Photonic Unitary Circuits for Quantum Information Processing

ABSTRACT Unitary operations lie at the heart of quantum computing, enabling the manipulation of quantum states in a reversible and coherent manner. In photonic integrated circuits, these operations are realized using photonic waveguide architectures composed of passive beam splitters and reconfigurable phase shifters. This review provides an overview of photonic circuit architectures designed to implement unitary transformations. We examine various design strategies, material platforms, and the current state‐of‐the‐art in realizing high‐fidelity photonic unitaries. In addition, we explore the theoretical underpinnings of photon transport in such circuits, shedding light on the quantum behavior of light in unitary photonic systems. Finally, we introduce a simulation framework for modeling and analyzing these photonic networks, offering a practical tool for research and development in this rapidly growing field.

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Publication Details

Journal
Advanced Quantum Technologies
Published
2026-03-01
DOI
https://doi.org/10.1002/qute.202500812
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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Photonic Unitary Circuits for Quantum Information Processing

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article en

Abstract

ABSTRACT Unitary operations lie at the heart of quantum computing, enabling the manipulation of quantum states in a reversible and coherent manner. In photonic integrated circuits, these operations are realized using photonic waveguide architectures composed of passive beam splitters and reconfigurable phase shifters. This review provides an overview of photonic circuit architectures designed to implement unitary transformations. We examine various design strategies, material platforms, and the current state‐of‐the‐art in realizing high‐fidelity photonic unitaries. In addition, we explore the theoretical underpinnings of photon transport in such circuits, shedding light on the quantum behavior of light in unitary photonic systems. Finally, we introduce a simulation framework for modeling and analyzing these photonic networks, offering a practical tool for research and development in this rapidly growing field.

Advanced Quantum TechnologiesVol. 9(3)
Rochester Institute of Technology (US), University of Missouri–St. Louis (US), Saint Louis University (US), Technische Universität Dresden (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Neural Networks and Reservoir Computing
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