output
20032026
most citedThe automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations

7.9k citations

Showing 2023 · astro-ph.GAShow all

11 papers · 2 filters

astro-ph.GA2023★ 2 cited

Environmental Quenching of Low Surface Brightness Galaxies near Milky Way mass Hosts

J. Bhattacharyya, A. H. G. Peter, P. Martini +48

Low Surface Brightness Galaxies (LSBGs) are excellent probes of quenching and other environmental processes near massive galaxies. We study an extensive sample of LSBGs near massiv…

astro-ph.GA2023★ 11 cited

A Bayesian Approach to Strong Lens Finding in the Era of Wide-area Surveys

Philip Holloway, Philip J. Marshall, Aprajita Verma +5

The arrival of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), Euclid-Wide and Roman wide area sensitive surveys will herald a new era in strong lens scienc…

astro-ph.GA2023★ 2 cited

Dark Energy Survey Year 6 Results: Intra-Cluster Light from Redshift 0.2 to 0.5

Yuanyuan Zhang, Jesse B. Golden-Marx, Ricardo L. C. Ogando +46

Using the full six years of imaging data from the Dark Energy Survey, we study the surface brightness profiles of galaxy cluster central galaxies and intra-cluster light. We apply…

astro-ph.GA2023★ 16 cited

On the detectability of strong lensing in near-infrared surveys

Philip Holloway, Aprajita Verma, Philip J. Marshall +2

We present new lensing frequency estimates for existing and forthcoming deep near-infrared surveys, including those from JWST and VISTA. The estimates are based on the JAdes extraG…

astro-ph.GA2023★ 12 cited

Filamentary Dust Polarization and the Morphology of Neutral Hydrogen Structures

George Halal, Susan E. Clark, Ari Cukierman +2

Filamentary structures in neutral hydrogen (HI) emission are well aligned with the interstellar magnetic field, so HI emission morphology can be used to construct templates that st…

astro-ph.GA2023★ 7 cited

Weakly-Supervised Anomaly Detection in the Milky Way

Mariel Pettee, Sowmya Thanvantri, Benjamin Nachman +3

Large-scale astrophysics datasets present an opportunity for new machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional searc…