On the Detectability of the Moving Lens Signal in CMB Experiments

TL;DR

This paper evaluates strategies for detecting the moving-lens effect in upcoming CMB experiments, confirming high significance detection is feasible and analyzing the impact of foregrounds and other factors on detection methods.

Contribution

The study extends previous work by including realistic simulations of foregrounds and competing signals, and compares detection strategies for the moving-lens effect in CMB data.

Findings

Moving-lens effect detectable at ≥10σ with CMB-S4 and LSST.

Foregrounds like CIB and tSZ significantly impact stacking analysis.

Halo lensing and pair counts are critical factors in pairwise detection.

Abstract

Upcoming cosmic microwave background (CMB) experiments are expected to detect new signals probing interaction of CMB photons with intervening large-scale structure. Among these the moving-lens effect, the CMB temperature anisotropy induced by cosmological structures moving transverse to our line of sight, is anticipated to be measured to high significance in the near future. In this paper, we investigate two possible strategies for the detection of this signal: pairwise transverse-velocity estimation and oriented stacking. We expand on previous studies by including in the analysis realistic simulations of competing signals and foregrounds. We confirm that the moving lens effect can be detected at $\ge 10\sigma$ level by a combination of CMB-S4 and LSST surveys. We show that the limiting factors in the detection depend on the strategy: for the stacking analysis, correlated extragalactic foregrounds, namely the cosmic infrared background and thermal Sunyaev Zel'dovich effect, play the most important role. The addition of foregrounds make the signal-to-noise ratio be most influenced by large and nearby objects. As for the pairwise detection, halo lensing and pair number counts are the main issues. In light of our findings, we elaborate on possible strategies to improve the analysis approach for the moving lens detection with upcoming experiments. We also deliver to the community all the simulations and tools we developed for this study.