Diskussion:Feynman-Kac-Formel

Question about Applications

Is there no more interesting example? As far as I understand the Feynman-Kac formula, it represents the relation between partial differential equations (PDEs) (their solutions) and stochastic processes. In other words, one can model stochastic processes, and use them to sample the approximate solution of a associated transport problem, represented by a PDE. For instance, Quantum Monte Carlo (QMC) methods exploit this connection, if I'm not completely wrong. Also, in neutron physics, one can for instance use MC methods to sample the neutron density in a nuclear reactor, and extract values such as the replication factor k. This is done instead of solving the Boltzmann transport equation (which classically experienced necessary approximations in order to be practically soluble at all on the those days computers).

In modern times of distributed memory or accelerator assisted and enhanced computer clusters, one may use the vastly embarassingly parallelizablity of MC methods, in order to solve PDEs. So, the field of applications of the Feynman-Kac formula is much more far reaching than this articles makes it appear. (nicht signierter Beitrag von 2001:16B8:2DE1:BB00:E498:FA57:6886:EB95 (Diskussion) 21:22, 24. Dez. 2020 (CET))