Dark energy is believed to be responsible for the acceleration of the Universe. In this paper, we reconstruct the dark energy scalar field potential V(ϕ) using the Hubble parameter H(z) through Gaussian process analysis. Our goal is to investigate dark energy using various H(z) data sets and priors. We find that the selection of the prior and the H(z) data set significantly affects the reconstructed V(ϕ). We compare two models, Power Law and Free Field, to the reconstructed V(ϕ) by computing the reduced chi-square. The results suggest that the models are generally in agreement with the reconstructed potential within a 3σ confidence interval, except in the case of Observational H(z) data with the Planck 18 prior. Additionally, we simulate H(z) data to measure the effect of increasing the number of data points on the accuracy of reconstructed V(ϕ). We find that doubling the number of H(z) data points can improve the accuracy rate of reconstructed V(ϕ) by 5%–30%.

中文翻译：

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高斯过程重建暗能量标量场势


暗能量被认为是宇宙加速的原因。在本文中，我们通过高斯过程分析，使用哈勃参数H(z)重建暗能量标量场势V(phi)。我们的目标是使用各种 H(z) 数据集和先​​验来研究暗能量。我们发现先验数据集和 H(z) 数据集的选择显着影响重建的 V(phi)。我们通过计算简化的卡方将幂律和自由场这两个模型与重建的 V(phi) 进行比较。结果表明，除了具有 Planck 18 先验的观测 H(z) 数据的情况外，模型通常与 3σ 置信区间内的重建势一致。此外，我们模拟 H(z) 数据来测量增加数据点数量对重建 V(phi) 准确性的影响。我们发现，将 H(z) 数据点数量加倍可以将重建 V(phi) 的准确率提高 5%–30%。