Passive Evolution of Galaxy Clustering
Hee-Jong Seo, Daniel J. Eisenstein, Idit Zehavi

TL;DR
This study uses N-body simulations to analyze how galaxy clustering evolves passively over time, revealing convergence in clustering properties and halo occupation distribution parameters, with implications for understanding galaxy evolution.
Contribution
It provides a detailed numerical analysis of passive galaxy flow evolution, highlighting convergence behaviors and comparing results with SDSS LRG observations.
Findings
Passive flow leads to convergence in galaxy clustering and HOD parameters at low redshift.
Satellite galaxy distributions tend toward Poisson statistics over time.
Discrepancies with observations suggest effects like galaxy merging or new member addition.
Abstract
We present a numerical study of the evolution of galaxy clustering when galaxies flow passively from high redshift, respecting the continuity equation throughout. While passive flow is a special case of galaxy evolution, it allows a well-defined study of galaxy ancestry and serves as an interesting limit to be compared to non-passive cases. We use dissipationless N-body simulations, assign galaxies to massive halos at z=1 and z=2 using various HOD models, and trace these galaxy particles to lower redshift while conserving their number. We find that passive flow results in an asymptotic convergence at low redshift in the HOD and in galaxy clustering on scales above ~3Mpc/h for a wide range of initial HODs. As galaxies become less biased with respect to mass asymptotically with time, the HOD parameters evolve such that M1/Mm decreases while alpha converges toward unity, where Mm is the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
