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arXiv:2610.05229

Integrated robust universal linear optics based on white-boxed multi-plane light conversion

Xinyu Song, Lan-Tian Feng, Pan Gong, Yu-Yang Ding, Guo G, Xi-Feng Ren

Published Oct 4, 2026• 0 citations
arXivHTMLPDF

Abstract

The integrated universal linear optical processor realized via multi-plane light conversion (MPLC) features low hardware complexity and high fabrication robustness, suitable for diverse photonic processing tasks. However, the lack of validated calibration protocols limits its universality and potential. Here, we propose a machine-learning-based calibration method and verify it using an eight-mode silicon photonic processor composed of interleaved multiport directional couplers and phase-shifter arrays. We characterize coupler transfer matrices and current-phase responses of individual phase shifters. To validate the robustness, we demonstrate its universality with Haar-random unitary matrices at wavelengths of 1500, 1550, and 1580 nm, and under partial phase-shifter deactivation. With this white-boxed device, we also demonstrate high-dimensional quantum gates and quantum reservoir computing for handwritten digit classification. Our work advances integrated MPLC-based universal linear optics and paves the way for large-scale, fabrication-robust, broadband hardware for classical and quantum photonic information processing.

DOI
10.48550/arxiv.2610.05229

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The integrated universal linear optical processor realized via multi-plane light conversion (MPLC) features low hardware complexity and high fabrication robustness, suitable for diverse photonic processing tasks. However, the lack of validated calibration protocols limits its universality and potential. Here, we propose a machine-learning-based calibration method and verify it using an eight-mode silicon photonic processor composed of interleaved multiport directional couplers and phase-shifter arrays. We characterize coupler transfer matrices and current-phase responses of individual phase shifters. To validate the robustness, we demonstrate its universality with Haar-random unitary matrices at wavelengths of 1500, 1550, and 1580 nm, and under partial phase-shifter deactivation. With this white-boxed device, we also demonstrate high-dimensional quantum gates and quantum reservoir computing for handwritten digit classification. Our work advances integrated MPLC-based universal linear optics and paves the way for large-scale, fabrication-robust, broadband hardware for classical and quantum photonic information processing.
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Programmable linear optical interferometers are a core primitive in optical signal processing, quantum information processing, and photonic computing. Existing photonic-integrated implementations realize arbitrary MMM-mode unitaries using Mach--Zehnder-interferometer meshes whose footprint and accumulated loss scale with O(M2)O(M^2)O(M2) optical components. Here we analyze and experimentally demonstrate a programmable architecture for implementing linear optical transformations directly on spatially tiled free-space {\em pixel modes} using multi-plane light conversion (MPLC). In this architecture, MMM spatial modes arranged on a transverse lattice undergo a unitary transformation and are mapped to MMM output modes of identical geometry through a sequence of programmable phase masks separated by free-space propagation segments. Numerical simulations show that arbitrary MMM-mode unitaries can be compiled to a desired high fidelity using a number of phase planes that scales approximately linearly with MMM. Using a spatial-light-modulator-based MPLC, we experimentally demonstrate programmable interferometers acting on up to 161616 spatial pixel modes, including tunable beamsplitters, Hadamard unitaries, spatial permutations, and partial unitaries on select subsets of modes. These results establish MPLC-based pixel-mode interferometers as a promising architecture for programmable linear optics with applications in classical and quantum optical interconnects, photonic switching, and quantum information processing.
High-dimensional entangled photons are a key resource for advanced quantum information processing. Efficient processing of high-dimensional entangled photons requires the ability to synthesize their state using general unitary transformations. The leading technology for processing photons in high-dimensions is integrated multiport interferometers. However, such devices are incompatible with free-space and fiber-based systems, and their architecture poses significant scaling challenges. Here we unlock these limitations by demonstrating a reconfigurable processor of entangled photons that is based on multi-plane light conversion (MPLC), a technology that was recently developed for multiplexing hundreds of spatial modes for classical free-space and fiber communication. To demonstrate the flexibility of MPLC, we perform four key tasks of quantum information processing using the same MPLC hardware: entanglement certification, tailored two-photon interference, arbitrary state transformations, and mode conversion. Based on the high degree of control we obtain, we expect MPLC will become a leading platform for future quantum technologies.
Optical computing is emerging as a promising platform for energy-efficient, high-throughput hardware in deep learning. A key challenge lies in the realization of optical matrix–vector multiplication, which often requires O ( N 2 ) modulators for the exact synthesis of N × N matrices, limiting its scalability. In this study, we propose an approximate matrix realization method using multi-plane light conversion (MPLC) that reduces both the system size and the number of phase shifters while maintaining acceptable error bounds. This approach introduces low-entropy mode mixers, in which couplings between optical modes are weak. We demonstrate that such mixers can preserve computational accuracy while reducing hardware requirements, enabling more flexible and compact implementations in unitary converters using MPLC. We further investigate converters with fewer phase-shifter layers than the theoretical minimum and show that they function as approximate converters by tolerating predefined error thresholds, achieving sub-quadratic scaling. To identify efficient architectures for implementing general linear matrices using unitary converters, we compare block-encoding (BE) and singular-value decomposition (SVD) schemes. Results indicate that BE exhibits superior iterative configuration properties. By characterizing the trade-offs between entropy of mode mixers, number of phase shifters, and error tolerance, this study provides a framework for designing scalable and efficient approximate optical converters. Finally, using model quantization techniques, we demonstrate that the proposed method reduces the number of required phase shifters by half while preserving the accuracy of a text classification model, highlighting the effectiveness of error-tolerant model training for analog computing platforms.
Programmable unitary photonic devices are emerging as promising tools to implement unitary transformation for quantum information processing, machine learning, and optical communication. These devices typically use a rectangular mesh of Mach-Zehnder interferometers, which has a clear mathematical structure and can be configured deterministically. However, this mesh architecture is sensitive to fabrication errors, and the correction techniques are still under investigation. In contrast, the multiplane light-conversion (MPLC) architecture is more robust against fabrication errors, but a deterministic method for configuring the converter has not yet been developed due to its complex mathematical structure. In this work, we propose a fast iterative configuration method for MPLC, following the mathematical review of the matrix distance and proposal of an alternative norm. We show through numerical simulations that adding a few redundant layers significantly improves the convergence of the MPLC architecture, making it a practical and attractive option. We also consider the effects of finite resolution and cross-talk in phase shifters in our simulations. In addition, we propose a phase-insensitive distance suited for applications using only intensity detections. Our method demonstrates orders of magnitude better accuracy and a 20-fold speedup compared to previous approaches.
High-dimensional entanglement offers a variety of advantages for both fundamental and applied applications in quantum information science. A central building block for such applications is a programmable processor of entangled states, which is crucial for the certification, manipulation, and distribution of high-dimensional entanglement. The leading technology for processing photons is integrated multiport interferometers. However, such devices are incompatible with structured light and their scaling is challenging. Here, we unlock these limitations by demonstrating a reconfigurable processor of entangled photons in high dimensions that is based on multiplane light conversion (MPLC), a technology that has recently been developed for multiplexing hundreds of spatial modes for classical communication. We use our programmable MPLC platform to certify three-dimensional entanglement in two mutually unbiased bases, perform 400 arbitrary random transformations on entangled photons, and convert the mode basis of entangled photons for entanglement distribution.