activity
20102022
most citedConstraints on dark matter scenarios from measurements of the galaxy luminosity function at high redshifts

120 citations · 587 across the 16 of their papers we have counts for

collaborators

16 papers

astro-ph.CO2022★ 31 cited

LensWatch: I. Resolved HST Observations and Constraints on the Strongly-Lensed Type Ia Supernova 2022qmx ("SN Zwicky")

J. D. R. Pierel, N. Arendse, S. Ertl +39

Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools…

nucl-ex2022★ 51 cited

Horizons: Nuclear Astrophysics in the 2020s and Beyond

H. Schatz, A. D. Becerril Reyes, A. Best +162

Nuclear Astrophysics is a field at the intersection of nuclear physics and astrophysics, which seeks to understand the nuclear engines of astronomical objects and the origin of the…

astro-ph.CO2021★ 15 cited

The RayGalGroupSims cosmological simulation suite for the study of relativistic effects: an application to lensing-matter clustering statistics

Y. Rasera, M-A. Breton, P-S. Corasaniti +8

General Relativistic effects on the clustering of matter in the universe provide a sensitive probe of cosmology and gravity theories that can be tested with the upcoming generation…

astro-ph.CO2020★ 3 cited

Dependence of the dynamical properties of light-cone simulation dark matter halos on their environment

Maria Chira, Manolis Plionis, Shankar Agarwal

Aims: We study the dependence of the dynamical properties of dark matter halos on their environment in a whole-sky CDM light-cone simulation extending to . The prope…

astro-ph.CO2020★ 11 cited

Cosmological Model Parameter Dependence of the Matter Power Spectrum Covariance from the DEUS-PUR Simulations

Linda Blot, Pier-Stefano Corasaniti, Yann Rasera +1

Future galaxy surveys will provide accurate measurements of the matter power spectrum across an unprecedented range of scales and redshifts. The analysis of these data will require…

astro-ph.GA2017★ 71 cited

Painting galaxies into dark matter halos using machine learning

Shankar Agarwal, Romeel Davé, Bruce A. Bassett

We develop a machine learning (ML) framework to populate large dark matter-only simulations with baryonic galaxies. Our ML framework takes input halo properties including halo mass…