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

Ting Tan, Huanyuan Shan, Eric Armengaud

First listed 2025-12-22 | Last updated 2025-12-22

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.

Short digest

Forecasting with CSST’s UV slitless GU grism (255–410 nm), this paper shows that 3D Lyα forest clustering at 1.1 < z < 2.0 can be recovered from Lyα auto-correlation plus cross-correlations with quasars and Euclid-like ELGs. Anisotropic redshift-space fits at z_eff = 1.59 (1.58 for ELGs) yield Lyα bias parameters at 10–30% precision, depending on tracer-bias priors. Combining auto- and cross-correlations gives a marginal BAO detection of 2.5σ with QSOs (3.7σ with ELGs), constraining the isotropic BAO scale to ~10% (~7%). This would provide the first 3D low‑z Lyα forest characterization and a complementary BAO anchor below z = 2, linking galaxy surveys to high‑z Lyα results.

Key figures to inspect

• Figure 1 — Redshift distributions of the mock QSO and ELG tracers: verify the overlap within 1.1 < z < 2.0 that enables Lyα–QSO and Lyα–ELG cross-correlations and check the GU-band selection mapping Lyα into 255–410 nm.
• Figure 2 — Mean transmitted flux versus redshift: confirm that the LyaCoLoRe-based mocks match HST/COS low‑z measurements and DESI high‑z trends, validating the extrapolated low‑z transmission used for clustering forecasts.
• Figure 3 — Lyα bias evolution and 1D flux power: inspect how the mock-measured Lyα bias in three z bins compares to the ACCEL2 simulation fit and to eBOSS/DESI measurements; in the lower panel, check that the mock 1D power amplitude and scale-dependence are consistent with HST/COS and DESI benchmarks.
• Figure 4 — Example transmission skewer with/without resolution smoothing: see how CSST’s low resolving power (R ~ 200–250) suppresses small-scale structure along sightlines, informing expectations for correlation measurements and BAO recovery.