Towards an optimal extraction of cosmological parameters from galaxy cluster surveys using convolutional neural networks

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Publication Details

Journal
Astronomy and Computing
Published
2026-02-03
DOI
https://doi.org/10.1016/j.ascom.2026.101067
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00

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article

Towards an optimal extraction of cosmological parameters from galaxy cluster surveys using convolutional neural networks

J-M Christille, I. Sáez-Casares, D. Bianchi, M. Calabrese et al.
Astronomy and Computing
Galaxies: Formation, Evolution, Phenomena
article

Towards an optimal extraction of cosmological parameters from galaxy cluster surveys using convolutional neural networks

J-M Christille, I. Sáez-Casares, D. Bianchi, M. Calabrese, M. Chiarenza, M.S. Cagliari, L. Guzzo
article en

Abstract

No abstract available for this paper.
Astronomy and ComputingVol. 55
Fondazione CRT, Università degli Studi di Milano, European Commission
Openalex Percentile: Top 68%
Galaxies: Formation, Evolution, Phenomena
DOIOpen Access PDFOpenAlex
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Towards an optimal extraction of cosmological parameters from galaxy cluster surveys using convolutional neural networks — J-M Christille, I. Sáez-Casares, et al. · Astronomy and Computing (2026) | TGRS Research Map | TGRS