Comparison of Cross-Correlation Methods for Line Intensity Mapping

TL;DR

This paper compares three cross-correlation methods for line intensity mapping, demonstrating their effectiveness in detecting the [CII] line at high redshifts and showing how combining them enhances detection significance and constraints.

Contribution

The study evaluates and compares three cross-correlation techniques for LIM, highlighting their individual strengths and the benefits of combining them for improved detection and modeling.

Findings

Detection of [CII] line at redshifts 2.5-3.5 with high significance.

Cross-correlation techniques improve detection under realistic noise conditions.

Combining methods yields the strongest constraints and detection significance.

Abstract

Line intensity mapping (LIM) is a technique for producing 3D maps of the Universe by scanning the sky with a spectrometer sensitive to a range of wavelengths corresponding to the redshifted spectral lines of atoms or molecules, such as hydrogen or carbon, commonly found in galaxies and the diffuse media around them. While LIM experiments have successfully detected the 21 cm line of neutral hydrogen, other lines that reveal large-scale structure or astrophysical processes remain undetected. Many LIM experiments are in development or are underway to fill this gap, but will likely suffer from contamination from systematics, like Galactic foregrounds, or noise. Cross-correlation techniques offer the smoothest route for making detections and constraining astrophysical processes in this regime. In this work, we apply three cross-correlation techniques (stacking, the conditional voxel intensity distribution (CVID), and the cross power spectrum) to simulated LIM maps produced using [CII] luminosity models for a pathfinder LIM experiment (EXCLAIM). We find that these cross-correlation techniques allow for mean detection of the target signal line ([CII]) at redshifts 2.5-3.5 at the 4.5$\sigma$, 3.9$\sigma$, and 8.4$\sigma$ level, respectively, and offer moderate constraints on the line emission model. Under a futuristic scenario with reduced noise, the techniques improve substantially, with detections at the 44.0$\sigma$, 24.6$\sigma$, and 34.3$\sigma$ levels and percent-level constraints. Each technique offers unique information, with the strongest constraints achieved by using the three techniques in combination.