The discovery and characterization of astrophysical transients with MeerKAT - Mlangeni, Moses (Department of Astronomy, 2025)
I present the findings of our commensal search for radio transients in the LADUMA field using SARAO Science Data Processor (SDP) UHF-band images, covering∼1 year of observations. Employing the Transient Pipeline (TraP), I identified source candidates within the LADUMA field, and applied additional filtering methods to remove false positives. I validated the use of the SDP images for transient search by comparing the SPD images with the independently reduced continuum images of the same of the data set. I conducted a multi-wavelength analysis on the potential sources, assessing radio variability through light curve inspection and radio image post-stamps. Our search spanned DES, Pan-STARRS, MeerLICHT data and the VizieR and SIMBAD database. Eight potential radio transients were selected, showing clear radio variability. The radio variability in seven of the eight sources can be attributed to interstellar scintillation. Notably, SRC213653 exhibits intrinsic variability, displaying high variability at 0.816 GHz with 13 radio detections across 41 epochs, reaching a peak flux of 1.041 ±0.043 mJy. SRC213653 is associated with the low-mass star LP 888-63, located at a distance of 23 pc from the Sun. LP 888-63 is a M-dwarf companion to a white dwarf binary system, WD 0326-273. Multiwavelength associations of LP 888-63 reveal active flaring behaviour across the electromagnetic spectrum. Optical photometry from TESS indicates a rotational period of 5.7793 ±0.5067 days. Considering the estimated radius of the star, it suggests LP 888-63 is a slow rotator, consistent with expectations for a typical low-mass star. Archive spectra from European Southern Observatory (ESO ESO-VLT-U2) show Hα emission, indicative of magnetic activity. Through this study I have shown that the SARAO SDP images can be used to detect and characterise radio transients and variables. This opens up the possibility of transient searches in near-to real time.