UniverseMachine: The correlation between galaxy growth and dark matter halo assembly from z = 0−10

We present a method to flexibly and self-consistently determine individual galaxies’ star formation rates (SFRs) from their host haloes’ potential well depths, assembly histories, and redshifts. The method is constrained by galaxies’ observed stellar mass functions, SFRs (specific and cosmic), quenched fractions, ultraviolet (UV) luminosity functions, UV–stellar mass relations, IRX–UV relations, auto- and cross-correlation functions (including quenched and star-forming subsamples), and quenching dependence on environment; each observable is reproduced over the full redshift range available, up to 0 5. Also presented are revised stellar mass – halo mass relations for all, quenched, star-forming, central, and satellite galaxies; the dependence of star formation histories on halo mass, stellar mass, and galaxy SSFR; quenched fractions and quenching time-scale distributions for satellites; and predictions for higher-redshift galaxy correlation functions and weak lensing surface densities. The public data release (DR1) includes the massively parallel (>10 5 cores) implementation (the UniverseMachine), the newly compiled and remeasured observational data, derived galaxy formation constraints, and mock catalogues including lightcones.Giacconi Fellowship from the Space Telescope Science Institute; NASA through a Hubble Fellowship grant from the Space Telescope Science Institute [HST-HF2-51353.001-A]; NASANational Aeronautics & Space Administration (NASA) [NAS5-26555]; NSFNational Science Foundation (NSF) [1066293]; National Science Foundation (NSF)National Science Foundation (NSF) [PHY11-25915]; Munich Institute for Astro-and Particle Physics (MIAPP) of the DFG cluster of excellence 'Origin and Structure of the Universe; Office of Science of the U.S. Department of EnergyUnited States Department of Energy (DOE) [DE-AC02-05CH11231]; DOEUnited States Department of Energy (DOE) [DE-AC02-76SF00515]; NASA High-EndComputing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center; PRACE [012060963]; Alfred P. Sloan FoundationAlfred P. Sloan Foundation; U.S. Department of Energy Office of ScienceUnited States Department of Energy (DOE); University of Arizona; Brazilian Participation Group; Brookhaven National LaboratoryUnited States Department of Energy (DOE); Carnegie Mellon University; French Participation Group; German Participation Group; Harvard University; Instituto de Astrofisica de Canarias; Michigan State/Notre Dame/JINA Participation Group; Johns Hopkins UniversityJohns Hopkins University; Lawrence Berkeley National LaboratoryUnited States Department of Energy (DOE); Max Planck Institute for Astrophysics; Max Planck Institute for Extraterrestrial Physics; Pennsylvania State University; Princeton UniversityPrinceton University; Spanish Participation Group; Yale University; University of FloridaUniversity of Florida; NewMexico State University; New York University; Ohio State UniversityOhio State University; University of Portsmouth; University of Tokyo; University of Utah; Vanderbilt University; University of Virginia; University of WashingtonUniversity of WashingtonThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu