An unconditionally stable hybrid numerical method for the gradient flow for the high-order Modica–Mortola functional

This paper presents a numerically stable, time-accurate algorithm for simulating the gradient flow associated with the Modica–Mortola functional with a uniformly spaced multi-well potential. The scheme uses operator splitting; the nonlinear component is updated analytically, while the linear part is advanced by a Fourier spectral discretization. The method is unconditionally stable, preserves pointwise boundedness independently of the time step size, and attains spectral accuracy in space and first-order accuracy in time. We provide a theoretical analysis establishing unconditional stability and boundedness, and present comprehensive numerical experiments that demonstrate the accuracy and robustness of the proposed approach.

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Publication Details

Journal
Electronic Research Archive
Published
2025-01-01
DOI
https://doi.org/10.3934/era.2025281
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
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An unconditionally stable hybrid numerical method for the gradient flow for the high-order Modica–Mortola functional

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Electronic Research Archive
Advanced Numerical Methods in Computational Mathematics
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An unconditionally stable hybrid numerical method for the gradient flow for the high-order Modica–Mortola functional

Zhengang Li, Xinpei Wu, Hyunho Shin, Hyun Dong Kim, Junseok Kim, Yunjae Nam
article en

Abstract

This paper presents a numerically stable, time-accurate algorithm for simulating the gradient flow associated with the Modica–Mortola functional with a uniformly spaced multi-well potential. The scheme uses operator splitting; the nonlinear component is updated analytically, while the linear part is advanced by a Fourier spectral discretization. The method is unconditionally stable, preserves pointwise boundedness independently of the time step size, and attains spectral accuracy in space and first-order accuracy in time. We provide a theoretical analysis establishing unconditional stability and boundedness, and present comprehensive numerical experiments that demonstrate the accuracy and robustness of the proposed approach.

Electronic Research ArchiveVol. 33(10)
Gangneung–Wonju National University (KR), Korea University (KR)
Openalex Percentile: Top 67%
Advanced Numerical Methods in Computational Mathematics
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