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Hauptverfasser: Sharma, Mohit K., Sami, M.
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2408.04204
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author Sharma, Mohit K.
Sami, M.
author_facet Sharma, Mohit K.
Sami, M.
contents We study the possibility of accommodating both early and late-time tensions using a novel reinforcement learning technique. By applying this technique, we aim to optimize the evolution of the Hubble parameter from recombination to the present epoch, addressing both tensions simultaneously. To maximize the goodness of fit, our learning technique achieves a fit that surpasses even the $Λ$CDM model. Our results demonstrate a tendency to weaken both early and late time tensions in a completely model-independent manner.
format Preprint
id arxiv_https___arxiv_org_abs_2408_04204
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Reconciling Early and Late Time Tensions with Reinforcement Learning
Sharma, Mohit K.
Sami, M.
Cosmology and Nongalactic Astrophysics
General Relativity and Quantum Cosmology
We study the possibility of accommodating both early and late-time tensions using a novel reinforcement learning technique. By applying this technique, we aim to optimize the evolution of the Hubble parameter from recombination to the present epoch, addressing both tensions simultaneously. To maximize the goodness of fit, our learning technique achieves a fit that surpasses even the $Λ$CDM model. Our results demonstrate a tendency to weaken both early and late time tensions in a completely model-independent manner.
title Reconciling Early and Late Time Tensions with Reinforcement Learning
topic Cosmology and Nongalactic Astrophysics
General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2408.04204