7 papers
Cluster Mass Inference from Galaxy Kinematics
Bonny Y. Wang, Leander Thiele, Matthew Ho
The masses of galaxy clusters carry cosmological and astrophysical information. We develop a simulation-based inference pipeline to infer cluster masses from full projected phase-s…
Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations
Laura Sommovigo, Deaglan J. Bartlett, Rachel K. Cochrane +3
Dust attenuation is a major source of systematic uncertainty in both SED fitting and forward modeling of galaxy populations, yet the functional form used to parameterize attenuatio…
\texttt{calypso}: a Parameter-Conditioned Stochastic Surrogate Model for Circumbinary Accretion Time-Series
Magdalena Siwek, Matt Ho, Earl Bellinger
We present calypso, a parameter-conditioned stochastic surrogate model for circumbinary accretion flows. We represent the total and individual accretion time series in a PCA basis…
Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer
Thomas Harvey, Christopher C. Lovell, Sophie Newman +13
We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible f…
Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours
Christopher C. Lovell, Tjitske Starkenburg, Matthew Ho +9
We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation based inference ap…
Cosmology with One Galaxy: Auto-Encoding the Galaxy Properties Manifold
Amanda Lue, Shy Genel, Marc Huertas-Company +2
Cosmological simulations like CAMELS and IllustrisTNG characterize hundreds of thousands of galaxies using various internal properties. Previous studies have demonstrated that mach…