5 papers
Exponential Low-Regularity Parareal Algorithms for Nonlinear Schrödinger Equations
Qingle Lin, Zhi Zhou
The parareal algorithm is one of the most widely studied parallel-in-time methods for the numerical approximation of time-dependent problems. For non-diffusive equations, however,…
Linear Convergence of Parareal Algorithm for Semilinear Parabolic Equations
Guanglian Li, Qingle Lin, Shu-lin Wu +1
Long-time simulations of evolution equations present substantial computational challenges due to the inherently sequential nature of conventional time-stepping schemes. The pararea…
Convergence analysis of a parareal algorithm with multistep fine propagator
Georgios Akrivis, Qingle Lin, Zhi Zhou
The parareal algorithm is a powerful parallel-in-time integration method that accelerates the numerical solution of evolution equations by iteratively combining a fine propagator a…
Optimized Two-Step Coarse Propagators in Parareal Algorithms
Guanglian Li, Qingle Lin, Kai Zhang +1
In this work, we propose a novel framework for accelerating the parareal algorithm, in which the coarse propagator is formulated as a two-step method and optimized with respect to…
Optimizing Coarse Propagators in Parareal Algorithms
Bangti Jin, Qingle Lin, Zhi Zhou
The parareal algorithm represents an important class of parallel-in-time algorithms for solving evolution equations and has been widely applied in practice. To achieve effective sp…