Archiving multi-epoch data and the discovery of variables in the near infrared

TL;DR

This paper introduces a new database and pipeline for time series photometry in near-infrared surveys, enabling efficient discovery of variable objects in large datasets.

Contribution

The paper presents a novel database design and processing pipeline that improves the detection and analysis of variable objects in multi-epoch near-infrared survey data.

Findings

0.6% of stars are variable with .015 mag amplitude

2.3% of galaxies are variable with .015 mag amplitude

Effective identification of rare variable objects in large survey datasets

Abstract

We present a description of the design and usage of a new synoptic pipeline and database model for time series photometry in the VISTA Data Flow System (VDFS). All UKIRT-WFCAM data and most of the VISTA main survey data will be processed and archived by the VDFS. Much of these data are multi-epoch, useful for finding moving and variable objects. Our new database design allows the users to easily find rare objects of these types amongst the huge volume of data being produced by modern survey telescopes. Its effectiveness is demonstrated through examples using Data Release 5 of the UKIDSS Deep Extragalactic Survey (DXS) and the WFCAM standard star data. The synoptic pipeline provides additional quality control and calibration to these data in the process of generating accurate light-curves. We find that 0.6+-0.1% of stars and 2.3+-0.6% of galaxies in the UKIDSS-DXS with K<15 mag are variable with amplitudes \Delta K>0.015 mag