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4 October 2024 Quantum reservoir computing for time series processing
Jorge Garcia-Beni, Gian Luca Giorgi, Miguel C. Soriano, Roberta Zambrini
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Proceedings Volume PC13148, Quantum Communications and Quantum Imaging XXII; PC131480E (2024) https://doi.org/10.1117/12.3027999
Event: Optical Engineering + Applications, 2024, San Diego, California, United States
Abstract
Photonic quantum technologies are noteworthy candidates in the achievement of quantum advantage for quantum information processing. Moreover, their capabilities for fast signal processing have attracted the interest of researchers in the field of quantum reservoir computing (QRC). In our research, we propose a scalable quantum photonic platform for QRC suitable for solving temporal tasks. In our platform, an optical pulse recirculating through an optical cavity creates a quantum memory, thus not needing external classical storage. A classical signal is sequentially encoded in the quantum field fluctuations of external optical pulses, which interact with the cavity pulse using a beam-splitter (BS). A nonlinear crystal is placed inside the cavity to generate non-trivial dynamics and create a quantum network of entangled modes. A homodyne detector is placed at one of the output paths of the BS for sequential data collecting. Our work focuses on the ability to process classical signals in real time and the noise robustness of our architecture.
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Jorge Garcia-Beni, Gian Luca Giorgi, Miguel C. Soriano, and Roberta Zambrini "Quantum reservoir computing for time series processing", Proc. SPIE PC13148, Quantum Communications and Quantum Imaging XXII, PC131480E (4 October 2024); https://doi.org/10.1117/12.3027999
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KEYWORDS
Reservoir computing
Quantum computing
Quantum processing
Pulse signals
Homodyne detection
Photons
Quantum advantages
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