Classifying LIGO Data with Neural Networks and Scaleograms

Project Goal

This project aims to detect burst gravitational waves using scaleograms and convolution neural networks.

Current Status

The model is currently only trained to detect sine-Gaussian bursts, and it does so with ~98% accuracy.

Future Plans

I’d like to train the model to classify other waveforms and also generate a larger set of training data when I have access to more computing resources.

Graduate Physics Student & Researcher

My research interests include Cosmology, High Energy Astrophysics, Gravitational Wave Physics, Computational Science, and HPC in Physics.