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1. Full transmission of vectorial waves through 3D multiple-scattering media

   https://doi.org/10.1364/OL.532642  

   Lin, Ho-Chun; Wei_Hsu, Chia (January 2024, Optics Letters)

   A striking prediction from the random matrix theory (RMT) in mesoscopic physics is the existence of “open channels”: waves that use multipath interference to achieve perfect transmission across an opaque disordered medium even in the multiple-scattering regime. Realization of such open channels requires a coherent control of the complete incident wavefront and has only been achieved for scalar waves in two dimensions (2D) so far. Here, we utilize a recently proposed “augmented partial factorization” full-wave simulation method to compute the polarization-resolved scattering matrix from 3D vectorial Maxwell’s equations and demonstrate the existence of open channels in 3D disordered media. We examine the spatial profile of such open channels, demonstrate the existence of a bimodal transmission eigenvalue distribution, and study the effects of incomplete polarization control and finite-area illumination. The simulations provide full access to all spatiotemporal properties of the complex wave transport in 3D disordered systems, filling the gap left by experimental capabilities. 

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2. Guiding waves through chaos: Universal bounds for targeted mode transport

   https://doi.org/10.1126/sciadv.aeb1158  

   Wang, Cheng-Zhen; Guillamon, John; Kuhl, Ulrich; Davy, Matthieu; Reisner, Mattis; Goetschy, Arthur; Kottos, Tsampikos (January 2026, Science Advances)

   Controlling wave propagation in complex environments is a central challenge across wireless communications, imaging, and acoustics, where multiple scattering and interference obscure direct transmission paths. Coherent wavefront shaping enables precise energy delivery but typically requires full knowledge of the medium. Here, we introduce a universal statistical framework for targeted mode transport (TMT) that circumvents this limitation and validate it on various platforms including microwave networks, two-dimensional chaotic cavities, and three-dimensional reverberation chambers. TMT quantifies the efficiency of transferring energy between specified input and output channels in multimode wave-chaotic systems. We develop a diagrammatic theory that predicts the eigenvalue distribution of the TMT operator and identifies the macroscopic parameters—coupling strength, absorption, and channel control—that govern performance. The theory provides explicit bounds for optimal TMT wavefronts and captures phenomena like statistical transmission gaps and reflectionless states. These findings establish design principles for energy delivery and information transfer in complex environments, with broad implications for adaptive signal processing and wave-based technologies. 

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3. Ultra-Fast Scattering Matrix Solver for Disordered Media

   https://doi.org/10.1364/CLEO_QELS.2022.FM5H.5  

   Lin, Ho-Chun; Wang, Zeyu; Hsu, Chia Wei (May 2022, Conference on Lasers and Electro-Optics (CLEO))

   Using the Schur complement scattering analysis (SCSA) method, we accelerate the scattering matrix computation for large-scale disordered media by many orders of magnitude and realize full-wave simulations of classical and quantum coherent backscattering. 

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4. Fast Multi-channel Full-wave Solver and Inverse Design with Augmented Partial Factorization

   https://doi.org/10.1364/NOMA.2023.NoW4C.1  

   Hsu, Chia Wei (January 2023, Optica Publishing Group)

   In this talk, I describe a fast full-wave Maxwell equations solver based on the “augmented partial factorization” (APF) method and our inverse design of nonlocal metasurfaces using APF. 

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5. NeuWS: Neural wavefront shaping for guidestar-free imaging through static and dynamic scattering media

   https://doi.org/10.1126/sciadv.adg4671  

   Feng, Brandon Y.; Guo, Haiyun; Xie, Mingyang; Boominathan, Vivek; Sharma, Manoj K.; Veeraraghavan, Ashok; Metzler, Christopher A. (June 2023, Science Advances)

   Diffraction-limited optical imaging through scattering media has the potential to transform many applications such as airborne and space-based imaging (through the atmosphere), bioimaging (through skin and human tissue), and fiber-based imaging (through fiber bundles). Existing wavefront shaping methods can image through scattering media and other obscurants by optically correcting wavefront aberrations using high-resolution spatial light modulators—but these methods generally require (i) guidestars, (ii) controlled illumination, (iii) point scanning, and/or (iv) statics scenes and aberrations. We propose neural wavefront shaping (NeuWS), a scanning-free wavefront shaping technique that integrates maximum likelihood estimation, measurement modulation, and neural signal representations to reconstruct diffraction-limited images through strong static and dynamic scattering media without guidestars, sparse targets, controlled illumination, nor specialized image sensors. We experimentally demonstrate guidestar-free, wide field-of-view, high-resolution, diffraction-limited imaging of extended, nonsparse, and static/dynamic scenes captured through static/dynamic aberrations. 

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