Abstract

This paper constraints dynamic dark energy equation of state (EoS) parameters using the type Ia supernovae from Union 2.1 dataset. The paper also discusses the dependency of dynamic dark energy EoS parameters on the chosen or assumed value of the Hubble Constant. To understand the correlation between the Hubble Constant values and measured dynamic dark energy EoS parameters, we used recent surveys being done through various techniques such as cosmic microwave background studies, gravitational waves, baryonic acoustic oscillations and standard candles to set values for different Hubble Constant values as fixed parameters with CPL and WCDM models. Then we applied trust region reflective (TRF) and dog leg (dogbox) algorithms to fit dark energy density parameter and dynamic dark energy EoS parameters. We found a significant negative correlation between the fixed Hubble Constant parameter and measured EoS parameter, \({{w}_{0}}\). Then we used two best fit Hubble Constant values (70 and 69.18474) km s^–1 Mpc^–1 based on Chi-square test to test more dark energy EoS parameters like: JBP, BA, PADE-I, PADE-II, and LH4 models and compared the results with \(\Lambda \)-CDM with constant \({{w}_{{{\text{de}}}}} = - 1\), WCDM and CPL models. We conclude that flat \(\Lambda \)‑CDM and WCDM models clearly provide best results while using the BIC criteria as it severely penalizes the use of extra parameters. However, the dependency of EoS parameters on Hubble Constant value and the increasing tension in the measurement of Hubble Constant values using different techniques warrants further investigation into looking for optimal dynamic dark energy EoS models to optimally model the relation between the expansion rate and evolution of dark energy in our universe.

中文翻译：

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动态暗能量状态方程（EoS）和哈勃常数分析，使用来自Union 2.1数据集的Ia型超新星

摘要

本文使用Union 2.1数据集中的Ia型超新星约束动态暗能量状态方程（EoS）参数。本文还讨论了动态暗能量EoS参数对哈勃常数的选定值或假定值的依赖性。为了了解哈勃常数值与测得的动态暗能量EoS参数之间的相关性，我们使用了通过各种技术（例如宇宙微波背景研究，引力波，重音声振荡和标准蜡烛）进行的最新调查来设置不同的哈勃常数值作为CPL和WCDM模型的固定参数。然后，我们应用信任区域反射（TRF）和狗腿（dogbox）算法来拟合暗能量密度参数和动态暗能量EoS参数。\（{{w} _ {0}} \）。然后，我们基于卡方检验，使用了两个最合适的哈勃常数值（70和69.18474）km s ^–1 Mpc ^–1来测试更多的暗能量EoS参数，例如：JBP，BA，PADE-I，PADE-II和LH4模型，并将结果与\（\ Lambda \）- CDM和常数\（{{{w} _ {{{\ text {de}}}}}} =-1 \），WCDM和CPL模型进行比较。我们得出结论，平\（\ Lambda \）‑CDM和WCDM模型在使用BIC标准的同时显然会提供最佳结果，因为它严重惩罚了额外参数的使用。然而，EoS参数对哈勃常数值的依赖性以及使用不同技术测量哈勃常数值时不断增加的张力值得进一步研究，以寻找最佳动态暗能量EoS模型，以最佳地模拟膨胀率与暗演化之间的关系。我们宇宙中的能量。