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Inverse theory of wavefront shaping in nonlinear scattering media

  • Daixuan Wu
  • , Zhen Yi
  • , Jiaming Liang
  • , Tijian Li
  • , Zhongzheng Zhu
  • , Zexian Zhang
  • , Haitao Ye
  • , Jiawei Luo
  • , Zhengyang Wang
  • , Meng Liu
  • , Zhi Chao Luo*
  • , Yuecheng Shen*
  • *Corresponding author for this work
  • Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices
  • South China Normal University
  • School of Physics
  • East China Normal University
  • School of Electronics and Information Technology
  • Sun Yat-Sen University
  • MOE Key Laboratory of Laser Life Science

Research output: Contribution to journal › Article › peer-review

Abstract

Scattering fundamentally limits the propagation of light in complex media, yet controlling it is essential for transformative advances in imaging, sensing, and optical communication. While decades of research have established powerful methods for linear wavefront shaping, the control of nonlinear scattering remains dominated by feedback-based optimization and neural networks — approaches that lack interpretability and theoretical bounds. Here, we establish the analytic inverse theory of nonlinear wavefront shaping under open-geometry scattering conditions with circular complex Gaussian statistics. By formulating an explicit scattering tensor model, we reveal how the optimal input field emerges from the dominant eigenchannel of the tensor’s spectral diagonalization. This framework directly leads to a closed-form enhancement bound for second-harmonic generation. We experimentally confirm the theory by shaping wavefronts to realize single-point focusing, multi-point focusing, and global second-harmonic signal enhancement in nonlinear scattering media. By bridging nonlinear optics and inverse wavefront control, this work transforms nonlinear wavefront shaping from an optimization-driven practice into a principled, interpretable, and prediction-capable discipline.

Original languageEnglish
Article number6011
JournalNature Communications
Volume17
Issue number1
DOIs
StatePublished - Dec 2026

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