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

Speaker: 孙鸿鹏 教授，中国人民大学

Inviter: 刘晓东 研究员

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

Time & Venue: 2025.12.4 15:00-16:00  #腾讯会议：271-794-206

Abstract: 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.