Clustering from the Local Universe to Cosmic Dawn

Abstract

Galaxy science and cosmology are rapidly extending to ever higher redshifts, where new observations have motivated a wide range of galaxy formation models. Because these models are all tuned to reproduce observed number densities, clustering provides the critical observable for breaking their degeneracies. Pure-parallel surveys, often underexploited, enable clustering to be measured through field-to-field variance across a broad redshift range. I will show measurements from the JWST PANORAMIC survey, spanning quiescent galaxies at intermediate redshift to luminous Lyman-break galaxies above z∼10. Linear-bias results from COSMOS-Web up to z∼8 reveal a consistent picture: galaxies in the early universe are highly clustered, placing strong constraints on models of early formation. Remarkably, even carefully tuned models struggle to reproduce the observed amplitudes. Cosmic variance also emerges as both a systematic and a tool in number-count statistics, with particular relevance for explaining the presence of ultra-massive quiescent galaxies already in the young universe. I will also provide a brief overview of complementary low-redshift work, including the use of small-scale clustering to reconstruct halo merger trees with graph neural networks, and other efforts to maximize the scientific return of the next generation of galaxy surveys.