-of-sky magnetic polarization field, p , represented with black pseudovectors. The noncolliding cases for B = 10, 30, and 50 μ G are shown in the first row, while the respective colliding cases are shown in the third row. Gas from the density-regulated SF models is shown in each case at t = 5 Myr. Second and fourth rows: histograms of relative orientations are shown directly below their corresponding column-density maps. HROs compare the angle between p and iso- N H contours pixel-by-pixel. The projected map is divided into 25 column-density bins of equal pixel count. HROs for the lowest (1st bin; black), middle (12th bin; blue), and highest (25th bin; red) N H are shown, using angle bins of 15°. The histogram color corresponds to the regions bounded by low (black), intermediate (blue), and high (red) value iso- N H contours as shown in the respective projection map. The thickness of the data points indicates the variance within each bin. Histograms with peaks at 0° correspond to p predominantly aligned with iso- N H contours (i.e., B -fields parallel to filaments), while peaks at 90° correspond to p predominantly perpendicular to iso- N H contours (i.e., B -fields perpendicular to filaments). Gas in the noncolliding, model is slightly preferentially aligned parallel to filaments at high, medium, and low column densities. At , the low- N H gas retains effectively the same orientation behavior, while the mid- and high- N H bins show an increasing trend toward perpendicular alignment. This trend increases
Paper: 2019A&A...623A..88B (acknowledgments)
Acknowledgements B.B. thanks the European Research Council (ERC Starting Grant 757448-PAMDORA) for their financial support. A.J. was supported by the European Research Council under ERC Consolidator Grant agreement 724687-PLANETESYS, the Swedish Research Council (grant 2014-5775), and the Knut and Alice Wallenberg Foundation (grants 2012.0150, 2014.0017, and 2014.0048). S.N.R. and A.M. thank the Agence Nationale pour la Recherche for support via grant ANR-13-BS05-0003-002 (grant MOJO). A. I. thank FAPESP for support via grants 16/19556-7 and 16/12686-2. We thank the referee John Chambers for his report and comments that helped to improve this article.
Paper: 2015ApJ...815...93G (acknowledgments)
We thank the anonymous referee for the careful and constructive comments that greatly improved this paper. This paper is based on observations made with the NASA/ESA Hubble Space Telescope , obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, under NASA Contract NAS 5-26555. These observations are associated with Program 13364 (LEGUS). Support for Program 13364 was provided by NASA through a grant from the Space Telescope Science Institute. This research has made use of the NASA/IPAC Extragalactic Database (NED) operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA. D.A.G. acknowledges financial support by the German Research Foundation (DFG) through grant GO 1659/3-2. M.F. acknowledges support by the Science and Technology Facilities Council (grant number ST/L00075X/1).
Paper: 2019MNRAS.490...96S (fulltext)
clear difference for the Dark Sage galaxies in Fig. C1 versus Fig. 10 is the upturn in the typical values of centrals at . This is not a sign that the analytic model breaks down; rather, what we are seeing here is a tendency for low- galaxies to have both low and low Σ 0 . This could potentially just be a reflection of the fact that this mass scale is at the simulation’s resolution limit; the median H i mass of Dark Sage galaxies occupying Millennium haloes of 100 particles is . Our Dark Sage galaxy sample with is therefore almost certainly not halo-mass complete. Current results from these galaxies should thus be taken with a grain of salt, but they should mature as Dark Sage is transitioned to higher-resolution simulations. TNG100 does not share the same feature. That is, satellites and centrals follow the same power-law-like relation for the full H i mass range (similar to the top panel of Fig. 11 ). Figure C1. Similar to Figs 10 and 11 (for the right- and left-hand panels, respectively) but now the classical H i radius has been replaced with the H i half-mass radius. For simplicity, we only show the GD14 prescription for the H i /H 2 breakdown for TNG100 (the other prescriptions give effectively the same results). Measurements of individual galaxies from our observed sample are overlaid in the top panels. Thin, dot–dashed lines in the top panel give the best-fitting linear relation to the simulated galaxies, assuming a slope of 0.5. Systematic differences seen between the simulations and observations are consistent with the standard H i size–mass relation results. For Dark Sage , satellites in low-mass haloes behave the same as centrals in their upturn in at low (cf. the top and bottom panels of Fig. C1 ). But for most satellites, i.e. those in haloes of , there is no strong upturn. To explain this, we need to understand how disc truncation would affect the – relation. As pointed out in Section 4.1 , a truncated model-1 or -2 profile with is indistinguishable from a