Project description
Probing the dark universe with gravitational waves
Since the first direct observation of gravitational waves in 2015, the LIGO and Virgo interferometers have detected over 50 gravitational waves from mergers of binary star systems. Yet it takes months for computers to crunch the data behind such mergers. The EU-funded Deledda project aspires to construct a new analytical model to compare data against, which looks for gravitational waves that could help explain dark energy. Using machine learning techniques, the model hopes to provide a new way to detect the unobserved dark energy and matter that make up most of our universe.
Objective
Gravitational wave astronomy has opened an extraordinary new window to test the theory of gravity in the genuinely strong, highly dynamical and relativistic regime. The LIGO-Virgo Collaboration has now detected over 50 mergers of compact binary systems and this number will considerably increase in the coming years. There are currently two main issues related to the possibility of testing gravity with gravitational wave observations: the weakness of parametric tests of General Relativity to go beyond null tests and the very long inference time required by standard samplers which can take up to months. Specific waveform models and new techniques to speed up statistical inference are therefore crucial to maximise the scientific return of already available and upcoming data. In this project, we will construct an analytical model of the gravitational waves emitted during the late inspiral and merger of compact objects in theories of gravity that are cosmologically motivated, namely that have a chance to explain Dark Energy. We will then leverage deep learning techniques to promptly produce the posterior for the corresponding parameters given the detector data. To this aim, we will build up on two codes developed by one of the supervisors - ROMAN and PERCIVAL - which pioneered the use of machine learning in gravitational wave science. We will then apply this new pipeline to the real LIGO-Virgo data and perform Bayesian inference of Dark Energy parameters. All together this project will provide a new and complete framework to test the dark Universe with gravitational wave observations, exploiting state-of-the-art deep learning techniques.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2021-PF-01
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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.
56126 PISA
Italy
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.