Detecting sources of continuous gravitation waves
Lead Research Organisation:
University of Glasgow
Department Name: School of Physics and Astronomy
Abstract
Detecting sources of continuous gravitation waves
Organisations
People |
ORCID iD |
Ik Heng (Primary Supervisor) | |
Joseph Bayley (Student) |
Publications
Bayley J
(2019)
Generalized application of the Viterbi algorithm to searches for continuous gravitational-wave signals
in Physical Review D
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/N504075/1 | 30/09/2015 | 30/03/2021 | |||
1802914 | Studentship | ST/N504075/1 | 30/09/2016 | 30/03/2020 | Joseph Bayley |
Title | SOAP |
Description | This uses the well known Viterbi algorithm, and applys it to the search for continuous gravitational waves. In this application it finds the most probable track through a spectrogram, and uses our statistic to decide whether a detection has been made. |
Type Of Material | Data analysis technique |
Year Produced | 2019 |
Provided To Others? | No |
Impact | We hope this will be a useful tool in the detection of continuous gravitational waves, and also a tool to identify instrumental effects within a gravitational wave detector. |
Title | Armadillo |
Description | Software loads matlab simulink diagrams into a python network graph. This is then reads in information for filters and other blocks in the simulink diagram such that a transfer function can be found between any two points within this model. |
Type Of Technology | Software |
Year Produced | 2018 |
Impact | No obvious impacts yet as still in development. |
Title | SOAP - web |
Description | Tool uses search method based of viterbi algorithm. This runs on chosen ligo data via the web interface and returns results on chosen frequecy bands such that any interesting candidates can be identified. |
Type Of Technology | Webtool/Application |
Year Produced | 2018 |
Impact | No direct impacts as still in testing. Will hopefully be a useful tool to identify instumental noise within the LIGO data. |