Augmented Lagrangian Method based adjoint space framework for sparse reconstruction of acoustic source with boundary measurements

Hongpeng Sun 孙鸿鹏

中国人民大学

孙鸿鹏，中国人民大学数学学院教授。2012年博士毕业于中科院数学所，2012-2014奥地利格拉茨大学博士后研究。主要从事反问题和图像处理方面的研究，近年来主要研究声波、电磁波的反散射问题和图像处理的非光滑非凸优化算法。相关研究工作发表在SIAM J. Scientific Computing, SIAM J. Numerical Analysis, Inverse Problems等国际权威杂志。

# Organizer

李宏杰

# Title

Augmented Lagrangian Method based adjoint space framework for sparse reconstruction of acoustic source with boundary measurements

# Time

Friday, 10:30-11:30,

Dec. 26, 2025

# Venue

C654, Shuangqing Complex Building A

#Abstract / 摘要

We propose a semismooth Newton-based augmented Lagrangian method for reconstructing sparse sources in inverse acoustic scattering problems. The semismooth Newton method can be iterated in the space of measurements instead of the unknown source to be reconstructed. It is highly efficient, especially when the measurement data is much less than the acoustic source. The source can be calculated from Fenchel-Rockafellar duality theory. We can obtain lots of acceleration and leverage the computational cost. The numerical examples show the high efficiency of the proposed semismooth Newton-based methods. This is a joint work with Tan Nirui.