Objective
Large-scale simulations of lattice Quantum Chromodynamics (QCD) can provide crucial input for searches of new physics at the precision frontier, like in the calculation of the hadronic contribution to the anomalous magnetic moment of the muon. To find evidence of new physics beyond the current knowledge provided by the Standard Model will require to reach per-mille precision. Attaining such accuracy in the hadronic contribution to the anomalous magnetic moment of the muon in lattice QCD can only be achieved by controlling lattice systematics, such as logarithmic terms in the continuum extrapolation, finite volume effects and exponentially increasing noise at large time distances. Simulating gauge ensembles at lattice spacing a<0.04 fm is impossible with current algorithms due to topological freezing. Generative models based on gauge equivariant flows can unfreeze the charge but scale badly with the volume, limiting, up to now, their applicability to toy models.
We propose a solution to overcome topological freezing and suppress exponential noise by developing scalable algorithms for lattice QCD simulations closer to the continuum limit and at physical quark masses based on domain decomposition. By combining machine-learned flow proposals with hierarchical accept/reject steps of the factorized fermion determinant, ensembles at very small lattice spacings can be generated using upcoming european exascale supercomputers. We will implement multi-level sampling techniques within a flexible framework to enable good performance of the here developed novel Markov Chain Monte Carlo algorithm on exascale systems. By the newly generated gauge ensembles lattice QCD will provide a leap in the precision frontier thereby critically contributing in the unraveling of new physics.
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)
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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
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-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.
42119 Wuppertal
Germany
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