A Self-calibrating Halo-based Galaxy Group Finder: Algorithm and Tests

Abstract We describe an extension of the halo-based galaxy group-finding algorithm. add freedom to algorithm in order more accurately determine which galaxies are central and satellites, provide unbiased estimates halo masses. focus on determination galaxy-halo relations for star-forming quiescent galaxies. The added is self-calibrated using observations color-dependent clustering, as well measurements total satellite luminosity deep imaging data around stacked samples spectroscopic galaxies, L sat . test this approach a series mocks that vary connection, including one mock constructed from Universe Machine results. Our shows marked improvement over previous methods estimating fraction It reduces error log M h by factor two, ≲0.2 dex. Through data, it can quantify differences luminosity-to-halo mass even groups with only member. Thus, whereas algorithms cannot constrain scatter gal at fixed M h , self-calibration technique robust lower limit scatter.