IMEX-RB: a self-adaptive implicit-explicit time integration scheme exploiting the reduced basis method
Micol Bassanini, Simone Deparis, Francesco Sala, Riccardo Tenderini

TL;DR
IMEX-RB introduces a self-adaptive implicit-explicit time integration scheme that dynamically constructs a reduced basis for efficient and stable numerical integration of ODE systems from PDE discretizations, outperforming traditional methods.
Contribution
The paper presents the first-order IMEX-RB method that builds a dynamic reduced basis without offline-online splitting, enhancing stability and efficiency in time integration.
Findings
IMEX-RB is unconditionally stable under certain hyperparameters.
The method outperforms backward Euler in accuracy and computational efficiency.
Numerical experiments confirm convergence and stability properties.
Abstract
In this work, we introduce a self-adaptive implicit-explicit (IMEX) time integration scheme, named IMEX-RB, for the numerical integration of systems of ordinary differential equations (ODEs), arising from spatial discretizations of partial differential equations (PDEs) by finite difference methods. Leveraging the Reduced Basis (RB) method, at each timestep we project the high-fidelity problem onto a suitable low-dimensional subspace and integrate its dynamics implicitly. Following the IMEX paradigm, the resulting solution then serves as an educated guess within a full-order explicit step. Notably, compared to the canonical RB method, IMEX-RB neither requires a parametrization of the underlying PDE nor features an offline-online splitting, since the reduced subspace is built dynamically, exploiting the high-fidelity solution history. We present the first-order formulation of IMEX-RB,…
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Taxonomy
TopicsNumerical methods for differential equations · Model Reduction and Neural Networks · Advanced Numerical Methods in Computational Mathematics
