Filtering out large-scale noise for cluster weak-lensing mass estimation

TL;DR

This paper introduces a Wiener filtering method to reduce noise correlations in weak-lensing magnification data, improving galaxy cluster mass estimates, especially for future deeper surveys.

Contribution

The paper presents a novel filtering technique that significantly reduces noise correlations in cluster magnification measurements, enhancing mass estimation accuracy.

Findings

Filtering reduces noise correlation between radial bins.

Mass estimates are consistent with previous methods.

Method is promising for future deeper surveys.

Abstract

We present a new method for estimating galaxy cluster masses using weak-lensing magnification. The effect of weak-lensing magnification introduces a correlation between the position of foreground galaxy clusters and the density of background sources. Therefore, cluster masses can be inferred through observations of these correlations. In this work, we introduce a method that allows us to considerably reduce noise correlations between different radial bins of the cluster magnification signal via a Wiener filtering of our observed magnification field on large scales. This method can reduce the uncertainty on the estimated galaxy cluster mass and it can also be applied to cluster mass estimation for weak-lensing shear. The method was applied to Hyper-Suprime Cam galaxies and CAMIRA clusters detected within the Hyper-Suprime Cam survey (HSC). With HSC data, we find that our filtering method significantly reduces the correlation of noise between radial magnification bins. The estimated cluster mass is consistent between the filtered and unfiltered methods, with similar errors between the two methods as our current measurement errors contain significant contributions from the irreducible shot-noise. For deeper surveys, the effects of shot noise will be less important and this method will lead to greater improvements on the estimated cluster mass.