Dark Energy Survey Year 3 results: wCDM cosmology from simulation-based inference with persistent homology on the sphere

Prat, J., Gatti, M., Doux, C., Pranav, P., Chang, C., Jeffrey, N., Whiteway, L., Anbajagane, D., Sugiyama, S., Thomsen, A., Alarcon, A., Amon, A., Bechtol, K., Bernstein, G. M., Campos, A., Chen, R., Choi, A., Davis, C., DeRose, J., Dodelson, S., Eckert, K., Elvin-Poole, J., Everett, S., Ferté, A., Gruen, D., Huff, E. M., Harrison, I. ORCID: https://orcid.org/0000-0002-4437-0770, Herner, K., Jarvis, M., Kuropatkin, N., Leget, P.-F., MacCrann, N., McCullough, J., Myles, J., Navarro-Alsina, A., Pandey, S., Raveri, M., Rollins, R. P., Roodman, A., Sánchez, C., Secco, L. F., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Aguena, M., Allam, S., Andrade-Oliveira, F., Blazek, J., Bocquet, S., Brooks, D., Carretero, J., Rosell, A. Carnero, Cawthon, R., De Vicente, J., Desai, S., Pereira, M. E. da Silva, Diehl, H. T., Flaugher, B., Frieman, J., García-Bellido, J., Gruendl, R. A., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., da Costa, L. N., Lahav, O., Lee, S., Marshall, J. L., Mena-Fernández, J., Miquel, R., Mohr, J. J., Ogando, R. L. C., Malagón, A. A. Plazas, Porredon, A., Samuroff, S., Sanchez, E., Santiago, B., Sevilla-Noarbe, I., Smith, M., Suchyta, E., Swanson, M. E. C., Thomas, D., To, C., Vikram, V., Walker, A. R., Weaverdyck, N. and Weller, J. 2025. Dark Energy Survey Year 3 results: wCDM cosmology from simulation-based inference with persistent homology on the sphere. Monthly Notices of the Royal Astronomical Society , staf2152. 10.1093/mnras/staf2152

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Abstract

We present cosmological constraints from Dark Energy Survey Year 3 (DES Y3) weak lensing data using persistent homology, a topological data analysis technique that tracks how features like clusters and voids evolve across density thresholds. For the first time, we apply spherical persistent homology to galaxy survey data through the algorithm TopoS2, which is optimized for curved-sky analyses and HEALPix compatibility. Employing a simulation-based inference framework with the Gower Street simulation suite—specifically designed to mimic DES Y3 data properties—we extract topological summary statistics from convergence maps across multiple smoothing scales and redshift bins.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Physics and Astronomy
Publisher:	Oxford University Press
ISSN:	0035-8711
Date of First Compliant Deposit:	8 December 2025
Last Modified:	08 Dec 2025 15:00
URI:	https://orca.cardiff.ac.uk/id/eprint/182983

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