Andrew Zentner: Halo Clustering, Galaxy Clustering, and the Theory and Detection of Assembly Bias

Tuesday 4 Nov 2025, 13:15 → 14:00 Europe/Stockholm

FB42 (AlbaNova Main Building)

Dark matter halos provide the potential wells within which galaxy formation occurs. As such, halos are the essential scaffolding of large-scale structure which supports the visible facade of galaxies. Understanding the clustering of halos is a first step toward understanding the clustering of galaxies. It has long been known that the clustering of dark matter halos is a very strong function of halo mass. What has been appreciated for roughly 20 years now, is that halos cluster differentially as a function of their other properties as well. Assembly bias of halos is a jargon term for the dependence of halo clustering on properties other than mass. This is interesting for many reasons. If galaxies populate halos in a manner that does not depend solely upon halo mass, but on other halo properties as well, then it will not be possible to model and interpret galaxy clustering at high precision with models of the galaxy—halo connection that map galaxies onto halos in a manner that depends only on mass. This can have many important consequences for the interpretation of galaxy surveys and for cosmology. As a simple example, it can add scatter and/or systematic errors into the inferred galaxy mass—halo mass relation. I will briefly review assembly bias and describe two recent claims of the detection of halo bias in SDSS and DESI data by members of my group. Time permitting, I would be happy to sketch other interesting work in my group including gravitational production of dark matter, using stars as probes of dark matter, and answer questions!

About the speaker:  Andrew Zentner (University of Pittsburgh) is a theorists with a broad range of research interest, falling under cosmology and structure formation. These include galaxy formation, the phenomenology and identification of the dark matter and dark energy, and astrophysical limits on fundamental physics. He maintains close collaborations with observational surveys to connect theoretical predictions and interpretation of data.

In the OKC:  A5:1049, Tuesday Nov 4th