adsabs/WIESP2022-NER huggingface dataset:
Paper: 2018MNRAS.477..845G (acknowledgments)
ACKNOWLEDGEMENTS CG and SC acknowledge support from the Natural Science and Engineering Research Council (NSERC) of Canada through a PGS D scholarship and a Research Discovery Grant, respectively. This work also benefited from enlightening discussions with Peter Erwin, Jairo Méndez-Abreu, Sebastian F. Sánchez, and Jakob Walcher. Our referee's comments contributed to a leaner presentation of this paper. Funding for the SDSS IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS web site is www.sdss.org . SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatory of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. This work 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.459.2558S (acknowledgments)
The authors would like to thank the reviewer for drawing their attention to the recent work of Fivet et al. ( 2016 ) and suggesting the comparison. PJS acknowledges financial support from the Atomic Physics for Astrophysics Project (APAP) funded by the Science and Technology Facilities Council (STFC). The collision strength data, as a function of electron energy, for the lowest 15 levels of Co + and Co 2+ can be obtained in electronic format with full precision from the Centre de Données astronomiques de Strasbourg (CDS) data base.
Paper: 2017MNRAS.468.1029D (acknowledgments)
Acknowledgments We thank the referee, Dr Wendy Lane, for her useful comments. We thank the staff at GMRT for their help during the observations. GMRT is run by the National Centre for Radio Astrophysics of the Tata Institute of Fundamental Research. RS and NG acknowledge the support from the IndoFench Centre for the Promotion of Advanced Research (IFCPAR) under Project No. 5504-2. This research has made use of the NASA/IPAC Extragalactic Database (NED) that is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation and the U.S. Department of Energy Office of Science. The SDSS-III website is http://www.sdss3.org/ . SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including University of Arizona, Brazilian Participation Group, Brookhaven National Laboratory, Carnegie Mellon University, University of Florida, French Participation Group, German Participation Group, Harvard University, Instituto de Astrofisica de Canarias, 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, Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington and Yale University.
Paper: 2019MNRAS.490.1774L (acknowledgments)
ACKNOWLEDGEMENTS We thank Sasha Philippov and Deepto Chakrabarty for helpful discussions and valuable comments on the manuscript. We gratefully acknowledge support from NASA grant NNX16AC56G and NSF grant PHY-1752809.
Paper: 2017MNRAS.465.1665K (acknowledgments)
Acknowledgments This research 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 NASA, XMMNewton , an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA, and the Hale Telescope at Palomar Observatory. 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). We like to acknowledge S.G. Djorgovski for providing the Palomar observations. We thank the anonymous referee for comments and suggestions, which significantly contributed to improving the quality of the manuscript. EB received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 655324. Facilities: NuSTAR , Palomar: DBSP, XMMNewton .
Paper: 2016MNRAS.457.2480C (acknowledgments)
GALC acknowledges the support of an STFC PhD studentship. This research utilised Queen Mary's MidPlus computational facilities, supported by QMUL Research-IT and funded by EPSRC grant EP/K000128/1.
Paper: 2020ApJ...899L...5P (fulltext)
based on color to focus for example on red galaxies. We explored making cuts based on color like focusing on red galaxies; however, these cuts reduced the galaxy samples too much and did not allow one to obtain sufficient statistics. Hopefully with other incoming larger surveys we can explore those kinds of selections and their effects on the self-calibration. We find here a negative IG intrinsic alignment signal using the self-calibration method in the third and fourth bins. This is in agreement with the negative IA amplitude of found by KIDS450 team in Hildebrandt et al. ( 2017 ) from using the marginalization method and the linear tidal alignment model (Catelan et al. 2001 ; Hirata Seljak 2004 ; Bridle King 2007 ). In brief, this model is physically motivated by the concept that large-scale correlations between intrinsic ellipticities of galaxies are related linearly to perturbations in the primordial gravitational tidal field where these galaxies formed, leading to galaxy linear alignment with large-scale structure. The IG type of IA comes from the fact that a structure of matter aligns radially its close galaxies and shears tangentially background galaxies creating a correlation between these two as shown in Figure 1 (left panel). Our results are also consistent with the further findings of the KiDS+Gamma results of Johnston et al. ( 2019 ) where a negative amplitude also was found using the same model. We do not use any IA model in the self-calibration, but for comparisons we plotted the theory curves from this linear tidal alignment model with the IA amplitude as found in the in KIDS450 paper (Hildebrandt et al. 2017 ). Some overall consistency is good to find, but it is not surprising that some discrepancies would be present—IA modeling is an active area of work and self-calibration offers the opportunity to test such models once the signal is extracted. Although we are limited here in pursuing such a task, we expect in future work to pursue such an endeavor using more and better quality data from ongoing and planned surveys to constrain models using this approach. This will also allow one to compare to models like the Halo model introduced in Piras et al. ( 2018 ), or the higher-order nonlinear model of Blazek et al. ( 2019 ). 