Analysis of HAT-P-23 b, Qatar-1 b, WASP-2 b, and WASP-33 b with an Optimized EXOplanet Transit Interpretation Code

TL;DR

This paper enhances the EXOTIC code to enable faster analysis of exoplanet transit data, facilitating citizen science efforts by processing larger datasets more efficiently.

Contribution

The authors optimized the EXOTIC codebase for faster image processing and light curve fitting, achieving approximately a 5x speedup on exoplanet transit analysis.

Findings

Achieved ~5x speedup in data processing

Successfully analyzed multiple exoplanet transits

Demonstrated scalability with larger datasets

Abstract

The ability for citizen scientists to analyze image data and search for exoplanets using images from small telescopes has the potential to greatly accelerate the search for exoplanets. Recent work on the Exoplanet Transit Interpretation Code (EXOTIC) enables the generation of high-quality light curves of exoplanet transits given such image data. However, on large image datasets, the photometric analysis of the data and fitting light curves can be a time-consuming process. In this work, we first optimize portions of the EXOTIC codebase to enable faster image processing and curve fitting. Specifically, we limited repetitive computation on fitting centroids with various apertures and annuli. Moreover, this speedup is scaled linearly based on the number of FITS files. After testing on existing HAT-P-32 b data and newer HAT-P-23 b data, our best demonstration was approximately a 5x speedup, though that factor increases given a larger number of FITS files. Utilizing the accelerated code, we analyzed transits of HAT-P-23 b, Qatar-1 b, WASP-2 b, and WASP-33 b using data captured by the 16" SRO telescope operated by Boyce-Astro.