Published on May 23, 2021–Updated on July 12, 2022
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e-Guest Lecture: Pierre-Emmanuel Jabin
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Large stochastic systems of interacting particles
Pierre-Emmanuel Jabin, director of the Center for Scientific Computing and Mathematical Modeling at the University of Maryland, is currently fellow-in-residence at CY AS, invited by laboratory AGM
Large stochastic many-particle or multi-agent systems are conceptually simple but exhibit a wide range of emerging macroscopic behaviors. For this reason, they are now employed in a large variety of applications from Physics (plasmas, galaxy formation...) to the Biosciences, Economy, Social Sciences...
The number of agents or particles is typically quite large, with 1020-1025 particles in many Physics settings for example and just as many equations. Analytical or numerical studies of such systems are potentially very complex leading to the key question as to whether it is possible to reduce this complexity, notably thanks to the notion of propagation of chaos (agents remaining almost uncorrelated).
I will present some of the main concepts around deriving this propagation of chaos, together with a recent statistical method that we have introduced.