Testing the ΛCDM paradigm with growth rate data and machine learning

DOI10.1088/1475-7516/2022/05/047zbMath1505.83009arXiv2107.04343OpenAlexW4287081840MaRDI QIDQ5099322

Rubén Arjona, A. Melchiorri, Savvas Nesseris

Publication date: 31 August 2022

Published in: Journal of Cosmology and Astroparticle Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2107.04343

zbMATH Keywords

machine learningmodified gravitydark energy theory

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Relativistic gravitational theories other than Einstein's, including asymmetric field theories (83D05) Cobordism and concordance in topological manifolds (57N70) Dark matter and dark energy (83C56)

Cites Work

• Unnamed Item
• A profile likelihood analysis of the constrained MSSM with genetic algorithms
• Novel null-test for the Λ cold dark matter model with growth-rate data
• Cosmological constraints with the Effective Fluid approach for Modified Gravity
• Machine learning meets the redshift evolution of the CMB temperature
• Regression methods in waveform modeling: a comparative study

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