Variability Flagging in the WISE Preliminary Data Release

TL;DR

This paper presents a method for identifying variable sources in the WISE Preliminary Data Release, flagging nearly 460,000 candidates with significant flux variability using chi-square analysis of single-exposure measurements.

Contribution

It introduces a novel variability flagging technique based on chi-square analysis, applied to a large infrared survey catalog, with detailed discussion of its benefits and limitations.

Findings

Identified ~460,000 variable source candidates.

Demonstrated the method with example light curves of different variable types.

Discussed the effectiveness and limitations of the flagging approach.

Abstract

The Wide-field Infrared Survey Explorer Preliminary Data Release Source Catalog contains over 257 million objects. We describe the method used to flag variable source candidates in the Catalog. Using a method based on the chi- square of single-exposure flux measurements, we generated a variability flag for each object, and have identified almost 460,000 candidates sources that exhibit significant flux variability with greater than \sim 7{\sigma} confidence. We discuss the flagging method in detail and describe its benefits and limitations. We also present results from the flagging method, including example light curves of several types of variable sources including Algol-type eclipsing binaries, RR Lyr, W UMa, and a blazar candidate.