The PAU survey: Ly$\alpha$ intensity mapping forecast

TL;DR

This study assesses the feasibility of detecting extended Ly$ ext{a}$ emission from the IGM through intensity mapping and cross-correlation techniques using simulated data, finding low probabilities of detection under current conditions.

Contribution

It introduces a simulation-based forecast of Ly$ ext{a}$ intensity mapping detection prospects with PAUS, exploring different survey configurations and noise scenarios.

Findings

Detection probabilities are low (~1-5%) with current PAUS noise levels.

Deeper and wider PAUS surveys increase detection likelihood.

Realistic correlated noise reduces detection prospects further.

Abstract

In this work, we explore the application of intensity mapping to detect extended Ly$\alpha$ emission from the IGM via cross-correlation of PAUS images with Ly$\alpha$ forest data from eBOSS and DESI. Seven narrow-band (FWHM=13nm) PAUS filters have been considered, ranging from 455 to 515 nm in steps of 10 nm, which allows the observation of Ly$\alpha$ emission in a range $2.7<z<3.3$. The cross-correlation is simulated first in an area of 100 deg$^2$ (PAUS projected coverage), and second in two hypothetical scenarios: a deeper PAUS (complete up to $i_{\rm AB}<24$ instead of $i_{\rm AB}<23$, observation time x6), and an extended PAUS coverage of 225 deg$^2$ (observation time x2.25). A hydrodynamic simulation of size 400 Mpc/h is used to simulate both extended Ly$\alpha$ emission and absorption, while the foregrounds in PAUS images have been simulated using a lightcone mock catalogue. Using an optimistic estimation of uncorrelated PAUS noise, the total probability of a non-spurious detection is estimated to be 1.8\% and 4.5\% for PAUS-eBOSS and PAUS-DESI , from a run of 1000 simulated cross-correlations with different realisations of instrumental noise and quasar positions. The hypothetical PAUS scenarios increase this probability to 15.3\% (deeper PAUS) and 9.0\% (extended PAUS). With realistic correlated noise directly measured from PAUS images, these probabilities become negligible. Despite these negative results, some evidences suggest that this methodology may be more suitable to broad-band surveys.