Low-redshift 3D Lyman-α Forest Correlations with China Space Station Telescope

TL;DR

This work investigates the feasibility of measuring low-redshift ($1.1<z<2.0$) 3D Ly$\alpha$ forest clustering with the China Space Station Telescope (CSST) by building end-to-end mock datasets (QSOs, ELGs, and Ly$\alpha$ transmission) and applying an anisotropic redshift-space clustering model. Using CSST-like mocks, the authors forecast Ly$\alpha$ bias and redshift-space distortion parameters at $z_{\rm eff}\approx1.6$, and evaluate BAO detectability from Ly$\alpha$ auto- and cross-correlations with QSOs and ELGs; they find a marginal $2.5\sigma$ BAO detection from Ly$\alpha$–QSO and a $3.7\sigma$ detection from Ly$\alpha$–ELG cross-correlations, with isotropic BAO scale precision around $10\%$ (QSO) or $7\%$ (ELG). The results indicate that CSST can provide the first 3D characterization of the low-redshift Ly$\alpha$ forest and offer a complementary BAO probe to link galaxy surveys with high-redshift Ly$\alpha$ studies, while highlighting the need to address systematics such as DLAs, metals, and quasar redshift errors. Overall, the study demonstrates CSST's potential to illuminate IGM properties and cosmic expansion during the critical transition to dark-energy domination. $z_{ m eff}$ values and dilation parameters $\alpha_{\parallel},\alpha_{\perp}$ and $A_{\rm BAO}$ are reported within a Bayesian framework, enabling precise forecasts for future UV-slitless surveys.

Abstract

While the Lyman-$α$ (Ly$α$) forest traces the large-scale matter distribution over a wide range of redshift, its three-dimensional (3D) clustering at $z < 2$ has not yet been measured. We investigate the prospects for measuring low-redshift Ly$α$ correlations with the UV slitless spectroscopic instrument of the China Space Station Telescope (CSST). We construct mock CSST quasar spectra that reproduce the expected survey depth, spectral resolution and noise properties, and derive Ly$α$ auto-correlation functions and cross-correlations with quasars (QSO) and emission-line galaxies (ELG) in the range $1.1 < z < 2.0$. We then interpret these three-dimensional correlation functions with a standard anisotropic redshift-space clustering model and obtain forecast constraints on the Ly$α$ and tracer parameters. At an effective redshift $z_{\rm eff}=1.59$ (1.58 for ELGs), the Ly$α$ bias parameters will be measured with a 10-30\% precision, depending on priors on other tracer's biases. We also forecast a marginal $2.5σ$ ($3.7σ$) detection of the BAO feature, corresponding to a $\sim$10\% (7\%) constraint on the isotropic BAO scale, from the combination of Ly$α$ auto- and Ly$α$-QSO (ELG) cross-correlations. These results show that CSST can provide the first three-dimensional characterization of the low-redshift Ly$α$ forest and a complementary Ly$α$-based BAO measurement at $z < 2$, helping to link galaxy clustering surveys with high-redshift Ly$α$ forest studies.

Figures (6)

• Figure 1: Redshift distribution of quasars ($1.1<z_{\rm{QSO}}<2.2$) and ELGs ($1.0<z_{\rm{ELG}}<1.9$) used in our mock, compared to QSO luminosity function (QLF) predictions for magnitude limit $r < 23$.
• Figure 2: Mean transmitted flux $\langle F(z) \rangle$ as a function of redshift in our LyaCoLoRe mocks (solid curve), obtained by averaging the Ly$\alpha$ transmission in narrow redshift slices. The hollow symbols show HST measurements (without strong absorption systems) from kirkman2007continuous, and the solid points indicate the latest measurements from DESI at high redshift turner2024new.
• Figure 3: Top: Redshift evolution of the Ly$\alpha$ forest bias. Red circles show the ACCEL2 hydrodynamical simulation results chabanier2024accel2, more precisely from the fit to the ACCL2_L160R25 box. The red dashed curve is a quadratic fit. Blue squares with error bars are the Ly$\alpha$ biases measured from our simulated CSST transmission field in three redshift bins. Orange and green squares show the measurements from DESI DR2 ($z_{eff}=2.33$) and eBOSS DR14 ($z_{eff}=2.19$ and $2.49$, table B1 in de2019baryon assuming no correlations between bias parameters) respectively. Bottom: One-dimensional flux power spectrum $P_{\rm 1D}(k)$ in the same redshift bins, compared with measurements from DESI and HST/COS.
• Figure 4: Example simulated transmission skewer, with (black, dashed) and without resolution smoothing (gray, solid).
• Figure 5: Distribution of the empirically estimated SNR values $\mathrm{SNR}_{8\text{\AA}}$ (solid line) and $\mathrm{SNR}_{14\text{\AA}}$ (dashed line) for our mock Lyman-$\alpha$ sample.