Emergent Mind
Multilevel Picard approximations of high-dimensional semilinear partial differential equations with locally monotone coefficient functions
(2202.02582)
Published Feb 5, 2022
in
math.NA
,
cs.NA
,
and
math.PR
Abstract
The full history recursive multilevel Picard approximation method for semilinear parabolic partial differential equations (PDEs) is the only method which provably overcomes the curse of dimensionality for general time horizons if the coefficient functions and the nonlinearity are globally Lipschitz continuous and the nonlinearity is gradient-independent. In this article we extend this result to locally monotone coefficient functions. Our results cover a range of semilinear PDEs with polynomial coefficient functions.
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