AbacusHOD: A highly efficient extended multi-tracer HOD framework and
  its application to BOSS and eBOSS data
  We introduce the AbacusHOD model and present two applications of AbacusHOD
and the AbacusSummit simulations to observations. AbacusHOD is an HOD framework
written in Python that is particle-based, multi-tracer, highly generalized, and
highly efficient. It is designed specifically with multi-tracer/cosmology
analyses for next generation large-scale structure surveys in mind, and takes
advantage of the volume and precision offered by the new state-of-the-art
AbacusSummit cosmological simulations. The model is also highly customizable
and should be broadly applicable to any upcoming surveys and a diverse range of
cosmological analyses. In this paper, we demonstrate the capabilities of the
AbacusHOD framework through two example applications. The first example
demonstrates the high efficiency and the large HOD extension feature set
through an analysis full-shape redshift-space clustering of BOSS galaxies at
intermediate to small scales (<30Mpc/h), assessing the necessity of introducing
secondary galaxy biases (assembly bias). We find strong evidence for using halo
environment instead of concentration to trace secondary galaxy bias, a result
which also leads to a moderate reduction to the "lensing is low" tension. The
second example demonstrates the multi-tracer capabilities of the AbacusHOD
package through an analysis of the extended Baryon Oscillation Spectroscopic
Survey (eBOSS) cross-correlation measurements between three different galaxy
tracers, LRGs, ELGs, and QSOs. We expect the AbacusHOD framework, in
combination with the AbacusSummit simulation suite, to play an important role
in a simulation-based analysis of the up-coming Dark Energy Spectroscopic
Instrument (DESI) datasets.
