KMTNet Synoptic Survey of Southern Sky II: Data Reduction and Real-Time Transient Detection Pipeline

TL;DR

This paper introduces a comprehensive data reduction and real-time transient detection pipeline for the KMTNet Southern Sky survey, achieving high astrometric and photometric accuracy over a large sky area, and enabling prompt transient identification.

Contribution

The paper presents a new, integrated pipeline for processing KMTNet survey data, including calibration, image stacking, and real-time transient detection, validated with successful gravitational-wave follow-up.

Findings

Achieved sub-pixel astrometric accuracy (< 0.4 arcsec)

Reaching 5-sigma depth of 22-23 AB mag in BVRI bands

Demonstrated effective real-time transient detection in gravitational-wave follow-up

Abstract

We present a comprehensive pipeline developed for the image processing of the KMTNet Synoptic Survey of the Southern Sky (KS4) Data Release 1. This pipeline encompasses several key processes, including data quality assurance, astrometry, photometric zero-point (ZP) calibration, bad pixel masking, image stacking, and difference image analysis (DIA). The astrometric solutions were validated by cross-matching with the Gaia EDR3 catalog, achieving sub-pixel astrometric accuracy (< 0.4 arcsec). To ensure spatial consistency, we divided each image into multiple subsections and confirmed that astrometric accuracy was maintained even at the edges. We performed a two-stage photometric calibration. Initial ZP solutions were computed for each individual image frame using the APASS DR9 and SkyMapper DR3 catalogs. Subsequently, we corrected residual spatial variations in the stacked images using Gaia XP photometry. This procedure yielded a 5-sigma depth of 22-23 AB mag across the BVRI bands, with root-mean-square errors of approximately 0.03 mag when referenced to Gaia stars in the magnitude range of 14-19 mag. The processed KS4 images span over 4,000 deg^2 of the southern sky, providing reference images suitable for DIA. This publicly available pipeline also supports real-time processing of newly acquired images, enabling prompt transient detection. We demonstrate its effectiveness through successful applications in gravitational-wave follow-up observations.