标题： Lya2pcf：一种高效流程，用于估计莱曼-$α$谱线森林的两点和三点相关函数 显示英文标题

标题： Lya2pcf: an efficient pipeline to estimate two- and three-point correlation functions of the Lyman-$α$ forest

摘要： 通过研究宇宙中的物质分布，利用Lyman-$\alpha$森林使我们能够约束高红移区域的小尺度物理现象。 光谱类星体调查正在生成越来越大的数据集，这需要高效的算法来计算相关函数。 此外，基于Lyman-$\alpha$森林的宇宙学分析可以通过结合高阶统计量与传统的两点相关性而显著受益。 在这项工作中，我们介绍了Lya2pcf，这是一个设计用于使用Lyman-$\alpha$森林数据计算三维两点和三点相关函数的流程。 该代码实现了当前光谱调查中广泛使用的标准算法，用于计算两点相关函数及其畸变矩阵、协方差矩阵；并且自然地将两点估计器扩展到三点相关性。 由于GPU优化，与广泛使用的PICCA代码相比，Lya2pcf在计算两点相关函数及其畸变矩阵时实现了计算时间的显著减少。 我们将Lya2pcf应用于斯隆数字天空调查（SDSS）第十六数据发布（DR16）的数据和暗能量光谱仪器第五年（DESI Y5）模拟数据集，展示了整体性能的提升，尤其是在GPU上。 我们展示了在大光谱样本上所有可能三角形的各向异性三点相关函数的首次测量，其尺度高达80 Mpc/h。 该估计器的快速计算和产生的信噪比——对于许多三角形配置来说高于一——证明了将三点统计量纳入未来宇宙学推断分析的可行性，特别是在预期有更大数据集的第四阶段光谱调查中。 显示英文摘要

摘要： Studying the matter distribution in the universe through the Lyman-$\alpha$ forest allows us to constrain small-scale physics in the high-redshift regime. Spectroscopic quasar surveys are generating increasingly large datasets that require efficient algorithms to compute correlation functions. Moreover, cosmological analyses based on Lyman-$\alpha$ forests can significantly benefit from incorporating higher-order statistics alongside traditional two-point correlations. In this work, we present Lya2pcf, a pipeline designed to compute three-dimensional two-point and three-point correlation functions using Lyman-$\alpha$ forest data. The code implements standard algorithms widely used in current spectroscopic surveys for computing the two-point correlation function with its distortion matrix, covariance matrices; and it naturally extends the two-point estimator to three-point correlations. Thanks to GPU optimization, Lya2pcf achieves a substantial reduction in computational time for both the two-point correlation function and its distortion matrix when compared to the widely used PICCA code. We apply Lya2pcf to data from the Sloan Digital Sky Survey (SDSS) sixteenth data release (DR16) and a Dark Energy Spectroscopic Instrument Year-5 (DESI Y5) mock dataset, demonstrating overall performance gains over PICCA, especially on GPUs. We show the first measurement of the anisotropic three-point correlation function on a large spectroscopic sample for all possible triangles with scales up to 80 Mpc/h. The estimator's fast computation and the resulting signal-to-noise ratio -- above one for many triangle configurations -- demonstrate the viability of incorporating three-point statistics into future cosmological inference analyses, particularly with the larger datasets expected from Stage IV spectroscopic surveys.