标题： LRG1和低$z$ Ia型超新星数据中暗能量演化的证据 显示英文标题

标题： Evidence for Evolving Dark Energy from LRG1 and Low-$z$ SNe Ia Data

摘要： 我们提供了观察证据，表明暗能量可能随时间演化，从而挑战了标准$\Lambda$CDM 模型的核心假设。 我们的研究超越了标准$\Lambda$CDM 模型，探索了一系列动态暗能量模型。 分析显示，物质密度参数$\Omega_m$随红移变化，并且这种变化显著受到 DESI DR2 调查中 LRG1 数据点的影响。 我们发现，包括 LRG1 显著影响这些模型的预测，特别是对于$\Omega_m$和$\omega_0$，后者从$-1$变为稍高的值。 这表明 DESI DR2 数据中演变暗能量的证据是由 LRG1 数据点驱动的。 当我们排除低红移超新星数据，特别是来自 DES-SN5YR 综合数据集的数据时，模型预测恢复到$\Lambda$CDM 模型。 这种效应在GEDE模型中尤为明显，移除低红移超新星数据会导致$\Delta = 0$，从而恢复$\Lambda$CDM范式。 我们的分析确认了动态暗能量的证据是显著的，尤其是在低红移（$z \lesssim 0.3$）处。 利用DESI DR2 BAO测量、CMB距离先验和超新星数据集对$\omega(z)$和$f_{DE}(z)$的重建，进一步支持了暗能量的演化特性。 这些结果支持一种由$\omega_0>-1$、$\omega_a<0$和$\omega_0+\omega_a<-1$（Quintom-B）表征的动力学暗能量情景。模型证据的贝叶斯分析显示，包含低红移超新星数据显著增强了对JBP和Mirage等演化暗能量模型的支持，而当排除低红移数据时，模型则退化为无结论或弱支持。 显示英文摘要

摘要： We present observational evidences indicating that dark energy may be evolving with time, thereby challenging the core assumptions of the standard $\Lambda$CDM model. Our investigation extends beyond the standard $\Lambda$CDM model by exploring a range of dynamical dark energy models. The analysis reveals that the matter density parameter, $\Omega_m$, changes with redshift, and this change is significantly influenced by the LRG1 datapoint from the DESI DR2 survey. We find that including LRG1 strongly affects the predictions of these models, especially for $\Omega_m$ and $\omega_0$, with the latter shifting from $-1$ to slightly higher values. This suggests that the evidence of evolving dark energy in the DESI DR2 data is driven by the LRG1 datapoint. When we exclude low-redshift supernovae data, particularly from the DES-SN5YR compilation, the model predictions are restored to the $\Lambda$CDM paradigm. This effect is particularly evident in the GEDE model, where removing low-redshift supernovae data leads to $\Delta = 0$, effectively recovering $\Lambda$CDM paradigm. Our analysis confirms that the evidence for dynamical dark energy is substantial, particularly at low redshift ($z \lesssim 0.3$). The reconstruction of $\omega(z)$ and $f_{DE}(z)$, using a combination of DESI DR2 BAO measurements, CMB distance priors, and supernovae datasets, further supports the evolving nature dark energy. These results favor a dynamical dark-energy scenario characterized by $\omega_0>-1$, $\omega_a<0$, and $\omega_0+\omega_a<-1$ (Quintom-B). Bayesian analysis of model evidence reveals that the inclusion of low-redshift supernovae data significantly strengthens the support for evolving dark energy models such as JBP and Mirage, while models revert to inconclusive or weak support when low-redshift data are excluded.