# Point Source Detection and False Discovery Rate Control on CMB Maps

## TL;DR

This paper introduces a new statistical method for detecting point sources in Cosmic Microwave Background maps while controlling the false discovery rate, using needlet filtering, peak selection, p-value computation, and multiple testing correction.

## Contribution

The paper presents a novel procedure combining needlet filtering and FDR control for point source detection in CMB maps, applied to Planck data.

## Key findings

- Effective control of false discoveries in point source detection.
- Improved detection accuracy using needlet filtering.
- Successful application to Planck CMB maps.

## Abstract

We discuss a new procedure to search for point sources in Cosmic Microwave background maps; in particular, we aim at controlling the so-called False Discovery Rate, which is defined as the expected value of false discoveries among pixels which are labelled as contaminated by point sources. We exploit a procedure called STEM, which is based on the following four steps: 1) needlet filtering of the observed CMB maps, to improve the signal to noise ratio; 2) selection of candidate peaks, i.e., the local maxima of filtered maps; 3) computation of \emph{p-}values for local maxima; 4) implementation of the multiple testing procedure, by means of the so-called Benjamini-Hochberg method. Our procedures are also implemented on the latest release of Planck CMB maps.