Login

ACME - AresGW

→ Europe/Paris
Alexandra Eleni Koloniari (Aristotle University of Thessaloniki), Nikolaos Stergioulas (Aristotle University of Thessaloniki)
Description

AresGW is a machine-learning-based pipeline designed for offline real-time gravitational wave (GW) detection of  binary black hole mergers. The structure of the code will be explained, and participants will learn how to generate training data and how to train AresGW and apply it to real LVK data. 

All training material for this session is available at this repository.

    • 1
      Introduction
      Speaker: Nikolaos Stergioulas (Aristotle University of Thessaloniki)
      ACME
    • 2
      AresGW overview
      Speaker: Alexandra Eleni Koloniari (Aristotle University of Thessaloniki)
      AresGW model 1
      AresGW training repository
    • 3
      LVK Gravitational Wave Data
      Speaker: Alexandra Eleni Koloniari (Aristotle University of Thessaloniki)
    • 4
      AresGW setup
      Speaker: Nikolaos Stergioulas (Aristotle University of Thessaloniki)
    • 5
      Training Data
      Speaker: Nikolaos Stergioulas (Aristotle University of Thessaloniki)
      MLGWSC-1
    • 11:45
      Break
    • 6
      Train - Test - Evaluate

      Hands-on Session

      Speakers: Alexandra Eleni Koloniari (Aristotle University of Thessaloniki), Nikolaos Stergioulas (Aristotle University of Thessaloniki)
      AresGW Variance Repository