21 papers
Astrometric constraints on stochastic gravitational wave background with neural networks
Marienza Caldarola, Gonzalo Morrás, Santiago Jaraba +3
Astrometric measurements provide a unique avenue for constraining the stochastic gravitational wave background (SGWB). In this work, we investigate the application of two neural ne…
Dark Energy Survey Year 6 Results: Cell-based Coadds and Metadetection Weak Lensing Shape Catalogue
M. Yamamoto, M. R. Becker, E. Sheldon +81
We present the Metadetection weak lensing galaxy shape catalogue from the six-year Dark Energy Survey (DES Y6) imaging data. This dataset is the final release from DES, spanning 44…
Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog
D. Anbajagane, M. Tabbutt, J. Beas-Gonzalez +79
Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, a…
Improving Galaxy Cluster Selection with the Outskirt Stellar Mass of Galaxies
Matthew Kwiecien, Tesla Jeltema, Alexie Leauthaud +53
The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, . However, recent res…
Euclid preparation LXXI. Simulations and nonlinearities beyond CDM. 3. Constraints on models from the photometric primary probes
Euclid Collaboration, K. Koyama, S. Pamuk +275
We study the constraint on gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical…
Discovering Strong Gravitational Lenses in the Dark Energy Survey with Interactive Machine Learning and Crowd-sourced Inspection with Space Warps
J. Gonzalez, P. Holloway, T. Collett +70
We conduct a search for strong gravitational lenses in the Dark Energy Survey (DES) Year 6 imaging data. We implement a pre-trained Vision Transformer (ViT) for our machine learnin…