6.6k citations · 31.5k across the 180 of their papers we have counts for
181 papers
Reproducibility of machine learning analyses of 21 cm reionization maps
Kimeel Sooknunan, Emma Chapman, Luke Conaboy +2
Machine learning (ML) methods have become popular for parameter inference in cosmology, although their reliance on specific training data can cause difficulties when applied across…
Field-level inference of cosmic shear with intrinsic alignments and baryons
Natalia Porqueres, Alan Heavens, Daniel Mortlock +2
We construct a field-based Bayesian Hierarchical Model for cosmic shear that includes, for the first time, the important astrophysical systematics of intrinsic alignments and baryo…
Hierarchical Bayesian inference of photometric redshifts with stellar population synthesis models
Boris Leistedt, Justin Alsing, Hiranya Peiris +2
We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectra…
Forward modeling of galaxy populations for cosmological redshift distribution inference
Justin Alsing, Hiranya Peiris, Daniel Mortlock +2
We present a forward modeling framework for estimating galaxy redshift distributions from photometric surveys. Our forward model is composed of: a detailed population model describ…
Assessing coincident neutrino detections using population models
F. Capel, J. M. Burgess, D. J. Mortlock +1
Several tentative associations between high-energy neutrinos and astrophysical sources have been recently reported, but a conclusive identification of these potential neutrino emit…
Rubin-Euclid Derived Data Products: Initial Recommendations
Leanne P. Guy, Jean-Charles Cuillandre, Etienne Bachelet +117
This report is the result of a joint discussion between the Rubin and Euclid scientific communities. The work presented in this report was focused on designing and recommending an…