Hello, I'm Adam Coogan.

I'm a physicist searching for dark matter in astrophysical systems by creating new statistical machine learning analyses and improving our physics models.

I am currently a postdoc at the Université de Montréal and Mila, the Quebec AI Institute. Previously I was a postdoc at GRAPPA , an institute in the University of Amsterdam. I did my PhD at UC Santa Cruz and my ScB at Brown University.

Research themes

Strong gravitational lensing. How can we use machine learning to probe the smallest dark matter structures in the universe in images of dramatically distorted galaxies?
Check out my interactive visualization to learn more!
Gravitational wave probes of new physics. What imprint does a black hole binary’s environment leave on its gravitational wave signal? How can we uncover this it in data?
Dark matter indirect detection. How can we best utilize cosmic rays and gamma rays to learn about the fundamental nature of dark matter, be it a particle or something else?
Machine learning and statistics. What new precision data analyses can we unlock using modern machine learning and computational statistics?

Papers

You can find all my physics publications on InspireHEP, and some highlights here:

Estimating the warm dark matter mass from strong lensing images with truncated marginal neural ratio estimation
Noemi Anau Montel, Adam Coogan, Camila Correa, Konstantin Karchev, Christoph Weniger
Accepted by Monthly Notices of the Royal Astronomical Society with minor revisions · [arXiv]
#lensing #machine-learning

Efficient Template Bank Generation with Differentiable Waveforms
Adam Coogan, Thomas D. P. Edwards, Horng Sheng Chia, Richard N. George, Katherine Freese, Cody Messick, Christian N. Setzer, Christoph Weniger, Aaron Zimmerman
Accepted by Physical Review D with minor revisions · [arXiv]
#gravitational-waves #machine-learning

Measuring the dark matter environments of black hole binaries with gravitational waves
Adam Coogan, Gianfranco Bertone, Daniele Gaggero, Bradley J. Kavanagh, David A. Nichols
Physical Review D 105 (2022) 4, 043009 · [arXiv]
#gravitational-waves

Strong-lensing source reconstruction with variationally-optimised Gaussian processes
Konstantin Karchev, Adam Coogan, Christoph Weniger
Monthly Notices of the Royal Astronomical Society, stac311 · [arXiv]
#lensing #machine-learning

Targeted Likelihood-Free Inference of Dark Matter Substructure in Strongly-Lensed Galaxies
Adam Coogan, Konstantin Karchev, Christoph Weniger
NeurIPS workshop on Machine Learning and the Physical Sciences (2020) · [arXiv]
#lensing #machine-learning

Direct Detection of Hawking Radiation from Asteroid-Mass Primordial Black Holes
Adam Coogan, Logan Morrison, Stefano Profumo
Physical Review Letters 126 (2021) 17, 171101 · [arXiv]
#indirect-detection

Hazma: A Python Toolkit for Studying Indirect Detection of Sub-GeV Dark Matter
Adam Coogan, Logan Morrison, Stefano Profumo
Journal of Cosmology and Astroparticle Physics 01 (2020) 056 · [arXiv]
#indirect-detection

Origin of the tentative AMS antihelium events
Adam Coogan, Stefano Profumo
Physical Review D 96 (2017) 8, 083020 · [arXiv]
#indirect-detection

Code

My Github page contains code for some of my papers and other projects, including:

diffbank: gravitational wave template bank generation made easy with jax's automatic differentiation. Created with Thomas Edwards.
Hazma: a python toolkit to compute indirect detection constraints for dark matter models producing MeV gamma rays. Co-developed with Logan Morrison and used in several of our papers: 1907.11846, 2010.04797 , 2101.10370, 2104.06168.
diffjeom: differential geometry powered by jax's automatic differentiation engine. You provide a metric tensor, diffjeom gives you the Christoffel symbols, scalar curvature, and more.
jaxinterp2d: simple bilinear interpolation on regular grids with jax.
Tasty Base: a React + Firebase app for keeping track of your recipes and finding new ones. I built Tasty Base with my partner, Laura Henn, who’s a cloud developer. Source code here.

Non-work

I like rock climbing, remote nature, cooking, traveling, sailing, learning languages, making and seeing art, and building digital and physical things.

I took all the photos on this site except the one of me, which Laura took. I made this site with her help.