P-31 LIGO Classification with Machine Learning
Abstract
Due to the popularity of probabilistic approaches to solving classification problems in interdisciplinary research environments, I propose to work on classifying LIGO data using a machine learning classification approach. I will be able to use training and testing datasets to classify whether the data contains gravitational wave signals, which will help the physicists at LIGO perform and analyze their experiments.
Start Date
2-28-2020 2:30 PM
P-31 LIGO Classification with Machine Learning
Due to the popularity of probabilistic approaches to solving classification problems in interdisciplinary research environments, I propose to work on classifying LIGO data using a machine learning classification approach. I will be able to use training and testing datasets to classify whether the data contains gravitational wave signals, which will help the physicists at LIGO perform and analyze their experiments.
Acknowledgments
Mentor: Tiffany Summerscales, Physics