A Method for Individual Source Brightness Estimation in Single- and Multi-band Data

TL;DR

This paper introduces a Bayesian method for accurately estimating individual source fluxes in sky maps, extending to multi-band data to improve source classification and reduce biases.

Contribution

It presents a novel Bayesian approach that reliably extracts properties of individual sources in single- and multi-band data, accounting for spectral behavior and prior correlations.

Findings

Method effectively extracts source fluxes in simulated data.

Multi-band extension improves source classification accuracy.

Proper prior treatment reduces estimation biases.

Abstract

We present a method of reliably extracting the flux of individual sources from sky maps in the presence of noise and a source population in which number counts are a steeply falling function of flux. The method is an extension of a standard Bayesian procedure in the millimeter/submillimeter literature. As in the standard method, the prior applied to source flux measurements is derived from an estimate of the source counts as a function of flux, dN/dS. The key feature of the new method is that it enables reliable extraction of properties of individual sources, which previous methods in the literature do not. We first present the method for extracting individual source fluxes from data in a single observing band, then we extend the method to multiple bands, including prior information about the spectral behavior of the source population(s). The multi-band estimation technique is particularly relevant for classifying individual sources into populations according to their spectral behavior. We find that proper treatment of the correlated prior information between observing bands is key to avoiding significant biases in estimations of multi-band fluxes and spectral behavior, biases which lead to significant numbers of misclassified sources. We test the single- and multi-band versions of the method using simulated observations with observing parameters similar to that of the South Pole Telescope data used in Vieira, et al. (2010).