non-truncated profile with . The higher the halo mass, the more truncated the satellite’s H i is, therefore the larger the typical fitted is, meaning the more common it is for , where . Also, because many of these satellites will have had more H i before infall, they are less likely to be biased towards low Σ 0 like Dark Sage centrals of the same current mass; in principle, unlike , truncation should not affect the best-fitting Σ 0 to [or, in this case, ]. Both effects mean satellites at low should typically have lower than centrals. The effect of halo mass on is otherwise the opposite to how it was for . That is, at fixed , satellites in higher halo masses have slightly higher on average. This can again be explained in terms of Σ 0 . Dark Sage satellites in higher-mass haloes tend to have slightly lower Σ 0 ; the medians for those in haloes of and are 10 and , respectively. While there is still a tendency for lower Σ 0 to also mean higher , the specific value of is less
Paper: 2019ApJ...871..211P (acknowledgments)
We thank the anonymous referees for useful suggestions on the manuscript. We are grateful to NuSTAR and Swift PIs for approving the ToO observations and to the mission operation teams for quickly executing them. We also thank P. Smith (Steward observatory) for considering our request of observations. V.S.P. acknowledges funding under NASA contracts 80NSSC17K0310 and 80NSSC18K0580. R.A. is a member of the International Max Planck Research School (IMPRS) for Astronomy and Astrophysics at the Universities of Bonn and Cologne. The Fermi LAT Collaboration acknowledges generous ongoing support from a number of agencies and institutes that have supported both the development and the operation of the LAT, as well as scientific data analysis. These include NASA and the Department of Energy in the United States; the Commissariat à l’Energie Atomique and the Centre National de la Recherche Scientifique/Institut National de Physique Nucléaire et de Physique des Particules in France; the Agenzia Spaziale Italiana and the Istituto Nazionale di Fisica Nucleare in Italy; the Ministry of Education, Culture, Sports, Science and Technology (MEXT), High Energy Accelerator Research Organization (KEK) and Japan Aerospace Exploration Agency (JAXA) in Japan; and the K. A. Wallenberg Foundation, the Swedish Research Council and the Swedish National Space Board in Sweden. Additional support for science analysis during the operations phase is gratefully acknowledged from the Istituto Nazionale di Astrofisica in Italy and the Centre National d’Études Spatiales in France. This work performed in part under DOE Contract DE- AC02-76SF00515. This work made use of data from the NuSTAR mission, a project led by the California Institute of Technology, managed by the Jet Propulsion Laboratory, and funded by the National Aeronautics and Space Administration. We thank the NuSTAR Operations, Software, and Calibration teams for support with the execution and analysis of these observations. This research has made use of the NuSTAR Data Analysis Software (NuSTARDAS) jointly developed by the ASI Science Data Center (ASDC, Italy) and the California Institute of Technology (USA). This research has made use of the XRT Data Analysis Software (XRTDAS). This work made use of data supplied by the UK Swift Science Data Centre at the University of Leicester. This research has made use of data obtained through the High Energy Astrophysics Science Archive Research Center Online Service, provided by the NASA/Goddard Space Flight Center. 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. Part of this work is based on archival data, software or online services provided by the ASI Data Center (ASDC). Data from the Steward Observatory spectropolarimetric monitoring project were used. This program is supported by Fermi Guest Investigator grants NNX08AW56G, NNX09AU10G, NNX12AO93G, and NNX15AU81G.
Paper: 2015MNRAS.447.2961S (acknowledgments)
We thank Boris Leistedt, Hiranya Peiris, Nishant Agarwal, Eduardo Rozo, Shirley Ho, Ashley Ross, and the anonymous referee for useful comments and discussions. We are supported by DOE Grant no. DE-FG02-95ER40899 and NSF Grant no. AST-080764. DH thanks the Aspen Center for Physics, supported by NSF Grant no. 106693, for hospitality.
Paper: 2017ApJ...850...94W (acknowledgments)
We thank the anonymous referee for helpful comments. M.L.W. and A.I.Z. acknowledge support from NSF grant AST-1211874. M.L.W. also thanks the Technology and Research Initiative Fund (TRIF) Imaging Fellowship program for its support. C.R.K. acknowledges support from NSF grant AST-1211385. K.C.W. is supported by an EACOA Fellowship awarded by the East Asia Core Observatories Association, which consists of the Academia Sinica Institute of Astronomy and Astrophysics, the National Astronomical Observatory of Japan, the National Astronomical Observatories of the Chinese Academy of Sciences, and the Korea Astronomy and Space Science Institute. Facilities: Mayall (Mosaic-I) , Blanco (Mosaic-II) , Magellan-1 (LDSS-2 , LDSS-3) , Magellan-2 (IMACS) , MMT (Hectospec) .
