adsabs/WIESP2022-NER huggingface dataset:
Paper: 2019MNRAS.487..198G (acknowledgments)
ACKNOWLEDGEMENTS This work was supported by the Science and Technology facilities Council (STFC) ST/L00075X/1. AJG acknowledges an STFC studentship funded by grant ST/N50404X/1. CL is funded by an Australian Research Council Discovery Early Career Researcher Award (DE150100618) and by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. This work used the Distributed Research using Advanced Computing (DiRAC) Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFC DiRAC High Performace Computing Facility ( www.dirac.ac.uk ). This equipment was funded by BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grants ST/H008519/1 and ST/K00087X/1, STFC DiRAC Operations grant ST/K003267/1, and Durham University. DiRAC is part of the National E-Infrastructure.
Paper: 2020A&A...643A.165B (fulltext)
assumptions on the mass profile. By introducing a mass-sheet degeneracy parameter, we add the maximal degree of freedom in H 0 while having minimal constraining power by lensing data on their own. This is the most conservative approach when adding a single degree of freedom in our analysis. While mathematically this result is clearly understood, it is worth discussing the physical interpretation of this choice. If we had perfect cosmological numerical simulations or perfect knowledge of the internal mass distribution within elliptical galaxies, we would not have to worry about the internal MST. The approach chosen by our collaboration ( Wong et al. 2020 ; Shajib et al. 2019 ; Millon et al. 2020 ) was to assume physically motivated mass profiles with degrees of freedom in their parameters. In particular, the collaboration used two different mass profiles, a power-law elliptical mass profile, and a composite mass profile separating the luminous component (with fixed mass-to-light ratio) and a dark component described as a NFW profile. The good fit to the data, the small pixellated corrections on the profiles from the first lens system ( Suyu et al. 2010 ), and the good agreement of H 0 inferred with the two mass profiles was a positive sanity check on the result ( Millon et al. 2020 ). In this paper we have taken a different viewpoint, and asked how much can the mass profiles depart from a power-law and still be consistent with the data. By phrasing the question in terms of the MST we can conveniently carry out the calculations, because the MST leaves the lensing observables unchanged and therefore it corresponds to minimal constraints and assumptions, and thus maximal uncertainties with one additional degree of freedom. However, after the inference, one has to examine the inferred MST transformed profile and evaluate it in comparison with existing and future data to make sure it is realistic. We know that the exact MST cannot be the actual answer because profiles have to go zero density at large radii, but the approximate MST discussed in Sect. 2 provides a convenient interpretation with the addition of a cored mass component. Figure 17 illustrates a cored mass component approximating the MST inferred from this work, λ int = 0.91 ± 0.04, in combination with a power-law model inferred from the population mean of the SLACS analysis by Shajib et al. (2020b) . The analysis presented here guarantees that the inferred mass profile is consistent with the properties of TDCOSMO and SLACS lenses. We discuss below how additional data may allow us to constrain the models even further and thus reduce the overall uncertainty while keeping the assumptions at a minimum. Fig. 17. Illustration of the inferred mass profile of the joint TDCOSMO+SLACS SDSS + IFU analysis. A pure power-law with γ pl = 2.10 ± 0.05 is shown in orange. In blue is the result of this work of λ int = 0.91 ± 0.045 when interpreted as a cored mass component with R c uniform in [3′′,
Paper: 2017ApJ...840...41E (acknowledgments)
We dedicate this paper to the memory of Neil Gehrels, the P.I. of Swift and a leading author of this paper. Neil was a great scientist who also brought out the best in others. He led the Swift team with enthusiasm and expertise, always happy and eager to take the satellite in new directions. For example, his strong and unwavering support is what allowed Swift to gather these unprecedented data on NGC 5548 and NGC 4151, providing a powerful method that should continue to inform our understanding of AGN physics for years to come. Specifically, without his courageous approval of increased UVOT filter changes well beyond the design lifetime of the filter wheel, the extraordinary 11-band light curve in Figure 3 , which forms the basis of this work, could not have been gathered. This is but one tiny piece of the rich legacy that he leaves us. We further thank the entire Swift team for their tireless dedication and flawless execution of these programs and acknowledge the use of public data from the Swift data archive. We also thank the anonymous referee for helpful and timely reports. This research has made use of the XRT Data Analysis Software (XRTDAS) developed under the responsibility of the ASI Science Data Center (ASDC), Italy. R.E. gratefully acknowledges support from NASA under awards NNX13AC26G, NNX13AC63G, and NNX13AE99G. J.M.G. acknowledges support from NASA under award NNH13CH61C. Research by A.J.B. and H.A.V. was supported by NSF grant AST-1412693. K.H. acknowledges support from STFC grant ST/M001296/1. M.B. gratefully acknowledges support from the NSF through CAREER grant AST-1253702. S.M.C. and E.R.C. gratefully acknowledge the receipt of research grants from the National Research Foundation (NRF) of South Africa. P.E. and K.P. acknowledge support from the UK Space Agency. A.V.F. and W.Z. are grateful for financial assistance from NSF grant AST-1211916, the TABASGO Foundation, and the Christopher R. Redlich Fund. D.C.L. gratefully acknowledges support from NSF under grants AST-1009571 and AST-1210311. T.T. has been supported by NSF grant AST-1412315 and by the Packard Foundation in the form of a Packard Research Fellowship. M.V. gratefully acknowledges support from the Danish Council for Independent Research via grant no. DFF 4002-00275.
