From DESI to Euclid: A Generative Bridge to Unbiased Galaxy Structures

arXiv:2607.06891 · astro-ph.GA, astro-ph.IM · Submitted 2026-08-20 · Read on arXiv

Renhao Ye, Shiyin Shen

astro-ph.GA, astro-ph.IM

Submitted: 2026-08-20

Updated: 2026-08-21

Comments: 10 pages, 6 figures, submitted to ApJL. Code and prediction available; feel free to download, use, and build on them. Prediction: https://doi.org/10.5281/zenodo.21032414

Code: https://github.com/Rh-YE/EBGS

License: http://creativecommons.org/licenses/by/4.0/

The gist: Ground-based seeing imprints a size-dependent bias on galaxy structural parameters, yet the space-based imaging needed to remove it currently covers only a small fraction of the sky.

Terminology

Abstract

Ground-based seeing imprints a size-dependent bias on galaxy structural parameters, yet the space-based imaging needed to remove it currently covers only a small fraction of the sky. We close this gap with a generative model that translates DESI imaging of Bright Galaxy Survey (BGS) targets into Euclid VIS images. A Fourier-domain analysis confirms that it recovers structure down to 0.37'' (from the 1.41'' DESI r-band baseline), an approximately 3.8-fold improvement in resolution. Although it stops short of the 0.16'' Euclid VIS resolution, this recovery already de-biases the structural parameters relative to the DESI r-band structure measurements: the Petrosian radius bias falls to +0.075'' (from-0.870''), independent of galaxy size; the S'ersic-radius bias drops to-0.018'' (from-0.322''); and the S'ersic-index bias to +0.093 (from +0.262). We release these translations over the Euclid DR1 footprint as the Euclid-resolution BGS (E-BGS), which can be blindly validated once DR1 is public.

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