Paper: 2015ApJ...807..107H (acknowledgments)
This work was supported by NASA under Astrophysics Theory Program grants NNX11AI96G and NNX14AK44G. The authors would like to thank the anonymous referee for very useful comments that have improved the paper.
Paper: 2017A&A...606A.128R (acknowledgments)
This work is supported in part by the French Agence Nationale de la Recherche under Grant ANR-12-BS05-0002. D.F.M. thanks the support of the Research Council of Norway.
Paper: 2016A&A...587A.111A (acknowledgments)
This work was partially supported by the Spanish Ministerio de Economía y Competitividad through project AYA2013-43188-P. The author also thanks R. Smith, S. Courtea, S. Zarattini, and T. Lisker for useful discussions during the preparation of this manuscript. The author would like to thank the anonymous referee for the constructive revision of the manuscript.
Paper: 2019A&A...628A..10B (acknowledgments)
Acknowledgements We thank the referee, Anthony Remijan, for his critical review of our article that helped to clarify several aspects of our analysis. This paper makes use of the following ALMA data: ADS/JAO. ALMA#2016.1.00074.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. The interferometric data are available in the ALMA archive at https://almascience.eso.org/aq/ . Part of this work has been carried out within the Collaborative Research Centre 956, sub-project B3, funded by the Deutsche Forschungsgemeinschaft (DFG) – project ID 184018867.
Paper: 2019MNRAS.488..495W (fulltext)
an arc and IRS 3 a jet. IRS 3 also exhibits 3–6 cm emission which indicates shock ionization due to the interaction between the jet from IRS 3 and the surrounding gas (Young et al. 2009 ). Finally, in the outflow source L1251A, a collimated molecular outflow was detected with CO J = 2 − 1 line observation by Lee et al. ( 2010 ). The dynamical timescale of this outflow is 5.2 × 10 4 yr assuming an inclination angle of 70° (Lee et al. 2010 ). Spitzer IRAC observations revealed four infrared sources IRS 1–IRS 4. The driving source is IRS 3, a Class 0 object. From this object, a collimated long infrared jet originated. Our observed position is 12 arcsec east and 9 arcsec south to IRS 3 (see Fig. A1 ). The detected strong Spitzer IRAC observations revealed a jet with a bipolar structure extending from north to south though IRS 3. The jet may originate from a paraboloidal shock (Lee et al. 2010 ). About the N-bearing species in these outflows, the average values of x(HC 3 N)/x(HC 5 N) and x(HC 5 N)/x(HC 7 N) are 6.8 and 4.6 respectively, which are both larger than those of the Lup I starless cores and the WCCC source Lup I-1, showing that the abundance of N-bearing species decreases faster with carbon length in these outflows than in starless cores and WCCC sources. The ratio of x(HC 3 N)/x(HC 5 N) is somewhat lower than the median value (8.7) of 16 low-mass protostars detected by Law et al. ( 2018 ). Table 7 shows that in the starless cores, x(C 3 S) is two or more times lower than x(HC 7 N). The x(C 3 S) in the WCCC source Lup I-1 is also three times less than x(HC 7 N). While in the other three outflow sources the x(C 3 S) are 2–5 times of the x(HC 7 N). These results demonstrate that the x(C 3 S)/x(HC 7 N) values for the three outflows are larger than those of starless cores and the WCCC source almost one order of magnitude higher than their average value. 4.3.2 Chemical mechanism of Group JS sources The abnormal high abundance of C 3 S compared with those of nitrogen-bearing CCMs in JS sources has not been seen before. Previous studies revealed that the column densities of C 2 S have good positive correlation with those of HC 3 N and HC 5 N in quiescent dark cores (Suzuki et al. 1992 ). The column densities of C 3 S are 3–5 times lower than those of C 2 S (Suzuki et al. 1992 ; Fuente et al. 1990 ). High C 2 S and C 3 S abundances were found towards Taurus dark clouds, and there is still a good correlation between column densities of C 2 S and HC 5 N. In star formation regions, S-bearing CCMs were at best only marginally detected (Suzuki et al. 1992 ), indicating that the results of our three outflow sources are unusual. WCCC theory was a possible explanation for the large hydrocarbon abundances such as C 4 H and C 6 H present in L1251A (Cordiner et al. 2011 ). However, WCCC cannot explain the abundances of C 3 S in the three outflow sources, since the relative intensities of N- and S-bearing molecules in WCCC sources are close to those in