Paper: 2016MNRAS.461.2068K (acknowledgments)
IK thanks Lodovico Coccato and Sergey Khoperskov for useful discussions. The work was supported by the Russian Science Foundation project 14-22-00041 ‘VOLGA – A View On the Life of GAlaxies’. The final interpretation of the data and paper writing was performed during visits to Chamonix workshop and The Research Institute in Astrophysics and Planetology in Toulouse which were supported by MD-7355.2015.2, RFBR 15-32-21062, and RFBR-CNRS 15-52-15050 grants. The project used computational resources funded by the M.V. Lomonosov Moscow State University programme of Development. The Russian 6-m telescope is exploited under the financial support by the Russian Federation Ministry of Education and Science (agreement No14.619.21.0004, project ID RFMEFI61914X0004). This research has made use of the NED which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration, and of the Lyon Extragalactic Database (LEDA). In this study, we used the SDSS DR12 data. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the US Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS web site is http://www.sdss.org/ .
Paper: 2021MNRAS.504.4626K (fulltext)
(Dubois et al. 2014 ; Codis et al. 2018 ; Wang et al. 2018 ; Ganeshaiah Veena et al. 2019 ; Kraljic, Davé Pichon 2020b ). The mass dependence of the spin alignment signal is however debated. While some works confirmed the existence of a galaxy spin transition from parallel to perpendicular with respect to the filament’s direction (Dubois et al. 2014 ; Codis et al. 2018 ; Kraljic et al. 2020b ), and analogously with respect to walls (Codis et al. 2018 ; Kraljic et al. 2020b ), others (Ganeshaiah Veena et al. 2019 ; Krolewski et al. 2019 ) found preferential perpendicular orientation with respect to filaments at all masses with no sign of a spin transition. A possible interpretation of this lack of detection of a clear transition is the nature of the filaments, with galaxies in thinner filaments having their spins more likely perpendicular to the filament’s axis, compared to galaxies of similar mass in thicker filaments (Ganeshaiah Veena et al. 2019 ). This can be in turn understood recalling the multiscale nature of the problem and the conditional TTT (Codis et al. 2015 ) predicting larger transition mass for denser, thus thicker, filaments. Further support for this interpretation was provided by the findings of stronger impact of large-scale tides on the galaxy spin orientation in denser filaments (Kraljic et al. 2020b , using filament density as a proxy for the thickness of filaments). In addition to the stellar mass, the spin-filament alignment was shown to depend on other internal properties of galaxies. Blue or rotation-supported galaxies were found to dominate the alignment signal at low stellar mass, while red or dispersion-dominated galaxies tend to show a preferential perpendicular alignment (Codis et al. 2018 ; Wang et al. 2018 ; Kraljic et al. 2020b ). The orientation of the galaxies’ spin with respect to their large-scale environment has been quite extensively studied also on the observational side. When focusing on disc galaxies, some groups find preferentially parallel orientation for spirals (Tempel Libeskind 2013 ; Tempel, Stoica Saar 2013 ), Scd types (Hirv et al. 2017 ), or both red and blue galaxies (Zhang et al. 2013 ). Others report a tendency for a perpendicular orientation for spirals (Lee Erdogdu 2007 ; Jones, van de Weygaert Aragón-Calvo 2010 ; Zhang et al. 2015 ) and Sab galaxies (Hirv et al. 2017 ), or no evidence for a clear signal (Pahwa et al. 2016 ; Krolewski et al. 2019 ). A much better agreement seems to exist for elliptical/S0 galaxies, for which a preferential orthogonal orientation of their spin (or minor axis) with respect to their host filaments is found (Tempel et al. 2013 ; Pahwa et al. 2016 ), in agreement with with results of shape measurements (e.g. Okumura Jing 2009 ; Joachimi et al. 2011 ; Singh, Mandelbaum More 2015 ; Chen et al. 2019 ; Johnston et al. 2019 ). More recently, Welker et al. ( 2020 ) studied the alignment of galactic spin in projection with respect to the filaments of the cosmic
Paper: 2018MNRAS.480.3152V (acknowledgments)
ACKNOWLEDGEMENTS We thank the referee, Prof. Harald Ebeling, for his insightful comments that allowed us to strengthen the results presented in this paper. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programme 196.B-0578. We acknowledge funding from the INAF PRIN-SKA 2017 program 1.05.01.88.04 (PI Hunt). YJ acknowledges support from CONICYT PAI (Concurso Nacional de Inserción en la Academia 2017) No. 79170132.
