The Goldilocks Principle of Learning Unitaries by Interlacing Fixed Operators with Programmable Phase Shifters on a Photonic Chip (2403.10469v1)
Abstract: Programmable photonic integrated circuits represent an emerging technology that amalgamates photonics and electronics, paving the way for light-based information processing at high speeds and low power consumption. Programmable photonics provides a flexible platform that can be reconfigured to perform multiple tasks, thereby holding great promise for revolutionizing future optical networks and quantum computing systems. Over the past decade, there has been constant progress in developing several different architectures for realizing programmable photonic circuits that allow for realizing arbitrary discrete unitary operations with light. Here, we systematically investigate a general family of photonic circuits for realizing arbitrary unitaries based on a simple architecture that interlaces a fixed intervening layer with programmable phase shifter layers. We introduce a criterion for the intervening operator that guarantees the universality of this architecture for representing arbitrary $N \times N$ unitary operators with $N+1$ phase layers. We explore this criterion for different photonic components, including photonic waveguide lattices and meshes of directional couplers, which allows the identification of several families of photonic components that can serve as the intervening layers in the interlacing architecture. Our findings pave the way for efficiently designing and realizing novel families of programmable photonic integrated circuits for multipurpose analog information processing.
- Photonic crystals: putting a new twist on light. \JournalTitleNature 386, 143–149, DOI: 10.1038/386143a0 (1997).
- Nanowire photonics. \JournalTitleNature photonics 3, 569–576, DOI: 10.1038/nphoton.2009.184 (2009).
- Shen, Y. et al. Deep learning with coherent nanophotonic circuits. \JournalTitleNature photonics 11, 441–446, DOI: 10.1038/nphoton.2017.93 (2017).
- Integrated photonic fractional convolution accelerator (2023). ArXiv:2307.10976 [physics.optics], 2023.
- Liao, K. et al. Matrix eigenvalue solver based on reconfigurable photonic neural network. \JournalTitleNanophotonics 11, 4089–4099, DOI: 10.1515/nanoph-2022-0109 (2022).
- Photonic memristor for future computing: a perspective. \JournalTitleAdvanced Optical Materials 7, 1900766, DOI: 10.1002/adom.201900766 (2019).
- Integrated optical memristors. \JournalTitleNature Photonics 1–12, DOI: 10.1038/s41566-023-01217-w (2023).
- An on-chip photonic deep neural network for image classification. \JournalTitleNature 606, 501–506, DOI: 10.1038/s41586-022-04714-0 (2022).
- Integrated photonic neural networks: Opportunities and challenges. \JournalTitleACS Photonics DOI: 10.1021/acsphotonics.2c01516 (2023).
- Saygin, M. Y. et al. Robust architecture for programmable universal unitaries. \JournalTitlePhysical review letters 124, 010501, DOI: 10.1103/PhysRevLett.124.010501 (2020).
- Zhou, H. et al. Photonic matrix multiplication lights up photonic accelerator and beyond. \JournalTitleLight: Science & Applications 11, 30, DOI: 10.1038/s41377-022-00717-8 (2022).
- Arbitrary optical wave evolution with fourier transforms and phase masks. \JournalTitleOptics Express 29, 38441–38450, DOI: 10.1364/OE.432787 (2021).
- Madsen, L. S. et al. Quantum computational advantage with a programmable photonic processor. \JournalTitleNature 606, 75–81, DOI: 10.1038/s41586-022-04725-x (2022).
- Harris, N. C. et al. Quantum transport simulations in a programmable nanophotonic processor. \JournalTitleNature Photonics 11, 447–452, DOI: 10.1038/nphoton.2017.95 (2017).
- Photonic quantum information processing: A concise review. \JournalTitleApplied Physics Reviews 6, DOI: 10.1063/1.5115814 (2019).
- Notaros, J. et al. Programmable dispersion on a photonic integrated circuit for classical and quantum applications. \JournalTitleOptics express 25, 21275–21285, DOI: 10.1364/OE.25.021275 (2017).
