LIGO Seismic State Characterization using Machine Learning Techniques

Document #:

LIGO-T2300147-v2

Document type:

T - Technical notes

Abstract:

Isaac Kelly SURF 2023 project at UC Riverside.

Files in Document:

• Final Report (Isaac_Kelly_SURF_2023_Final_Report.pdf, file is not accessible)

Other Files:

• Final Presentation (Isaac Kelly SURF Presentation.pptx, file is not accessible)
• Interim Report 1 (Isaac_Kelly_SURF_2023_Interim_1.pdf, file is not accessible)
• Interim Report 2 (Isaac_Kelly_SURF_2023_Interim_2.pdf, file is not accessible)
• Project Proposal (Isaac_Kelly_SURF_2023.pdf, file is not accessible)

Topics:

• Machine Learning
• State Control and Monitoring

Authors:

• Isaac Kelly
• Pooyan Goodarzi
• Rutuja Gurav
• Vagelis Papalexakis
• Jonathan Richardson

Keywords:

SURF23

Notes and Changes:

Final report upload

Referenced by:

• LIGO-T2300416: Final reports from LIGO SURF program, Summer 2023