Abstrakt: Despite the tremendous success of mathematical general relativity which revealed among others surprising features of the geometry of rotating (Kerr) black holes and developed approximation techniques to study early stages of their inspiral, the necessity to describe completely the merger of two black holes lead to a substantial progress of numerical relativity. This field necessarily uses techniques of modern computer science to amass and command number crunching capabilities of current computers as well as numerical methods for partial differential equations, but the successful...
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Semináře a workshopy oddělení 29
Seminář / Středa, 29.01.2020 14:00
Abstrakt: Machine learning has revolutionized most fields it has penetrated, and the range of its applications is growing rapidly. The last years has seen efforts towards bringing the tools of machine learning to lattice QFT. After giving a general idea of what is machine learning, I will present two recent results on lattice QFT: 1) computing the Casimir energy for a 3d QFT with arbitrary Dirichlet boundary conditions, 2) predicting the critical temperature of the confinement phase transition in 2+1 QED at different lattice sizes.
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