- Xu, X. et al. Neuromorphic computing based on wavelength-division multiplexing. \JournalTitleIEEE Journal of Selected Topics in Quantum Electronics 29, 1–12, DOI: 10.1109/JSTQE.2022.3203159 (2023).
- Zhu, H. et al. Space-efficient optical computing with an integrated chip diffractive neural network. \JournalTitleNature Communications 13, 1044, DOI: 10.1038/s41467-022-28702-0 (2022).
- Li, X.-K. et al. High-efficiency reinforcement learning with hybrid architecture photonic integrated circuit. \JournalTitleNature Communications 15, 1044, DOI: 10.1038/s41467-024-45305-z (2024).
- Tang, R. et al. Two-layer integrated photonic architectures with multiport photodetectors for high-fidelity and energy-efficient matrix multiplications. \JournalTitleOpt. Express 30, 33940–33954, DOI: 10.1364/OE.457258 (2022).
- Xu, S. et al. Parallel optical coherent dot-product architecture for large-scale matrix multiplication with compatibility for diverse phase shifters. \JournalTitleOptics Express 30, 42057–42068, DOI: 10.1364/OE.471519 (2022).
- Experimental realization of any discrete unitary operator. \JournalTitlePhysical review letters 73, 58, DOI: 10.1103/PhysRevLett.73.58 (1994).
- Miller, D. A. All linear optical devices are mode converters. \JournalTitleOptics express 20, 23985–23993, DOI: 10.1364/OE.20.023985 (2012).
- Miller, D. A. Self-configuring universal linear optical component. \JournalTitlePhotonics Research 1, 1–15, DOI: 10.1364/PRJ.1.000001 (2013).
- Miller, D. A. Self-aligning universal beam coupler. \JournalTitleOptics express 21, 6360–6370, DOI: 10.1364/OE.21.006360 (2013).
- Optimal design for universal multiport interferometers. \JournalTitleOptica 3, 1460–1465, DOI: 10.1364/OPTICA.3.001460 (2016).
- Burgwal, R. et al. Using an imperfect photonic network to implement random unitaries. \JournalTitleOptics Express 25, 28236–28245, DOI: 10.1364/OE.25.028236 (2017).
- The diamond mesh, a phase-error-and loss-tolerant field-programmable mzi-based optical processor for optical neural networks. \JournalTitleOptics Express 28, 23495–23508, DOI: 10.1364/OE.395441 (2020).
- Addressing the programming challenges of practical interferometric mesh based optical processors. \JournalTitleOptics Express 31, 23851–23866, DOI: 10.1364/OE.489493 (2023).
- On, M. B. et al. Programmable integrated photonics for topological hamiltonians. Arxiv:2307.05003 [physics.optics], 2023.
- Wang, M. et al. Topologically protected entangled photonic states. \JournalTitleNanophotonics 8, 1327–1335, DOI: 10.1515/nanoph-2019-0058 (2019).
- Labroille, G. et al. Efficient and mode selective spatial mode multiplexer based on multi-plane light conversion. \JournalTitleOpt. Express 22, 15599–15607, DOI: 10.1364/OE.22.015599 (2014).
- Morizur, J.-F. et al. Programmable unitary spatial mode manipulation. \JournalTitleJOSA A 27, 2524–2531, DOI: 10.1364/JOSAA.27.002524 (2010).
- All-optical synthesis of an arbitrary linear transformation using diffractive surfaces. \JournalTitleLight: Science & Applications 10, 196, DOI: 10.1038/s41377-021-00623-5 (2021).
- Robust integrated optical unitary converter using multiport directional couplers. \JournalTitleJournal of Lightwave Technology 38, 60–66, DOI: 10.1109/JLT.2019.2943116 (2020).
