Abstract
Cosipy is a custom-written data analysis Python package for the upcoming Compton Spectrometer and Imager (COSI) - a gamma-ray space telescope set for satelitte launch in the near-future. The Cosipy data processing library will provide data retrieval and analysis functionality to astrophysicists, allowing them to make observations of nucleosynthesis, black hole accretion, and other gamma-ray band events using the COSI instrument’s observational dataset. This Independent Study represents a theoretical investigation into imaging algorithms, libraries and physical theory for Compton space telescopes in general and the COSI in particular. Theoretical work is done to explain de-convolution algorithms and the principle of image recovery from raw image datasets. Experimental work is done with the Compton experiment, to contextualize the raw COSI detector dataset and understand the Compton data space. Engineering work is done to accelerate the Cosipy library and meet performance require- ments for the astrophysics community; in particular, I contribute memory and compute time optimizations to two different Cosipy modules.
Advisor
DeGroot, Laura
Department
Computer Science; Physics
Recommended Citation
Thomas, Augustus R., "Exploring Optimizations in the COSI High-Level Data Analysis Library" (2025). Senior Independent Study Theses. Paper 11376.
https://openworks.wooster.edu/independentstudy/11376
Disciplines
Astrophysics and Astronomy | Software Engineering | Theory and Algorithms
Keywords
Deconvolution, Software Acceleration, Python, Gamma ray bursts
Publication Date
2025
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2025 Augustus R. Thomas