Paper: 2017ApJ...844..148V (fulltext)
due to the forces connected to the torsional Alfvén wave. Therefore, by having these expressions to hand, the efficiency of collimation due to the atmospheric and equilibrium conditions together with the nonlinear forces connected to the torsional Alfvén wave can be better understood. This provides a helpful tool and a robust standing point for observation purposes and coronal seismology. If one asks how, the answer lies in Figures 2 and 3 , where the interplay of the plasma- β and the shear flow on the density perturbations and jet cross section is highlighted. It can clearly be seen that the efficiency of the shear flow is highly elevated in higher plasma- β regions. This means that in the solar photosphere, where the plasma- β equals unity, the density perturbation amplitude due to the nonlinear forces and the external pressure force increases to over twice that of the solar corona. Note in the absence of the shear flow, the plasma- β acts mutually for the density perturbations due to the nonlinear effects connected to the torsional Alfvén wave. Figure 2. Interplay of the plasma- β and the shear flow ( u 0 ) effective on the density perturbations inside the jet due to the nonlinear forces (left panel) and the external pressure force (right panel). The surface plot is created from Equation ( 25 ), and the shear flow is normalized by the Alfvén speed. The interplay of the plasma- β and the shear flow on the perturbations of the jet cross section is pictured in the two panels of Figure 3 . By glancing over the surface plots of Figure 3 it can beseen that for coronal conditions (low plasma- β ) the perturbations of the jet cross section are anti-phase with those inside the jet. This means that for coronal conditions the forces effective on the jet collimation prove more efficient compared with the photospheric conditions. Figure 3. Interplay of the plasma- β and the shear flow ( u 0 ) effective on the jet cross section perturbation due to the nonlinear forces (left panel) and the external pressure force (right panel. The surface plot is created from Equation ( 33 ), and the shear flow is normalized by the Alfvén speed. The reason for this anti-phase behavior for coronal conditions can be better understood when the parallel speed perturbations surf against the shear flow and plasma- β . Figure 4 shows that the parallel speed perturbations due to the forces working on the jet collimation connected to the torsional wave are in phase with the density perturbations. In the low plasma- β regime, an increase in the perturbation amplitude of the density is accompanied by an increase in the parallel speed of the plasma. The decrease in the jet cross section is therefore due to the Bernoulli effect. However for photospheric conditions (finite plasma- β regime), the jet cross section is in phase with the density and parallel speed perturbations connected to the nonlinear torsional Alfvén wave. Figure 4. Interplay of the plasma- β and the shear flow (
Paper: 2016ApJ...832...88B (fulltext)
of the most massive stars to the core results in a runaway stellar collision (Portegies Zwart et al. 2004 ; van der Marel 2004 , p. 37). This collision produces a seed BH of several hundred to several thousand solar masses (Katz et al. 2015 ). 3. Over the next several billion years the halo continues to accrete gas, feeding additional star formation and the central BH. During this era, feedback from bursty star formation precludes the formation of a significant bulge (Guedes et al. 2011 ; Governato et al. 2010 ). 4. Between 5 and 10 Gyr ago, the dwarf falls into Centaurus A. This allows enough time for its gas, dark matter, and outer stars to be completely stripped (Smith et al. 2013 , 2015 ), therefore the DSCs would not be hosted in the surviving subhalos at z = 0. At z = 0, the only remaining sign of the lost dwarf is the remnant cusp of stars surrounding its central SMBH. Excepting its dynamics and metallicity, the surviving stellar cusp resembles a GC. Since these systems resemble GCs photometrically and structurally, it is only possible to disentangle their origin as lost dwarf galaxies through the dynamic signatures of their central BHs and the following observational criteria. Chemical composition : if the DSCs formed as dwarf galaxies their residual stellar populations should accordingly have dwarf galaxy-like chemical abundances; namely, a significantly elevated metallicity dex, a measurable metallicity spread (), and a higher ratio than expected for their present stellar mass on the –luminosity relation of stellar systems (e.g., Thomas et al. 2005 ; Smith et al. 2009 ). In addition, they should be above expectations from the L –[Fe/H] relation for systems with . From the selective enrichment by core-collapse supernovae we would also expect enhanced ratios of light elements (CNO) to iron, as well as a significant variance in iron-peak elements. X-ray flux : while the central BH is likely now quiescent, low-level accretion (∼10 −8 Eddington) is possible via AGB (asymptotic giant branch) winds and planetary nebulae. At Centaurus A’s distance, even these low accretion rates would be detectable by Chandra or XMM for the expected central BH masses. 6. SUMMARY AND CONCLUSIONS We have used a new set of high-resolution simulations of an isolated Centaurus A analog to investigate possible formation models for the DSCs found in T15 . We assume that the DSCs formed within dark matter halos before determining which Centaurus A subhalos at z = 0 have the highest probability of being DSC progenitors. We find that DSCs likely formed in dark matter halos that virialized at high redshift with . Since dark matter halos grow in mass in isolation, we assume that any DSC progenitor had . However, no dark matter profile associated with the Centaurus A system, whether for the subhalos at z = 0, z peak , or high redshift (e.g., z = 9.3), has a high enough central density to account for the dynamical mass derived for the DSCs. Even the densest DM halos fall
Paper: 2016ApJ...819...32U (acknowledgments)
This work is supported by NSF CAREER grant EAR-60023026 to W.R.P.. Special thanks to Ian Rose for creating the initial mass–radius code for the CIDER 2014 Summer Institute. The Python scripts for Figure 1 are available in latest release of the BurnMan software as planet_builder.py with code for creating other figures available upon request.
