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      The SAMI Galaxy Survey: The Internal Orbital Structure and Mass Distribution of Passive Galaxies from Triaxial Orbit-superposition Schwarzschild Models

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          Abstract

          Dynamical models are crucial for uncovering the internal dynamics of galaxies; however, most of the results to date assume axisymmetry, which is not representative of a significant fraction of massive galaxies. Here, we build triaxial Schwarzschild orbit-superposition models of galaxies taken from the SAMI Galaxy Survey, in order to reconstruct their inner orbital structure and mass distribution. The sample consists of 161 passive galaxies with total stellar masses in the range 10 9.5–10 12 M . We find that the changes in internal structures within 1 R e are correlated with the total stellar mass of the individual galaxies. The majority of the galaxies in the sample (73% ± 3%) are oblate, while 19% ± 3% are mildly triaxial and 8% ± 2% have triaxial/prolate shape. Galaxies with log M / M > 10.50 are more likely to be non-oblate. We find a mean dark matter fraction of f DM = 0.28 ± 0.20, within 1 R e. Galaxies with higher intrinsic ellipticity (flatter) are found to have more negative velocity anisotropy β r (tangential anisotropy). β r also shows an anticorrelation with the edge-on spin parameter λ Re , EO , so that β r decreases with increasing λ Re , EO , reflecting the contribution from disk-like orbits in flat, fast-rotating galaxies. We see evidence of an increasing fraction of hot orbits with increasing stellar mass, while warm and cold orbits show a decreasing trend. We also find that galaxies with different ( V/ σh 3) kinematic signatures have distinct combinations of orbits. These results are in agreement with a formation scenario in which slow- and fast-rotating galaxies form through two main channels.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            THE AVERAGE STAR FORMATION HISTORIES OF GALAXIES IN DARK MATTER HALOS FROMz= 0-8

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              The Sloan Digital Sky Survey: Technical Summary

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                Journal
                The Astrophysical Journal
                ApJ
                American Astronomical Society
                0004-637X
                1538-4357
                May 13 2022
                May 01 2022
                May 13 2022
                May 01 2022
                : 930
                : 2
                : 153
                Article
                10.3847/1538-4357/ac5bd5
                98329067-5de9-4223-b23c-7f7b77035ce3
                © 2022

                http://creativecommons.org/licenses/by/4.0/

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