3–5 Jun 2026
Pisa
Europe/Rome timezone

Second Order IMEX Time Stepping Methods for Efficient Multi-Electrode Array simulations

3 Jun 2026, 16:45
15m
Aula E

Aula E

MS05 - Multiscale Cardiac Electrophysiology: From Scalable Computational Solvers to Patient-Specific Simulations MS05 - Multiscale Cardiac Electrophysiology: From Scalable Computational Solvers to Patient-Specific Simulations

Speaker

Sofia Tonali (Università di Pavia)

Description

Multi-electrode arrays (MEAs) enable tissue-level electrophysiological studies of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) by recording extracellular field potentials (FPs). Recent in-silico models have improved MEA simulations by coupling detailed electrode descriptions with the Bidomain framework, a parabolic-elliptic system of nonlinear PDEs coupled with a stiff ionic model.
The standard numerical strategy relies on operator splitting techniques that decouple the PDE and ODE components. In most existing implementations, the ionic subsystem is treated explicitly while the diffusive Bidomain operator is handled implicitly, leading to first-order Implicit-Explicit (IMEX) time discretizations. Although computationally convenient, this approach limits temporal accuracy and may compromise efficiency in large-scale simulations.
In this work, we revisit this framework and investigate higher-order IMEX Runge–Kutta schemes within the Strang operator splitting, specifically tailored for the Bidomain–MEA setting. The proposed method preserves the computational advantages of the IMEX structure while achieving higher temporal accuracy without increasing algorithmic complexity. We compare first- and second-order schemes in terms of computational cost and global error with respect to a high-fidelity reference solution computed with a very small time step. For a fixed computational time, the higher-order scheme significantly enhances accuracy. These results demonstrate that increasing the temporal order within an IMEX operator-splitting framework provides tangible efficiency gains and enhances the reliability of large-scale MEA simulations.

Authors

Prof. Luca Franco Pavarino (Università di Pavia) Sofia Botti (MOX, Politecnico di Milano) Sofia Tonali (Università di Pavia)

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