Large-scale structure surveys measure the shapes and positions of millions of galaxies in order to constrain the cosmological model with high precision. The resulting large data volume poses a challenge for the analysis of the data, from the estimation of photometric redshifts to the calibration of shape measurements. We present GalSBI, a model for the galaxy population, to address these challenges. This phenomenological model is constrained by observational data using simulation-based inference (SBI). The galsbi Python package provides an easy interface to generate catalogs of galaxies based on the GalSBI model, including their photometric properties, and to simulate realistic images of these galaxies using the UFig package.
@article{arxiv.2412.08722,
title = {galsbi: A Python package for the GalSBI galaxy population model},
author = {Silvan Fischbacher and Beatrice Moser and Tomasz Kacprzak and Joerg Herbel and Luca Tortorelli and Uwe Schmitt and Alexandre Refregier and Adam Amara},
journal= {arXiv preprint arXiv:2412.08722},
year = {2025}
}
Comments
8 pages, 2 figures, accepted for publication in JOSS