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

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.

Figures (14)

• Figure 1: An example of a KS4 0001 field image observed from the CTIO observatory, illustrating the four-CCD mosaic (labeled K, M, T, and N), each measuring 9216 $\times$ 9232 pixels at a scale of 0.4 arcsec pixel$^{-1}$. Notably, the N-chip is shown subdivided into eight "readout port images," each read out from a separate port. The FOV of each chip is approximately 1.024 deg $\times$ 1.026 deg, with inter-chip gaps of 184 arcsec (horizontal, east–west) and 373 arcsec (vertical, south–north). An arrow in the bottom-right corner indicates the north and east orientation.
• Figure 2: Flowchart of the data reduction and transient detection pipeline after image acquisition. (a) Preprocessing steps performed by the KASI pipeline 2013PKAS...28....1K. (b) KS4 DR1 reference image reduction sequence. (c) Difference image analysis (DIA) applied to newly obtained ToO images, which are reduced using the same procedures as the KS4 images and subsequently subtracted from the reference frame.
• Figure 3: Stellar photometry from the COSMOS field is used to calibrate the KMTNet $I$-band. The $x$-axis shows the $(i - z)$ color from the SMSS catalog, and the $y$-axis shows the difference between the KMTNet $I$-band magnitude and the SMSS $i$-band magnitude. The KMTNet $I$-band magnitudes are calibrated to the Johnson-Cousins system using known transformations in the COSMOS field. The distribution consists of the photometric reference stars (blue points) after the rejection of outliers (gray crosses), and binned statistics (white squares) representing the median and 1$\sigma$ dispersion of the reference stars for each 0.1 mag interval in $(i - z)$. The red line represents a robust linear fit to the data points.
• Figure 4: Photometric ZP distribution of KS4 DR1 chip images before (red) and after (blue) the ZP scaling process. Individual points represent the mean ZP for each of the 32 readout ports averaged over 979 image sets; shaded regions indicate the 1$\sigma$ standard deviation of these measurements. The pronounced scatter before the scaling process is primarily attributed to systematic ZP offsets between the different observation sites. The four panels show the distribution for the $B$, $V$, $R$, and $I$ bands from left to right.
• Figure 5: Example cutout images illustrating the primary contaminating features flagged in the KS4 bad pixel mask. For each source type, a science image snippet (grayscale) and the corresponding mask region (binary) are shown. From left to right: cosmic rays, cross-talk artifacts, pixel bleeding from saturated stars, CCD bad pixels at the edges, and defective readout ports of the CTIO N-chip CCD. Due to their elongated nature, pixel bleeding features are displayed in an extended vertical layout.