4. Conclusion A first detection of intrinsic shape–gravitational shear (IG) and the intrinsic shape–galaxy density (Ig) in a photometric redshift survey using the self-calibration method is reported. The IG cross-correlation between the third and fourth bins of the KiDS-450 data set is measured with a significance of 3.51 σ . The Ig correlation is measured in the third bin with a 3.65 σ significance. The negative IA signal we find here from the self-calibration method in the third and fourth bins, using the BPZ-determined best redshift estimate of Hildebrandt et al. ( 2017 ) is in agreement with the negative sign IA amplitude found there using the marginalization approach and the BPZ method and also is
Paper: 2016MNRAS.460.1390R (acknowledgments)
We would like to thank K. Abazajian, G. Bertone, A. Geringer-Sameth, M. Lovell, M. Walker, C. Weniger for collaboration, discussion and useful comments. EB acknowledges support by NASA through grant no. NNX123AE77G. The work of DI has been partially supported from the Swiss National Science Foundation grant SCOPE IZ7370-152581, the grant no. F64/42-2015 of the State Fund for Fundamental Research of Ukraine, the Program of Cosmic Research of the National Academy of Sciences of Ukraine, and the State Programme of Implementation of Grid Technology in Ukraine. The Draco dSph observations were performed as a part of AO-14 Very Large Programme obtained with XMM–Newton , an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA.
Paper: 2016MNRAS.455..462V (fulltext)
of different values of N and α. The 20 main simulations are divided into four sets with different orbital parameters e and Ω * . For each of these four sets, we have performed five simulations with different values of R * . We have performed the O1R39 simulation with N = 500 000 twice to investigate an unexpected effect of the numerical error in the angular momentum (see Section 4.3 ). The age at which the star reaches the desired radius is also included in Table 3 . Table 2. The initial parameters that we did not vary between the main simulations used in this work. The initial parameters that we did vary between simulations can be found in Table 3 . Table 3. The 20 main simulations used in this work and the initial parameters that were varied between them. For the three simulations in bold font, we also performed eight additional test simulations varying N and α (below table). 4.1 Tidal dissipation Before investigating the combined effects of tidal dissipation and mass-loss on the stellar orbit, we isolate the effect of tidal dissipation. We choose a simulation in which the stellar radius R * R Roche (model O0R37, see Table 3 ) so that mass-loss is negligible. In the absence of mass-loss, the change in the orbital parameters is dominated by the effects of tidal dissipation. In Fig. 5 we present the evolution of Ω * , a and e over a period of 5000 d (∼13 orbits). All simulations use the initial conditions of model O0R37 while we varied N (left-hand figure) and α (right-hand figure). It can be seen that for different values of these SPH parameters we find different values of . Figure 5. The long-term evolution through tidal dissipation of Ω * , a and e for model O0R37 with varying values of N and α. Dotted lines show the analytical solution for tidal dissipation (Hut 1981 ) with k / T ≈ 3( k / T ) Rasio . Different values of N and α result in a different radius of the relaxed SPH realization of the star. The analytical solution matching each simulation is therefore calculated with the effective radius of the SPH realization of the star in that simulation. The simulations with N = 100 000 and 200 000 are more computationally expensive and we have therefore decided to run them for only 2000 d. Note that the blue line in both plots is the same simulation. The difference in can be understood by taking the radius of the star into account. Because of the quantization approximations inherent to SPH, a different value of N can result in a slightly different hydrodynamical balance within the star. This difference, or even a different value of α, can result in variation of the radius of the SPH realization of the star after relaxation. Even a small change in R * can account for the differences in because (Hut 1981 ). While we do not include the physical processes that regulate tidal damping in our simulations, the artificial viscosity in SPH can cause dissipation. To interpret the results of our simulation, it is good to know how the time-scale of
Paper: 2017A&A...606A..83C (acknowledgments)
The authors would like to thank the referee for the constructive criticism. We also thank M. Sun, who kindly shared his X-ray data with us. This research has made use of the GOLDmine database (Gavazzi et al. 2003, 2014b) and 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. M. Fossati acknowledges the support of the Deutsche Forschungsgemeinschaft via Projects WI 3871/1-1, and WI 3871/1-2. M. Fumagalli acknowledges support by the Science and Technology Facilities Council [grant number ST/P000541/1]. For access to the codes and advanced data products used in this work, please contact the authors or visit https://github.com/mifumagalli/mypython/tree/master/ifu . Raw data are publicly available via the ESO Science Archive Facility.
