Signature flips in time-varying $$\Lambda (t)$$ cosmological models with observational data

Author:

Myrzakulov YerlanORCID,Koussour M.ORCID,Karimov M.,Rayimbaev J.ORCID

Abstract

AbstractIn this study, we investigate signature flips within the framework of cosmological models featuring a time-varying vacuum energy term $$\Lambda (t)$$ Λ ( t ) . Specifically, we consider the power-law form of $$\Lambda =\alpha H^n$$ Λ = α H n , where $$\alpha $$ α and n are constants. To constrain the model parameters, we use the MCMC technique, allowing for effective exploration of the model’s parameters. We apply this approach to analyze 31 points of observational Hubble Data (OHD), 1048 points from the Pantheon data, and additional CMB data. We consider three scenarios: when n is a free parameter (Case I), when $$n=0$$ n = 0 (Case II), and when $$n=1$$ n = 1 (Case III). In our analysis across all three cases, we observe that our model portrays the universe’s evolution from a matter-dominated decelerated epoch to an accelerated epoch, as indicated by the corresponding deceleration parameter. In addition, we investigate the physical behavior of total energy density, total EoS parameter, and jerk parameter. Our findings consistently indicate that all cosmological parameters predict an accelerated expansion phase of the universe for all three cases ($$q_0<0$$ q 0 < 0 , $$\omega _0<-\frac{1}{3}$$ ω 0 < - 1 3 , $$j_0>0$$ j 0 > 0 ). Furthermore, our analysis reveals that the Om(z) diagnostics for Cases I and III align with the quintessence region, while Case II corresponds to the $$\Lambda $$ Λ CDM model.

Funder

Ministry of Education and Science of the Republic of Kazakhstan

Publisher

Springer Science and Business Media LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3