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Published June 2017 | Submitted + Published
Journal Article Open

Forward and backward galaxy evolution in comoving cumulative number density space

Abstract

Galaxy cumulative comoving number density is commonly used to forge progenitor/descendant links between observed galaxy populations at different epochs. However, this method breaks down in the presence of galaxy mergers, or when galaxies experience stochastic growth rates. We present a simple analytic framework to treat the physical processes that drive the evolution and diffusion of galaxies within comoving number density space. The evolution in mass rank order of a galaxy population with time is influenced by (1) the non-conservative nature of total galaxy number density driven by galaxies combining in mergers (which we tabulate as a galaxy 'coagulation' rate) and (2) galaxy 'mass rank scatter' driven by stochasticity in stellar-mass growth rates from in situ star formation and mergers. We quantify the relative contribution of these two effects to the total mass rank order evolution using the Illustris simulation. We show that galaxy coagulation is dominant at lower redshifts and stellar masses, while scattered growth rates dominate the mass rank evolution at higher redshifts and stellar masses. For a galaxy population at 10^(10) M⊙, coagulation has been the dominant effect since z = 2.2, but a galaxy population at 10^(11) M⊙ was dominated by mass rank scatter until z = 0.6. We show that although the forward and backward median cumulative number density evolution tracks are asymmetric, the backward median cumulative number density evolution can be obtained by convolving the descendant distribution function with progenitor relative abundances. We tabulate fits for the median cumulative number density evolution and scatter that can be applied to improve the way galaxy populations are linked in multi-epoch observational data sets.

Additional Information

© 2017 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2017 February 9. Received 2017 February 8; in original form 2016 June 23. Published: 16 February 2017. We thank the referee, Bart Clauwens, for the many thoughtful comments that have strengthened this work. PT is supported through Hubble Fellowship grant #HST-HF2-51384.001-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. Support for PFH was provided by an Alfred P. Sloan Research Fellowship, NASA ATP Grant NNX14AH35G, NSF Collaborative Research Grant #1411920 and CAREER Grant #1455342. MV acknowledges support through an MIT RSC award. The Illustris simulation was run on the CURIE supercomputer at CEA/France as part of PRACE project RA0844, and the SuperMUC computer at the Leibniz Computing Centre, Germany, as part of project pr85je. Further simulations were run on the Harvard Odyssey and CfA/ITC clusters, the Ranger and Stampede supercomputers at the Texas Advanced Computing Center through XSEDE and the Kraken supercomputer at Oak Ridge National Laboratory through XSEDE. The analysis reported in this paper was performed on the Caltech compute cluster 'Zwicky' (NSF MRI award #PHY-0960291), the joint partition of the MIT-Harvard computing cluster 'Odyssey' supported by MKI and FAS, and allocation TG-AST150059 granted by the Extreme Science and Engineering Discovery Environment (XSEDE) supported by the NSF.

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Submitted - 1606.07271.pdf

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Additional details

Created:
August 19, 2023
Modified:
October 25, 2023