Develops parareal methods with exponential integrators for NLS that achieve provable linear convergence with contraction factor proportional to coarse step size for low-regularity solutions.
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math.NA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
An optimized two-step coarse propagator for the parareal algorithm achieves a convergence factor of approximately 0.0064 on linear parabolic equations via a derived error bound, with numerical support on linear and nonlinear cases.
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Exponential Low-Regularity Parareal Algorithms for Nonlinear Schr\"odinger Equations
Develops parareal methods with exponential integrators for NLS that achieve provable linear convergence with contraction factor proportional to coarse step size for low-regularity solutions.
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Optimized Two-Step Coarse Propagators in Parareal Algorithms
An optimized two-step coarse propagator for the parareal algorithm achieves a convergence factor of approximately 0.0064 on linear parabolic equations via a derived error bound, with numerical support on linear and nonlinear cases.