Objective
During the last two decades, Machine Learning (ML) and Artificial Intelligence (AI) tools have created a true paradigm shift and impacted numerous fields and industries. In quantum physics, ML is rapidly gaining popularity and is already being extensively used for variational quantum state representation. Recently, a more ambitious and new research direction is developing where Reinforcement Learning agents could be used to solve quantum statistical problems while improving during the task. This field is still in its infancy and is highly promising to yield efficient and scalable computational tools for physics that would be situated between semi-analytical approximations and brute-force Monte Carlo calculations. In this proposal such tools will be developed for applications in modern quantum many-body physics at finite temperatures. In particular, the goal is to train smart AI agents to sample path integrals that occur in various quantum statistical problems. Important research questions include exploring domain generalization where learned knowledge by the agent can be transferred between tasks. The developed methodology will be applied to challenging systems in condensed matter physics such as many-fermion systems and polaronic systems with memory. Besides providing powerful computational tools, this research on the thrilling synthesis of Reinforcement Learning and quantum statistics will yield new insights and perspectives at the forefront of the current AI explosion in physics.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- natural sciences computer and information sciences computational science
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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-2024-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.
2000 Antwerpen
Belgium
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.