Objective
A primary challenge in quantum computing (QC) is finding its ideal application, i.e. an essential problem with the largest advantage of quantum over classical computing. To resolve it, I propose to focus on the notoriously complex area of quantum many-body systems. This project will characterise which quantum many-body problems, in various physics domains, allow for significant quantum advantages even over any future machine learning, data-driven methods. By exploiting my pioneering research in this area, I will also develop new quantum machine learning (QML) methods to solve them better than classically possible, using a two-stage approach.
In the first stage, we will develop the project's theoretical foundations. My recent works on quantum-over-classical learning advantages provide the starting points for the development of new mathematical machinery which facilitates the proving of quantum advantages in selected many-body settings. In parallel,
building on circuit-decomposition methods I recently developed, we will elucidate the role of quantum phenomena in QML in order to design new QML methods which can be better tuned to quantum many-body settings.
In the second stage, we will identify suitable concrete quantum many-body problems with substantial real-world interest, apply the newly designed high-performing quantum learners, and formally prove learning advantages using the developed theoretical machinery.
The positive results of the project will resolve some of the main open problems in QML and will have a major impact on both QC theory and aspects of foundations and applications of QML. In our search for the best application, we will consider many-body problems from diverse areas of physics: condensed matter, high-energy, and quantum control. The project will therefore also establish new bridges between quantum many-body physics, machine learning, and quantum computing.
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.1.1 - European Research Council (ERC)
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-ERC - HORIZON ERC Grants
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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) ERC-2023-COG
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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.
2311 EZ Leiden
Netherlands
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.