144 citations · 480 across the 9 of their papers we have counts for
19 papers
Inpainting Galaxy Counts onto N-Body Simulations over Multiple Cosmologies and Astrophysics
Antoine Bourdin, Ronan Legin, Matthew Ho +3
Cosmological hydrodynamical simulations, while the current state-of-the art methodology for generating theoretical predictions for the large scale structures of the Universe, are a…
Caustics: A Python Package for Accelerated Strong Gravitational Lensing Simulations
Connor Stone, Alexandre Adam, Adam Coogan +9
Gravitational lensing is the deflection of light rays due to the gravity of intervening masses. This phenomenon is observed in a variety of scales and configurations, involving any…
Interpretable machine learning for finding intermediate-mass black holes
Mario Pasquato, Piero Trevisan, Abbas Askar +4
Definitive evidence that globular clusters (GCs) host intermediate-mass black holes (IMBHs) is elusive. Machine learning (ML) models trained on GC simulations can in principle pred…
Searching for strong gravitational lenses
Cameron Lemon, Frédéric Courbin, Anupreeta More +9
Strong gravitational lenses provide unique laboratories for cosmological and astrophysical investigations, but they must first be discovered - a task that can be met with significa…
Time Delay Cosmography with a Neural Ratio Estimator
Ève Campeau-Poirier, Laurence Perreault-Levasseur, Adam Coogan +1
We explore the use of a Neural Ratio Estimator (NRE) to determine the Hubble constant () in the context of time delay cosmography. Assuming a Singular Isothermal Ellipsoid (SI…
AstroPhot: Fitting Everything Everywhere All at Once in Astronomical Images
Connor Stone, Stephane Courteau, Jean-Charles Cuillandre +3
We present AstroPhot, a fast, powerful, and user-friendly Python based astronomical image photometry solver. AstroPhot incorporates automatic differentiation and GPU (or parallel C…