Paper: 2017ApJ...843L..23V (fulltext)
i.e., . The relative plasmoid distances in a string vary depending on their different speeds along the jet, with the leading one significantly slowed down primarily by snow-plow effects against jet material, in particular, BLR clouds. This constitutes an interesting condition as the leading member in a string can reprocess and partially reflect some of the primary S radiation emitted by the trailing members (photons “mirrored” by slow clouds in the BLR were originally proposed by Ghisellini Madau 1996 ). Shrinking mirror-plasmoid gaps so produced provide compact sites with high seed photon densities for intense IC to take place. In a scenario with multiple emitting plasmoids (see Figure 1 ), the primary S flux in the optical–UV bands is emitted by a plasmoid like H starting within the BLR, that is, in the range . The S flux is emitted forward and mirrored backward by the leading plasmoid M toward an incoming plasmoid K . The whole process is subject to a “causality condition” (Böttcher Dermer 1998 ); the mirrored photons are received by an incoming plasmoid when the latter is at the receiving point that we denote with (cf. Figure 1 ). Figure 1. Schematic picture of the source structures we expect at and beyond the BLR. S radiation (orange dashed line) is emitted by inner plasmoids such as H at a radius r h and is reflected back (violet dotted lines) by the outermost mirror-plasmoid M at a radius toward an incoming plasmoid K : the encounter occurs at a radius . Dense seed photons build up in the gap between the approaching plasmoid K and the mirror, where they are IC upscattered to gamma-ray energies (green dotted lines) by electrons accelerated in and around plasmoids. The condition is easily evaluated when the same plasmoid moving with radial coordinate and boost Γ first emits at r , and then receives the radiation reflected backward by the mirror moving with coordinate and boost . The receiving point reads in the AGN frame, for primary photons emitted in the named range and reflected back at /. Here and correspondingly are the relative velocity and boost between the receiver and the mirror (note that /). Moreover, is the receiving point for primary photons emitted at and reflected at /. Note that for small values of r 0 the approximation holds; so the factor makes it possible to have relevant reflections beyond R BLR . The IC radiative event is completed when the plasmoid K crosses the effective gap defined byand lasts for an observer time /: this turns out to be about 2 minutes when, e.g., , , and hold. In the initial stage, the primary emitter radiates from an inner position and the mirror surface is small relative to the cross section of the emission beam as to reduce the effective power received by the mirror to in the head-on approximation and with . A fraction thereof is reflected back and is received by the incoming plasmoid when the latter is close to the reflection point, that is, in a cone of a cross section of order . Then,
Paper: 2019A&A...632A.125G (acknowledgments)
We thank Chris Flynn for carefully reading this manuscript and for providing valuable comment and suggestions. We also thank the participants of the 2017−2019 FRB meetings for the useful discussions. Thanks additionally go to Sarah Burke-Spolaor for initial survey parameter data. DWG acknowledges travel support from the Research Corporation for Scientific Advancement to attend the Aspen FRB meeting in 2017. The research leading to these results has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement n. 617199 (“ALERT”); from Vici research programme “ARGO” with project number 639.043.815, financed by the Netherlands Organisation for Scientific Research (NWO); and from the Netherlands Research School for Astronomy (NOVA4-ARTS). EP further acknowledges funding from an NWO Veni Fellowship. This research has made use of numpy ( van der Walt et al. 2011 ), scipy ( Oliphant 2007 ), astropy ( Astropy Collaboration 2018 ), matplotlib ( Hunter 2007 ), bokeh ( Bokeh Development Team 2018 ) and NASA’s Astrophysics Data System.
