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Gravitational-wave data mining

Project description

Data mining techniques to make the best out of the gravitational wave data deluge

Gravitational-wave astronomy is set to become a very data-rich science, driven by the advances in detector sensitivity and data-analysis techniques. Thousands of gravitational wave events will soon be available, providing a wealth of information on the most compact objects in the Universe – black holes and neutron stars. The EU-funded GWmining project plans to apply data-mining techniques to explore these upcoming gravitational-wave catalogues. It will train machine-learning algorithms directly on large banks of simulations of stellar population synthesis and post-Newtonian integrations. Combined with a hierarchical Bayesian analysis, this approach will deliver the most stringent measurements to date on elusive phenomena affecting the lives of massive stars.

Objective

Gravitational-wave astronomy is entering its large-statistics regime. Catalogs with thousands of gravitational-wave events will soon be available, providing a wealth of information on the most compact objects in the Universe --black holes and neutron stars. These new datasets need new tools to be exploited effectively in order to maximize their scientific impact.

GWmining is an ambitious program to explore upcoming gravitational-wave catalogs with data-mining techniques. We will develop a complete framework to analyze gravitational-wave data in light of astrophysical predictions. Going beyond phenomenological models, we will train machine-learning algorithms directly on large banks of population-synthesis simulations and post-Newtonian integrations. The development of these astrophysical predictions requires new modeling strategies to accurately capture all the gravitational-wave observables, notably spins and eccentricities.
Combined with a hierarchical Bayesian analysis, our neural network will deliver the most stringent measurements to date on elusive phenomena influencing the lives of massive stars. We will constrain phenomena such as binary common envelope, supernova kicks, stellar winds, tidal interactions, etc.

Besides harnessing the catalog in its entirety, our complete framework will put us at the forefront to analyze outliers --golden events with favorable properties of one or more parameters. We will design a complete strategy to exploit the strongest signals to infer exquisite details of the relativistic dynamics of their sources.

GWmining is a unique project strategically placed at the intersection of astronomy, data analysis, and relativity. As the large-statistics revolution of gravitational-wave astronomy unfolds, GWmining will pioneer the application of data-mining techniques in gravitational-wave population studies, setting the foundations of this booming field for decades.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2020-STG

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Host institution

UNIVERSITA' DEGLI STUDI DI MILANO-BICOCCA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 499 917,00
Address
PIAZZA DELL'ATENEO NUOVO 1
20126 Milano
Italy

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Region
Nord-Ovest Lombardia Milano
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 499 917,00

Beneficiaries (2)

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