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An efficient and memory saving algorithm for subdiffusion equation using incremental singular value decomposition

delete2026-07-29
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PRE
AI
J
Jichun Li
Y
Yangpeng Zhang *
Y
Yangwen Zhang
DOI:10.1016/j.jcp.2026.115246delete
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Abstract

Abstract

En 中文
In this paper, we address the well-known challenge in the numerical solution of time-fractional partial differential equations (TFPDEs), namely, that the dependence on all previous time levels leads to storage requirements that grow linearly with the number of time steps. To overcome this difficulty, we develop an efficient algorithm based on incremental singular value decomposition (ISVD), which avoids the excessive memory demands associated with storing the full solution history. A rigorous error analysis is established, and numerical experiments are presented to validate the theoretical results. Comparisons with the direct method and a representative fast evaluation method show that the proposed ISVD approach dramatically reduces memory usage relative to the direct method and remains competitive with the fast method over the tested parameter regimes.
Keywords:
Time-fractional partial differential equation
Caputo derivative
Incremental singular value decomposition
Finite element method

Journal

Journal of Computational Physics cover
Journal of Computational Physics
IF:
3.8
Papers:
1.5W
Citations:
7.4W

Organization

U
university of nevada las vegas
Scholars:
3.8K
Papers: 3.4K
Citations: 8
U
university of louisiana at lafayette
Scholars:
138
Papers: 70
Citations: 0