Project description
Efficient computational approach to describing the dynamics of large, complex systems
Interacting particle- and agent-based systems are encountered in many scientific fields, including materials science, biology, economics and social sciences. However, current mathematical models struggle to simulate high-dimensional problems. Funded by the European Research Council, the HighLEAP project aims to develop a new mathematical framework to simulate high-dimensional particle- and agent-based systems more efficiently and accurately. The main challenges to be addressed include sparse optimisation problems for multi-marginal optimal transport problems, numerical resolution of high-dimensional partial differential equations and efficient approximation of parametric stochastic differential equations. By enhancing the predictive power of particle- and agent-based models, HighLEAP has important implications for various fields, such as quantum chemistry, molecular dynamics, crowd motion and urban traffic.
Objective
Interacting particle- or agent-based systems are ubiquitous in science. They arise in an extremely wide variety of applications including materials science, biology, economics and social sciences. Several mathematical models exist to account for the evolution of such systems at different scales, among which stand stochastic differential equations, optimal transport problems, Fokker-Planck equations or mean-field games systems. However, all of them suffer from severe limitations when it comes to the simulation of high-dimensional problems, the high-dimensionality character coming either from the large number of particles or agents in the system, the high amount of features of each agent or particle or the huge quantity of parameters entering the model.
The objective of this project is to provide a new mathematical framework for the development and analysis of efficient and accurate numerical methods for the simulation of high-dimensional particle or agent systems, stemming from applications in materials science and stochastic game theory.
The main challenges which will be addressed in this project are:
-sparse optimization problems for multi-marginal optimal transport problems, using moment constraints;
-numerical resolution of high-dimensional partial differential equations, with stochastic iterative algorithms;
-efficient approximation of parametric stochastic differential equations, by means of reduced-order modeling approaches.
The potential impacts of the project are huge: making possible such extreme-scale simulations will enable to gain precious insights on the predictive power of agent- or particle-based models, with applications in various fields, such as quantum chemistry, molecular dynamics, crowd motion or urban traffic.
Fields of science (EuroSciVoc)
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Keywords
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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)
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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
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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.
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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-2022-STG
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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.
77455 Marne La Vallee Cedex 2
France
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