Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 63 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 31 tok/s Pro
GPT-5 High 32 tok/s Pro
GPT-4o 86 tok/s Pro
Kimi K2 194 tok/s Pro
GPT OSS 120B 445 tok/s Pro
Claude Sonnet 4.5 35 tok/s Pro
2000 character limit reached

Viability of general relativity and modified gravity cosmologies using high-redshift cosmic probes (2505.19960v1)

Published 26 May 2025 in astro-ph.CO

Abstract: Several models based on General Relativity and Modified Gravity aim to reproduce the observed universe with precision comparable to the standard flat-$\Lambda$CDM model. In this study, we investigate the consistency of some of these models with current high-redshift cosmic data, assessing their ability to simultaneously describe both the background expansion and matter clustering, using measurements of the Hubble parameter $H(z)$, the luminosity distance $D_L(z)$, and the growth rate of structures $f\sigma_8$ through parametric and non-parametric methods. Our results indicate that background observables alone offer limited capacity to distinguish between models, while the inclusion of growth of structures data proves useful in revealing deviations, even if small. An $F(Q)$ model, the non-flat $\Lambda$CDM and the $\omega$CDM emerge as alternatives well supported by data, closely matching the growth data and showing performance comparable to $\Lambda$CDM, as revealed by the Akaike Information Criterion. In contrast, $F(R)$ models are strongly disfavored compared to $\Lambda$CDM and $F(Q)$. These analyses illustrate the usefulness of both parametric and non-parametric approaches to explore the observational viability of alternative cosmological models.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.