Theses and Dissertations

Date of Award


Document Type


Degree Name

Master of Science (MS)



First Advisor

Soma Mukherjee

Second Advisor

Malik Rakhmanov

Third Advisor

Soumya D. Mohanty


Core collapse supernovae (CCSN) are highly anticipated sources of gravitational waves during the fourth observation run (O4). CCSN signals are weak and unmodeled and the rate of occurrence in our galaxy is very low. Because of this, they provide a greater challenge to detect than previously detected GW sources. CCSN simulations are used to test the detection pipeline in the event a CCSN is detected. CCSN GW signals are often indistinguishable from the noise sources present in GW data. We present a multi layered signal enhancement pipeline which we have applied Machine Learning (ML) techniques. We have used a Convolutional Neural Network (CNN) to train on 10 different simulated CCSN signals, and then tested the preformance of our pipeline on rotating CCSN signals.


Copyright 2023 Michael Gale Benjamin. All Rights Reserved.

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