WG3 explores the use of Machine Learning (ML) techniques in the control and noise mitigation strategies of scientific experiments, specifically for Gravitational Wave (GW) detectors. GW detectors, both those currently running and those foreseen to be spaceborne, are uniquely complex instruments with specific and new challenges in terms of control and noise issues. These challenges call for significant adaptation and ingenuity in the ML approaches, which are seldom used as textbook cases and are often coupled with simulations and burden with heavy experimental constraints. These developments need diverse expertise and interaction, which is the benefit of the current COST action. This working group’s goal is to develop ML algorithms as part of the detectors’ feedback-control systems as well as for the feed-forward cancellation of noise.
In the training school we address the following topics:
- Einstein Telescope
- LISA
- Deep learning taxonomy
- Newtonian noise cancellation with machine learning
- Fractal analysis for controlling interferometers
- Robotics for interferometers
The workshop is organised during August 30-September 2, 2021, ONLINE, see below for the zoom coordinates.
The following speakers have kindly agreed to join us:
- Dr Francesca Badaracco, UCLouvain, Belgium: "Newtonian Noise Cancellation Strategies and Optimisation Problems"
- Prof Marco Cavaglia, Missouri Univeristy of Science and Technology, US: "Fractal analysis for interferometer control"
- Dr Razvan Pascanu, DeepMind, UK: "Deep learning Taxonomy"
- Dr Natalia Korsakova, Artemis, France : "LISA talk on disentanglement"
- Dr Fabio Bonsignorio, HeronRobotics: "Robotics for interferometers"
- Dr Luca Naticchioni, INFN, Italy: "Einstein Telescope site characterisation measures and their impact on the third generation GW detectors"
- Prof Stefan Hild, Maastricht University, The Netherlands: "Einstein Telescope: technical & scientific challenges for the future GW detectors"
These speakers will also oversee a round table discussion on Thursday, September 2, mainly on investigating the machine learning potential in their topics, but also discussing other topics of interest.
Please contact either/both Luigia and Andrea (lpetre@abo.fi, andrea.chincarini@ge.infn.it) if you have questions.
Luigia Petre is inviting you to a scheduled Zoom meeting.
Topic: WG3's Training School, August 30- September 2, 2021
Time: This is a recurring meeting Meet anytime
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Meeting ID: 636 3418 8394
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Meeting ID: 636 3418 8394
