Theoretical Astrophysicist · Carnegie Observatories

Andrew Benson

I am a Staff Scientist at the Carnegie Observatories. My research is focused on understanding the nature of dark matter and the process of galaxy formation — combining analytic models, numerical simulations, and large astronomical surveys.

Andrew Benson

Research focus

What I work on

Three threads tie my research together: building a coherent theoretical model of galaxy formation; constraining the microphysics of dark matter; and designing the synthetic universes that next-generation surveys need to interpret their data.

Recent work

Selected recent papers

These cards are rebuilt automatically from my NASA ADS library on a weekly schedule. Summaries and figures are generated from the paper itself.

Figure from Mixed Dark Matter: Limits from the Milky Way Satellite Galaxies

arXiv e-prints 2026

Mixed Dark Matter: Limits from the Milky Way Satellite Galaxies

Crumrine, Wendy, A. Benson, et al.

This study establishes new constraints on mixed dark matter models using data from Milky Way satellite galaxies, revealing how the presence of different dark matter components affects the formation of small-scale structures. The findings indicate that as the fraction of non-standard dark matter increases, the constraints on its properties weaken, highlighting the need for future surveys to refine these limits further.

Figure from The free-streaming length of dark matter from JWST observations of 28 strong gravitational lenses

arXiv e-prints 2026

The free-streaming length of dark matter from JWST observations of 28 strong gravitational lenses

Gilman, D., A. Benson, et al.

This study uses observations from the James Webb Space Telescope to measure the properties of dark matter halos in 28 strong gravitational lens systems, providing significant constraints on the free-streaming length of dark matter. The results support the cold dark matter model by ruling out deviations on large scales and establishing lower limits on the mass of thermal relic dark matter particles.

Figure from Calibrating the self-interacting dark matter gravothermal catastrophe with <inline-formula><mml:math><mml:mi>N</mml:mi></mml:math></inline-formula>-body simulations

Physical Review D 2026

Calibrating the self-interacting dark matter gravothermal catastrophe with N-body simulations

Mace, Charlie, A. Benson, et al.

This study calibrates the heat transfer parameter in self-interacting dark matter models using advanced simulations, revealing that this parameter is consistent across various halo conditions. The findings provide a reliable model for predicting dark matter halo evolution, streamlining comparisons with simulations and enhancing our understanding of dark matter dynamics.

Figure from Connection between Galaxy Morphology and Dark-matter Halo Structure. II. Predicting Disk Structure from Dark-matter Halo Properties

The Astrophysical Journal 2026

Connection between Galaxy Morphology and Dark-matter Halo Structure. II. Predicting Disk Structure from Dark-matter Halo Properties

Liang, Jinning, A. Benson, et al.

This study reveals that the structure of galactic disks can be accurately predicted from the properties of their dark-matter halos, highlighting the influence of baryonic processes on halo characteristics. The findings provide valuable empirical relations for modeling galaxy structures, particularly emphasizing the differences in predictions based on halo mass and redshift.

Figure from DiffstarPop: A generative physical model of galaxy star formation history

The Open Journal of Astrophysics 2026

DiffstarPop: A generative physical model of galaxy star formation history

Alarcon, Alex, A. Benson, et al.

DiffstarPop is a new model that accurately simulates the star formation histories of galaxies by linking them to the mass assembly of dark matter halos. This tool can efficiently generate large catalogs of synthetic galaxies, enhancing our understanding of galaxy formation and evolution in cosmological simulations.

See all recent papers →

Open source

Galacticus

Most of my modeling work happens inside Galacticus, an open-source semi-analytic model of galaxy formation that I wrote and continue to develop. It's used by groups around the world to study dark matter, galaxy evolution, and forecast observations for upcoming surveys. See the full software stack →