Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function
Forecasting constraints on the mean free path of ionizing photons at z ≥ 5.4 from the Lyman-α forest flux autocorrelation function
复制标题
根据 Lyman-α 森林通量自相关函数预测 z ≤ 5.4 处电离光子平均自由程的约束
DOI：
10.1093/mnras/stad701
复制
发表时间：
2023
影响因子：
4.8
通讯作者：
Oñorbe, Jose
中科院分区：
文献类型：
--
作者：
Wolfson, Molly;Hennawi, Joseph F.;Davies, Frederick B.;Oñorbe, Jose
莱曼-α（Ly α）森林向高Z类星体传输的涨落部分来源于紫外背景的空间涨落，其能级由电离光子的平均自由程（λmfp）决定。Ly α森林通量的自相关函数表征了传输波动的强度和规模，因此对λmfp敏感。最近的测量表明λmfpatz> 5.0的快速演化，这将在自相关函数的演化中留下签名。对于这种预测，我们模拟Ly α森林数据，其性质类似于XQR-30扩展数据集，在5.4 ≤z≤ 6.0。在每一次，我们调查了100个模拟数据集和一个理想的情况下，模拟数据匹配自相关函数的模型值。对于λmfp= 9.0 cMpc的理想数据，在z = 6.0时，我们恢复了cMpc。这种精确度可以与直接测量类星体光谱叠加后超过莱曼极限的λ mfp相媲美。假设的高分辨率数据会导致误差线在所有z上的减少。在这项工作中，自相关函数的模拟值的分布对于高z是高度非高斯的，这应该提醒使用高zLy α森林的其他统计量的工作不要做出这种假设。我们使用严格的统计方法来通过推理测试，但是未来对非高斯方法的研究将实现更高精度的测量。
Fluctuations in Lyman-α (Ly α) forest transmission towards high-zquasars are partially sourced from spatial fluctuations in the ultraviolet background, the level of which are set by the mean free path of ionizing photons (λmfp). The autocorrelation function of Ly α forest flux characterizes the strength and scale of transmission fluctuations and, as we show, is thus sensitive to λmfp. Recent measurements atz∼ 6 suggest a rapid evolution of λmfpatz> 5.0 which would leave a signature in the evolution of the autocorrelation function. For this forecast, we model mock Ly α forest data with properties similar to the XQR-30 extended data set at 5.4 ≤z≤ 6.0. At eachz, we investigate 100 mock data sets and an ideal case where mock data matches model values of the autocorrelation function. For ideal data with λmfp= 9.0 cMpc atz= 6.0, we recovercMpc. This precision is comparable to direct measurements of λmfpfrom the stacking of quasar spectra beyond the Lyman limit. Hypothetical high-resolution data leads to areduction in the error bars over allz. The distribution of mock values of the autocorrelation function in this work is highly non-Gaussian for high-z, which should caution work with other statistics of the high-zLy α forest against making this assumption. We use a rigorous statistical method to pass an inference test, however future work on non-Gaussian methods will enable higher precision measurements.