Paper: 2020A&A...633A.104P (acknowledgments)
The authors are grateful to the referee, whose detailed and constructive comments greatly improved the manuscript. We would also like to thank P. Bonfini and T. Bitsakis for many useful discussions and comments on this work. This research made use of MONTAGE . It is funded by the National Science Foundation under Grant Number ACI-1440620, and was previously funded by the National Aeronautics and Space Administration’s Earth Science Technology Office, Computation Technologies Project, under Cooperative Agreement Number NCC5-626 between NASA and the California Institute of Technology. M. V. was supported by an IKY postdoctoral Scholarship.
Paper: 2016A&A...585A..58V (fulltext)
flux were fit simultaneously by varying and the gas-to-dust ratio. The outer radius was set by fitting the CO spectrum (the maxima in the spectra or double peaks that arise from the Keplerian motion) and provides outer boundaries for computing the gas masses. Using this surface density profile, the emission inside the cavity is constrained by the parameters (Fig. 4 ). The near-infrared excess determines the dust density in the inner disk through . The gas cavity radius and drop were fit to the CO emission. In some cases, an additional drop in gas surface density is required between and the dust cavity radius . This drop is indicated by . The main parameters that are varied are the gas cavity radius and the drop in gas density between and . The CO isotopologs provide better constraints on the density than the CO because they are less optically thick (CO) or even optically thin (CO). The effects of isotope-selective photodissociation are properly considered in the modeling and are discussed in Sect. 4.3 . 4. Results Table 3 Results for the gas density profile of each transition disk. Notes. (a) HD13 = HD 135344B. (b) The masses are only constrained within for the detected surface brightness. (c) The drop inside 7 AU could not be constrained by the ALMA data; we adopt the value from CO rovibrational spectroastrometry by Pontoppidan et al. (2008) . (d) The uncertainties on the gas cavity size are typically 5 AU and lower than one order of magnitude on the depth of the drop. Fig. 5 Modeling results and observations of the CO and CO emission for the best-fitting models in derotated images and spectra. The left panels show the direct image comparison of the zero-moment map: derotated observations, model, convolved model, and residual. In the residual map the overlaid contours indicate the 3 levels, where dashed lines are negative. The central panels show the gas density profiles with different drops as solid lines and the dust density profile as dashed lines. The right panels show the resulting intensity cuts for the major and minor axis for both CO and CO. The best-fitting model is indicated in red, other values in blue. The drop in density can be constrained to within an order of magnitude. Data and models are compared through the spectra and the zero-moment maps (intensity maps) of both CO and CO. For each target we show the direct comparison of the images of the intensity map of the best-fit model and the constraint on both and through spectra and intensity cuts through the major and minor axis of the zero-moment map. In three of the four targets an inner gas cavity (smaller than the dust cavity) was required to fit the data. In SR21 the 7 AU cavity previously derived from rovibrational emission was adopted, but no gas cavity is resolved at the spatial resolution of (24 AU) in our observations. In all disks, the depth is constrained to within an order of magnitude and the cavity size to within 5 AU, mainly through the comparison of the spatially
Paper: 2016MNRAS.463.4422Z (acknowledgments)
GZ thanks insightful discussions with Andrew Vanderburg and Bryce Croll. JPM is supported by a UNSW Vice-Chancellor's Postdoctoral Fellowship. We thank the support staff at the AAO , who made the continued IRIS2 observations possible. This work makes use of observations from the LCOGT network. DD acknowledges support provided by NASA through Hubble Fellowship grant HST-HF2-51372.001 -A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555.