- Tanomura, R. et al. Scalable and robust photonic integrated unitary converter based on multiplane light conversion. \JournalTitlePhysical Review Applied 17, 024071, DOI: 10.1103/PhysRevApplied.17.024071 (2022).
- Universal unitary photonic circuits by interlacing discrete fractional fourier transform and phase modulation. ArXiv:2307.07101 [physics.optics], 2023.
- Demonstration of a 4×\times× 4-port universal linear circuit. \JournalTitleOptica 3, 1348–1357, DOI: 10.1364/OPTICA.3.001348 (2016).
- Taballione, C. et al. 8×\times× 8 reconfigurable quantum photonic processor based on silicon nitride waveguides. \JournalTitleOptics express 27, 26842–26857, DOI: 10.1364/OE.27.026842 (2019).
- Ten-port unitary optical processor on a silicon photonic chip. \JournalTitleACS Photonics 8, 2074–2080, DOI: 10.1021/acsphotonics.1c00419 (2021).
- Taballione, C. et al. A universal fully reconfigurable 12-mode quantum photonic processor. \JournalTitleMaterials for Quantum Technology 1, 035002, DOI: 10.1088/2633-4356/ac168c (2021).
- Multi-wavelength dual-polarization optical unitary processor using integrated multi-plane light converter. \JournalTitleJapanese Journal of Applied Physics 62, SC1029, DOI: 10.35848/1347-4065/acab70 (2023).
- Waveguide-lattice-based architecture for multichannel optical transformations. \JournalTitleOptics Express 29, 26058–26067, DOI: 10.1364/OE.426738 (2021).
- Auto-calibrating universal programmable photonic circuits: hardware error-correction and defect resilience. \JournalTitleOpt. Express 31, 37673–37682, DOI: 10.1364/OE.502226 (2023).
- Learning arbitrary complex matrices by interlacing amplitude and phase masks with fixed unitary operations (2023). ArXiv:2312.05648 [physics.optics], 2023.
- Weimann, S. et al. Implementation of quantum and classical discrete fractional fourier transforms. \JournalTitleNature Communications 7, 11027, DOI: 10.1038/ncomms11027 (2016).
- Analysis of multimode interferometers. \JournalTitleOptics express 24, 22481–22515, DOI: 10.1364/OE.24.022481 (2016).
- Iterative configuration of programmable unitary converter based on few-layer redundant multiplane light conversion. \JournalTitlePhysical Review Applied 19, 054002, DOI: 10.1103/PhysRevApplied.19.054002 (2023).
- Mezzadri, F. How to generate random matrices from the classical compact groups. ArXiv:math-ph/0609050, 2007.
- Levenberg, K. A method for the solution of certain non-linear problems in least squares. \JournalTitleQuarterly of applied mathematics 2, 164–168 (1944).
- Marquardt, D. W. An algorithm for least-squares estimation of nonlinear parameters. \JournalTitleJournal of the society for Industrial and Applied Mathematics 11, 431–441 (1963).
- Integrated reconfigurable unitary optical mode converter using mmi couplers. \JournalTitleIEEE Photonics Technology Letters 29, 971–974, DOI: 10.1109/LPT.2017.2700619 (2017).
- Introduction to Random Matrices: Theory and Practice (Springer, Cham, 2018).
- Huang, W.-P. Coupled-mode theory for optical waveguides: an overview. \JournalTitleJOSA A 11, 963–983, DOI: 10.1364/JOSAA.11.000963 (1994).
- Discretizing light behaviour in linear and nonlinear waveguide lattices. \JournalTitleNature 424, 817–823, DOI: 10.1038/nature01936 (2003).
- Miri, M.-A. Integrated random projection and dimensionality reduction by propagating light in photonic lattices. \JournalTitleOptics Letters 46, 4936–4939, DOI: 10.1364/OL.433101 (2021).
- Simple factorization of unitary transformations. \JournalTitlePhysical Review A 97, 022328, DOI: 10.1103/PhysRevA.97.022328 (2018).