Publications & Research Output
Peer-reviewed research and scholarly contributions
Research Areas
🤖 Statistical Learning & AI
Developing novel methods to discover patterns from large, messy datasets.
🔍 Interpretability & Insight
Understanding how statistical methods work to extract scientific insights.
⚡ Inference & Computation
Designing robust algorithms to quantify how much we can learn from data.
🌌 Discovery & Understanding
Applying these methods to astronomical surveys to understand galaxy formation and evolution.
Publications Overview
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Featured Publications
It's a matter of time: Empirical Constraints on Supernova Yields and Delay Times from Dwarf Spheroidal Galaxies
2026 • arXiv e-prints
The chemical abundances of a stellar population encode information about nucleosynthesis and its astrophysical sites, but this information is confounded by the specific star formation history of the host galaxy. As a result, placing empirical constraints on supernova yields and timing using abundances has been very challenging. We introduce a galactic chemical evolution model DLEIY that uses an observed star formation history and metallicity distribution to reduce these confounding factors. Using a joint statistical model of the dwarf spheroidal galaxies Sculptor and Fornax, simultaneous constraints on population-averaged yields and galactic outflows are achieved with DLEIY, without fixing the absolute scale of nucleosynthetic yields. The Fe yield from core collapse supernovae is consistent with existing theoretical yield models, while the measured Mg yield is a factor of 2-4 higher, corroborating previous suggestions that yield models may under-predict [Mg/Fe]. We also find that the rate of Type Ia supernovae is enhanced by about a factor of 5 relative to field galaxies, and the delay-time distribution goes as $\sim t^{-2}$, a much steeper relationship than that measured from supernova surveys ($\sim t^{-1.1}$). These findings may suggest a metallicity dependence of the Type Ia rate and delay-time distribution.
An Ancient Descendant of the First Galaxies
2025 • arXiv e-prints
JWST has revealed unexpectedly bright galaxies in the first 500 Myr after the Big Bang. Their overabundance suggests that they are preferentially observed during burst phases, where their star formation rates increase dramatically. In cosmological simulations, such bursts transition into short ($\approx 40$ Myr) periods without star formation or naps. Using JWST/NIRCam medium-band observations, we report the discovery of the galaxy CANUCS-A370-2228423 ($z = 5.95 \pm 0.06$, $\log(M_\ast/M_{\odot}) = 9.14 \pm 0.09$), dubbed The Sleeper. Its star formation history indicates rapid assembly in the first 300 Myr ($z \gtrsim 14$), where it formed a $\log(M_\ast/M_{\odot}) = 8.7^{+0.3}_{-0.4}\ M_{\odot}$ progenitor, comparable in stellar mass to the few spectroscopically confirmed galaxies at those redshifts. Unexpectedly, this is followed by several hundred million years of suppressed star formation, in stark contrast to nappers. This results in a remarkably strong hydrogen Balmer break, exceeding that of any galaxy observed within the first billion years by a factor of $\approx 3$. Furthermore, Sleeper-like systems are overabundant in the observed survey volume compared to theory, as the probability of finding such galaxies in simulations is $< 0.2\%$. The discovery of The Sleeper therefore disrupts the current narrative that all luminous galaxies in the first few hundred million years grow into massive descendants. Instead it presents an alternative evolutionary pathway in which these unusually luminous galaxies fade into inefficient dwarfs after an early starburst, revealing greater diversity in the first stages of galaxy evolution.
Deriving Stellar Properties, Distances, and Reddenings using Photometry and Astrometry with BRUTUS
2025 • arXiv e-prints • 2 citations
We present brutus, an open source Python package for quickly deriving stellar properties, distances, and reddenings to stars based on grids of stellar models constrained by photometric and astrometric data. We outline the statistical framework for deriving these quantities, its implementation, and various Galactic priors over the 3-D distribution of stars, stellar properties, and dust extinction (including $R_V$ variation). We establish a procedure to empirically calibrate MIST v1.2 isochrones by using open clusters to derive corrections to the effective temperatures and radii of the isochrones, which reduces systematic errors on the lower main sequence. We also describe and apply a method to estimate photometric offsets between stellar models and observed data using nearby, low-reddening field stars. We perform a series of tests on mock and real data to examine parameter recovery with MIST under different modeling assumptions, illustrating that brutus is able to recover distances and other stellar properties using optical to near-infrared photometry and astrometry. The code is publicly available at https://github.com/joshspeagle/brutus.