TRIPP: A General Purpose Data Pipeline for Astronomical Image Processing
Alex Thomas, Natalie LeBaron, Luca Angeleri, Samuel Whitebook, Rachel, Darlinger, Phillip Morgan, Varun Iyer, Prerana Kottapalli, Enda Mao, Jasper, Webb, Dharv Patel, Kyle Lam, Kelvin Yip, Michael McDonald, Robby Odum, Cole, Slenkovich, Yael Brynjegard-Bialik, Nicole Efstathiu

TL;DR
TRIPP is a versatile, real-time data pipeline designed for detecting transient and variable astronomical sources using difference imaging and light curve analysis, demonstrated on supernova and SETI data.
Contribution
The paper introduces TRIPP, a general-purpose, rapid analysis pipeline for astronomical transient detection, combining difference imaging and light curve techniques, with validation on supernova and SETI data.
Findings
Successfully detected SN2023ixf in near-real time.
Validated TRIPP's results against published supernova photometry.
Demonstrated TRIPP's capability to identify SETI optical signals.
Abstract
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.
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Taxonomy
TopicsAstronomical Observations and Instrumentation · Astronomy and Astrophysical Research
