An analytic approach to number counts of weak-lensing peak detections

TL;DR

This paper presents an analytic method based on Gaussian random fields to predict weak-lensing peak counts, accounting for noise and spurious detections, and compares it with simulations.

Contribution

It introduces a new analytic approach to predict weak-lensing peak counts that accounts for noise and spurious detections, validated against simulations.

Findings

Peak counts are dominated by spurious detections up to S/N of 3-5.

Most filters yield few detections above this threshold.

An optimized filter can increase detections by an order of magnitude.

Abstract

We develop and apply an analytic method to predict peak counts in weak-lensing surveys. It is based on the theory of Gaussian random fields and suitable to quantify the level of spurious detections caused by chance projections of large-scale structures as well as the shape and shot noise contributed by the background galaxies. We compare our method to peak counts obtained from numerical ray-tracing simulations and find good agreement at the expected level. The number of peak detections depends substantially on the shape and size of the filter applied to the gravitational shear field. Our main results are that weak-lensing peak counts are dominated by spurious detections up to signal-to-noise ratios of 3--5 and that most filters yield only a few detections per square degree above this level, while a filter optimised for suppressing large-scale structure noise returns up to an order of magnitude more.