For a semilinear parabolic tumor-growth PDE with uniform random coefficients, quasi-Monte Carlo achieves near-linear error convergence O(N^{-1}) for output expectations, beating Monte Carlo's O(N^{-1/2}), with proof and numerical confirmation.
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Quasi-Monte Carlo methods for uncertainty quantification of tumor growth modeled by a parametric semi-linear parabolic reaction-diffusion equation
For a semilinear parabolic tumor-growth PDE with uniform random coefficients, quasi-Monte Carlo achieves near-linear error convergence O(N^{-1}) for output expectations, beating Monte Carlo's O(N^{-1/2}), with proof and numerical confirmation.