Paper: 2017A&A...606L...6Z (fulltext)
GHz transition under study belongs to the A series. Maser emission in transitions of this series was not observed or theoretically predicted. However, qualitative considerations show that this transition probably belongs to Class II. Observations show that the strongest Class II maser occurs in the A transition, while the strongest Class I maser occurs in the A transition. Class II methanol masers are therefore characterized by overpopulation of A levels of the ladder with respect to the A levels of the ladder, while for Class I masers the situation is opposite. Model calculations for Class II methanol maser conditions by Cragg et al. (2005) show that A levels of the ladder tend to be overpopulated with respect to A levels of the ladder. This means that the 349.1070 GHz transition from A series most probably belongs to the Class II family. Strong support for this conclusion comes from the observational evidence that emission in the newly discovered maser transition covers the same velocity range and shows a similar position-velocity dependence as the strongest Class II methanol maser at 6.7 GHz ( Moscadelli et al. 2017 ). The spectra and the peak locations of the new maser may not coincide with those of the 6.7 GHz masers because of the different sensitivity to the physical conditions, which is usual for Class II methanol maser transitions ( Cragg et al. 2005 ). The A line series contains transitions with frequencies starting from 303.37 GHz. Many of them can be observed with the same instrument, which allows avoiding calibration problems in determining the relative line intensities. The lower levels of these transitions cover a rather wide range of energies from 2.32 K for the A level to 243.45 K for the A lower level of the transition under study and higher. It is worth mentioning that in our SMA data obtained in December 2010, the CHOH A line at 342.729796 GHz was detected in quasi-thermal emission ( Zinchenko et al. 2015 ). This may indicate that the discovered maser is related to the accretion burst in 2015, but additional modeling and monitoring of these lines is needed for an exact answer. Observations of the methanol line series proved to be a good tool for the physical parameter diagnostics both in maser and quasi-thermal cases ( Voronkov et al. 2006 ; Menten et al. 1988 ; Salii Sobolev 2006 ). This is very important because the new maser line was detected toward positions that are spread over the disk. An inspection of our channel maps shows that the peaks of the maser emission at different velocities lie on a curve that resembles an arc (Fig. 3 c). This can be part of a ring in the disk or on the surface of the disk at a substantial distance of several hundred AU from the star. Taking into account the disk orientation, which follows from the outflow data ( Zinchenko et al. 2015 ; Burns et al. 2016 ), it becomes clear that the brightest emission comes from the part of the disk that is closer to us. For the lower brightness
Paper: 2016ApJ...830...12M (fulltext)
Because complete atomic line lists for these heavy species are not available (Kasen et al. 2013 ), we have simply assumed that the energy integral of the full radiative spectra of r -process material is similar to that of Fe. Under these conditions, we find that metal cooling from r -process material is not expected to influence the dynamics of NSBM remnants expanding into an ambient medium with . The resulting NSBM remnant evolution in these environments should solely be determined by the metal cooling of the swept-up material. However, the mass fraction of r -process material at shell formation within the remnant is expected to be severely enhanced to about , assuming a solar abundance ratio and . In contrast, with a total r -process mass per supernova of (Shen et al. 2015 ), we expect a local enhancement of only about when a Type II SNR attains shell formation in similar external conditions. Of particular relevance in this case is the heavy element composition of galactic halo stars with the metallicity regime , which has been found to have pure r -process products with a distribution that is characteristic of solar system matter but with a large star-to-star scatter in their r -process concentrations (Sneden et al. 2008 ). In some stars with , the r -process enrichment can be as large as 10 2 , assuming a solar abundance ratio. The presence of r -process material in these stars with a distribution that is characteristic of solar abundance ratios illustrates that r -process enrichment has operated in a fairly robust manner, while their abundance dispersions further suggest that r -process production sites must be rare and locally very enhanced, as expected from NSBM enrichment (e.g., Shen et al. 2015 ). These localized inhomogeneities would then be smoothed out as more NSBMs take place and r -process material is given more time to be transported and mixed throughout the early Milky Way. Metal feedback from NSBM remnants is thus essential to understand the formation of r -process enhanced stars in galaxies. Despite the initial differences, our conclusions regarding the efficacy of the transport and mixing of r -process material by NSBM remnants in a cosmological context should be similar to that expected from single SNRs. APPENDIX RESOLUTION CONVERGENCE Here we describe the results of our resolution study. Simulations are initialized with a static AMR and with a maximum level of refinement of 10 within a sphere enclosing all of the tail material. In all cases, we reduce the refinement by two levels after the size of the tidal remnant reaches 1/20 of the size of the computational box. The grid mesh refinement is then based on the value of the density. To test how our results are sensitive to the refinement criteria and resolution, we run two more simulations using the initial fiducial model parameters but subtracting three and one level(s) of refinement, respectively. We compare the different simulations in Figure 8 with final