2026 Project Description

Beyond Halo Mass: Building Realistic Galaxy Mock Catalogs

Supervisors

Tomomi Sunayama
Find out more about supervisors on ASIAA website

Task Description and Goals

Modern galaxy surveys rely heavily on mock galaxy catalogs to interpret observations and extract precise cosmological information. These mocks are typically constructed from N-body simulations, which track only cold dark matter. To populate dark matter halos with galaxies, a widely used approach is the Halo Occupation Distribution (HOD) model, which assumes that the number of galaxies in a halo depends only on its mass.

While powerful, this assumption is an oversimplification. In reality, galaxy formation depends not only on halo mass, but also on how and when the halo formed. Halos with identical masses but different assembly histories can host very different galaxy populations — an effect known as halo assembly bias.

In this project, the student will move beyond standard HOD modeling and construct next-generation galaxy mock catalogs that incorporate halo assembly bias. Using high-resolution N-body simulations, the student will:

• Explore different galaxy–halo connection models, from traditional HOD to assembly-bias–aware prescriptions
• Quantify how halo formation history (e.g. concentration, formation time, environment) influences galaxy occupation and properties
• Generate mock galaxy catalogs and compare their clustering, number densities, and environmental trends
• Assess the impact of assembly bias on cosmological observables, such as galaxy clustering and galaxy–halo correlations

This project directly addresses a key systematic uncertainty in precision cosmology and is highly relevant for current and future surveys such as HSC, DESI, LSST, and Roman.

Required Background

Strong programming skills, especially in Python