Dense cell-by-cell systems of PDEs: approximation, spectral analysis, and preconditioning

Abstract In the present study, we consider the Extra-Membrane-Intra (EMI) model for the simulation of excitable tissues at the cellular level. We provide the (possibly large) system of partial differential equations (PDEs), equipped with ad hoc boundary conditions, relevant for modelling portions of excitable tissues, composed of several cells. In particular, we study two geometrical settings in the context of computational cardiology and neuroscience. The Galerkin approximations of the considered system of PDEs lead to large linear systems of algebraic equations, where the coefficient matrices depend on the number N of cells and the fineness parameters. We present a structural and spectral analysis of the related matrix-sequences as the fineness parameters tends to zero. Based on the theoretical results, we propose preconditioners and specific multilevel solvers. Numerical experiments are presented and critically discussed, showing that a monolithic multilevel solver is efficient and robust with respect to all the problem and discretization parameters. In particular, we include numerical results for an increasing number of cells N , both for idealized geometries (with N exceeding $$10^5$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mn>5</mml:mn> </mml:msup> </mml:math> ) and for realistic, densely populated 3D tissue reconstructions.

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Publication Details

Journal
BIT Numerical Mathematics
Published
2026-07-28
DOI
https://doi.org/10.1007/s10543-026-01136-6
Citations
1
Primary Topic
Molecular Communication and Nanonetworks
Type
article
Field-Weighted Citation Impact
0.00

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article

Dense cell-by-cell systems of PDEs: approximation, spectral analysis, and preconditioning

Pietro Benedusi, Stefano Serra‐Capizzano, Paola Ferrari, Marius Causemann
1 citations
BIT Numerical Mathematics
Molecular Communication and Nanonetworks
article

Dense cell-by-cell systems of PDEs: approximation, spectral analysis, and preconditioning

Pietro Benedusi, Stefano Serra‐Capizzano, Paola Ferrari, Marius Causemann
article en
1 citations

Abstract

Abstract In the present study, we consider the Extra-Membrane-Intra (EMI) model for the simulation of excitable tissues at the cellular level. We provide the (possibly large) system of partial differential equations (PDEs), equipped with ad hoc boundary conditions, relevant for modelling portions of excitable tissues, composed of several cells. In particular, we study two geometrical settings in the context of computational cardiology and neuroscience. The Galerkin approximations of the considered system of PDEs lead to large linear systems of algebraic equations, where the coefficient matrices depend on the number N of cells and the fineness parameters. We present a structural and spectral analysis of the related matrix-sequences as the fineness parameters tends to zero. Based on the theoretical results, we propose preconditioners and specific multilevel solvers. Numerical experiments are presented and critically discussed, showing that a monolithic multilevel solver is efficient and robust with respect to all the problem and discretization parameters. In particular, we include numerical results for an increasing number of cells N , both for idealized geometries (with N exceeding $$10^5$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mn>10</mml:mn> <mml:mn>5</mml:mn> </mml:msup> </mml:math> ) and for realistic, densely populated 3D tissue reconstructions.

BIT Numerical MathematicsVol. 66(3)
University of Insubria (IT), Uppsala University (SE), University of Wuppertal (DE), Simula Research Laboratory (NO), Università della Svizzera italiana (CH), University of Genoa (IT)
Athens University of Economics and Business, Istituto Nazionale di Alta Matematica "Francesco Severi", European Commission, Ministero della Salute, Norges Forskningsråd, Gruppo Nazionale per il Calcolo Scientifico
Openalex Percentile: Top 100%
Molecular Communication and Nanonetworks
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