用液滴诱导渐近法对波动方程源进行有效数值重建

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Shutong Hou, Mourad Sini, Haibing Wang
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引用次数: 0

摘要

SIAM数值分析杂志,64卷,第3期,1018-1042页,2026年6月。摘要。本文提出并数值实现了一种求解三维声波方程逆源问题的新方法。通过向介质中注入一个小的高对比度液滴,我们利用在单个外部点随时间测量的波场扰动。该方法可以实现稳定的源重建,而传统方法由于不适定式而失败,在医学成像和无损检测中具有潜在的应用前景。主要贡献包括:(1)利用牛顿算子的特征系统实现了一个理论上合理的渐近展开式,并对谱截断进行了误差分析。(2)利用Riesz基展开和基于柔化的数值微分求解时域Lippmann-Schwinger方程和重构源的新数值格式。(3)重构仅需单点测量,克服了传统空间数据的局限性。(4)三维数值实验证明了在噪声(信噪比为[math]阶)下的精确源恢复,并对液滴大小(阶[math])和光谱模式数(阶[math])进行了误差分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Numerical Reconstruction of Wave Equation Sources via Droplet-Induced Asymptotics
SIAM Journal on Numerical Analysis, Volume 64, Issue 3, Page 1018-1042, June 2026.
Abstract. In this paper, we develop and numerically implement a novel approach for solving the inverse source problem of the acoustic wave equation in three dimensions. By injecting a small high-contrast droplet into the medium, we exploit the resulting wave field perturbation measured at a single external point over time. The method enables stable source reconstructions where conventional approaches fail due to ill-posedness, with potential applications in medical imaging and nondestructive testing. Key contributions include: (1) Implementation of a theoretically justified asymptotic expansion, from [], using the eigensystem of the Newtonian operator, with error analysis for the spectral truncation. (2) Novel numerical schemes for solving the time-domain Lippmann–Schwinger equation and reconstructing the source via Riesz basis expansions and mollification-based numerical differentiations. (3) Reconstruction requiring only single-point measurements, overcoming traditional spatial data limitations. (4) 3D numerical experiments demonstrating accurate source recovery under noise (SNR of the order [math]), with error analysis for the droplet size (of the order [math]) and the number of spectral modes [math].
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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