Multiscale computational methods in kinetic theory and optimal transport

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Kinetic equations with multiple scales arise in diverse applications such as rarefied gas dynamics, plasma physics, semiconductors, and biology; they often introduce severe numerical challenges due to the stiffness that comes from the small scales. Optimal transport plays a fundamental role in image registration, video restoration, urban transport, kinetic theory and many others. However, numerical methods for it have not reached their full capacity to meet the most demanding practical applications. This project aims at both advancing the multiscale computational methods - particularly the asymptotic preserving (AP) schemes - in new prospects for kinetic equations including multi-stage and fractional asymptotic limit, and developing fast parallelizable algorithms for optimal transport via advanced optimization technique. Specifically, the following topics will be investigated in this project: (1) theoretically study the AP schemes for semiconductor Boltzmann equation with two-scale collisions at a deeper depth and generalize them to implicit/high order schemes and to capture the hierarchy of macroscopic models; (2) extend the AP scheme for kinetic equation with fractional diffusion limit to a broader scope including anisotropic scattering, degenerate collision, and Levy-Fokker-Planck interaction (applications to nonclassical photon transport in clouds will be addressed); (3) develop efficient algorithms for optimal transport problems and conduct convergence analysis and apply it to practical problems especially for human crowd dynamics in panic situations. With increasing interest in multiscale kinetic equations and optimal transport, the computational methods developed here will impact beyond the particular applications in this proposal. The dynamics of electron transport in semiconductor devices are one of the main concerns in physics and engineering; the developed methods from this proposal will be equally applicable in a broader context such as gas discharges and multi-group radiative transfer. Nonclassical transport that leads to a fractional diffusion has attracted much attention in plasma physics and economy; it has now been applied in climate science to model the photon transport in clouds as well as in criminology to model the hotspots in residential burglaries. Optimal transport has become a useful tool in image processing, urban transport, computer vision and etc; the development of fast parallelizable algorithms will substantially advance these areas and the application in modeling human crowds is crucial for better preparation of safe mass events.