Theoretical Astrophysicist · Carnegie Observatories
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.
Research focus
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.
Galaxy formation
An open-source semi-analytic model of galaxy formation used to interpret observations across cosmic time.
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Dark matter
Using halo substructure, gravitational lensing, and dwarf galaxies to test warm, self-interacting, and other non-CDM models.
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Surveys
Building galaxy mocks for the Roman GRS Project Infrastructure Team and the NASA Open Universe initiative.
Read more →Recent work
These cards are rebuilt automatically from my NASA ADS library on a weekly schedule. Summaries and figures are generated from the paper itself.
This research presents a highly precise model for the dark matter halo mass function, applicable across various dark matter theories and effective over a vast range of halo masses. The model's accuracy and ability to account for environmental influences make it essential for future dark matter studies and data analysis.
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.
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.
This research presents a refined model for understanding how dark matter substructures interact with stellar streams, predicting significantly more gaps in these streams than previously estimated. The findings enhance the potential of stellar streams as tools for probing dark matter, providing a more accurate framework for future observations.
This research calibrates the heat transfer parameter in self-interacting dark matter models, finding it to be consistent across various halo properties. The developed effective model allows for accurate predictions of dark matter halo evolution without the need for extensive simulations.
This study establishes new lower limits on the mass of ultralight dark matter particles by analyzing the abundance of Milky Way satellite galaxies. The findings suggest that the particle mass must exceed approximately \(6 \times 10^{-18}\) eV, which has significant implications for understanding the nature of dark matter.
Open source
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 →