Machine Learning and Gravitational Wave Astronomy

Lead Research Organisation: CARDIFF UNIVERSITY
Department Name: School of Physics and Astronomy

Abstract

In recent years machine learning techniques such as deep neural networks have shown tremendous promise in applications such a image classification. This project will explore machine learning applications in the new field of gravitational-wave astronomy, both for signal detection and background noise classification.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
ST/P006779/1 30/09/2017 29/09/2024
1946053 Studentship ST/P006779/1 30/09/2017 29/09/2021 Vasileios Skliris
 
Description Application for long term attachment costs for students starting in 2017 academic year.
Amount £4,413 (GBP)
Funding ID ST/P006779/1 
Organisation Science and Technologies Facilities Council (STFC) 
Sector Public
Country United Kingdom
Start 05/2018 
End 06/2020
 
Title Machine Learning Data generator tool for gravitational waves 
Description This is a python package that generates datasets with gravitational waves and noise. It also simplifies the creation of machine learning models , their training and their testings to extract scientific information. 
Type Of Material Data handling & control 
Year Produced 2019 
Provided To Others? Yes  
Impact Me and new students can be relieved from the time consuming and complicated procedure of making datasets from scratch. New PhD students are using my tool for similar research. 
URL https://github.com/VasSkliris/mly
 
Description LIGO Scientific Collaboration 
Organisation LIGO Scientific Collaboration
Country United States 
Sector Academic/University 
PI Contribution As my work is related to gravitational waves, I am part of LIGO Scientific collaboration. My contribution is to make machine learning algorithm that helps distinguish signals from noise in the detectors.
Collaborator Contribution LIGO offers me access to their data that are not open in public, also I get involved in various projects that need attention.
Impact My work combines computer science, signal processing and astrophysics.
Start Year 2017