{"title":"用液滴诱导渐近法对波动方程源进行有效数值重建","authors":"Shutong Hou, Mourad Sini, Haibing Wang","doi":"10.1137/25m1794899","DOIUrl":null,"url":null,"abstract":"SIAM Journal on Numerical Analysis, Volume 64, Issue 3, Page 1018-1042, June 2026. <br/> 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].","PeriodicalId":49527,"journal":{"name":"SIAM Journal on Numerical Analysis","volume":"35 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Efficient Numerical Reconstruction of Wave Equation Sources via Droplet-Induced Asymptotics\",\"authors\":\"Shutong Hou, Mourad Sini, Haibing Wang\",\"doi\":\"10.1137/25m1794899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"SIAM Journal on Numerical Analysis, Volume 64, Issue 3, Page 1018-1042, June 2026. <br/> 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].\",\"PeriodicalId\":49527,\"journal\":{\"name\":\"SIAM Journal on Numerical Analysis\",\"volume\":\"35 1\",\"pages\":\"\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2026-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIAM Journal on Numerical Analysis\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1137/25m1794899\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Numerical Analysis","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1137/25m1794899","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
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].
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.