We present the TRansient Image Processing Pipeline (TRIPP), a transient and variable source detection pipeline that employs both difference imaging and light curve analysis techniques for astronomical data. Additionally, we demonstrate TRIPP's rapid analysis capability by detecting transient candidates in near-real time. TRIPP was tested using image data of the supernova SN2023ixf and from the Local Galactic Transient Survey (LGTS, Thomas et al. (2025)) collected by the Las Cumbres Observatory's (LCO) network of 0.4 m telescopes. To verify the methods employed by TRIPP, we compare our results to published findings on the photometry of SN2023ixf. Additionally, we report the ability of TRIPP to detect transient signals from optical Search for Extra Terrestrial Intelligence (SETI) sources.
@article{arxiv.2501.18142,
title = {TRIPP: A General Purpose Data Pipeline for Astronomical Image Processing},
author = {Alex Thomas and Natalie LeBaron and Luca Angeleri and Samuel Whitebook and Rachel Darlinger and Phillip Morgan and Varun Iyer and Prerana Kottapalli and Enda Mao and Jasper Webb and Dharv Patel and Kyle Lam and Kelvin Yip and Michael McDonald and Robby Odum and Cole Slenkovich and Yael Brynjegard-Bialik and Nicole Efstathiu and Joshua Perkins and Ryan Kuo and Audrey O'Malley and Alec Wang and Ben Fogiel and Sam Salters and Marlon Munoz and Ruiyang Wang and Natalie Kim and Lee Fowler and Philip Lubin},
journal= {arXiv preprint arXiv:2501.18142},
year = {2025}
}