发表机构
Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal University; School of Physics and Astronomy, Beijing Normal University; National Centre for Nuclear Research（北京师范大学天文与天体物理前沿研究所; 北京师范大学物理与天文学院; 国家核研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文利用DESI DR2 BAO数据与三种机器学习方法约束哈勃常数，结果与普朗克测量在1σ内一致，表明数据驱动方法有潜力缓解哈勃常数危机。
AI 中文摘要
现代宇宙学中一个尚未解决的关键问题是哈勃常数危机，它源于基于近邻观测确定的哈勃常数（$H_0$）与标准$\Lambda$CDM范式下早期宇宙数据所预测的值之间的不一致。最近的进展已将新的暗能量光谱仪器（DESI）巡天确定为探测晚期宇宙学的一个有前景的观测工具。在本文中，我们使用最新的DESI DR2重子声学振荡（BAO）测量，结合非参数重建的Ia型超新星和宇宙学计时器数据，利用三种互补的机器学习方法：高斯过程回归（GPR）、人工神经网络（ANNs）和长短期记忆（LSTM）网络来约束哈勃常数。我们在DESI DR2示踪剂的有效红移处对$H_0$进行了单独和联合约束，得到$H_0 = 61.8 \pm 5.3\\,\mathrm{km\\,s^{-1}\\\\,Mpc^{-1}}$（GPR），$66.3 \pm 5.2\\,\mathrm{km\\,s^{-1}\\\\,Mpc^{-1}}$（ANN），以及$68.7 \pm 6.0\\,\mathrm{km\\,s^{-1}\\\\,Mpc^{-1}}$（LSTM）。我们的结果与最近的普朗克测量在$1\sigma$内表现出极好的一致性，这凸显了数据驱动、模型无关的方法在解决哈勃常数危机方面的潜力。最后，我们进一步测试了我们的结果对DESI数据中潜在系统误差的敏感性，强调了理解BAO巡天中系统不确定性重要性。
英文摘要
One of the key unresolved questions in modern cosmology is the Hubble tension, which arises from the inconsistency between determinations of the Hubble constant ($H_0$) based on nearby observations and those predicted by early-Universe data under the standard $Λ$CDM paradigm. Recent advances have identified the new Dark Energy Spectroscopic Instrument (DESI) survey as a promising observational tool for probing late-time cosmology. In this paper, we use the latest DESI DR2 baryon acoustic oscillation (BAO) measurements, combined with nonparametrically reconstructed Type Ia supernovae and cosmic chronometer data, to constrain the Hubble constant using three complementary machine learning methodologies: Gaussian process regression (GPR), artificial neural networks (ANNs), and long short-term memory (LSTM) networks. We perform individual and joint constraints on $H_0$ at the effective redshifts of DESI DR2 tracers, yielding $H_0 = 61.8 \pm 5.3\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (GPR), $66.3 \pm 5.2\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (ANN), and $68.7 \pm 6.0\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$ (LSTM). Our results exhibit excellent agreement with the recent Planck measurements within $1σ$, which highlight the potential of data-driven, model-independent methods to address the Hubble tension. Finally, we further test the sensitivity of our results to potential systematics in the DESI data, emphasizing the importance of understanding systematic uncertainties in BAO surveys.
Comments17 pages, 9 figures, 4 tables. Published in The Astrophysical Journal Supplement Series
Journal refThe Astrophysical Journal Supplement Series, 285:63 (2026)
