Small-scale clustering of DESI emission-line galaxies
Cosmological constraints from ELG clustering down to 0.3 h−1 Mpc with SHAMe-SF.
Research theme · 02
Galaxy–halo connection
Galaxies do not trace dark matter in a simple way. I develop and test empirical models that capture this connection well enough to use nonlinear clustering for cosmology.
Modern surveys measure galaxy clustering with such precision that simplified assumptions about galaxy formation can dominate the error budget. Assembly history, satellite evolution, baryonic physics, and sample selection all reshape the observed signal.
I study these effects in hydrodynamical simulations and encode them in flexible empirical models such as SHAMe and SHAMe-SF. The goal is to extract unbiased cosmology from small scales while retaining a transparent physical interpretation of the galaxy population.
Selected work
Modelling galaxies in halos
Measuring and predicting galaxy assembly bias
Understanding how assembly bias changes with selection, number density, and redshift.
Validating empirical models with FLAMINGO
Testing HOD and SHAMe predictions with clustering, lensing, and higher-order statistics.
Consistent clustering and lensing of BOSS galaxies
Showing how flexible galaxy–halo models resolve the artificial lensing-is-low discrepancy.