Quantum neuro-inspired computing with loop-based photonic arquitectures

Jorge Garcia-Beni; Gian Luca Giorgi; Miguel C. Soriano; Roberta Zambrini

doi:10.1117/12.3028007

4 October 2024 Quantum neuro-inspired computing with loop-based photonic arquitectures

Jorge Garcia-Beni, Gian Luca Giorgi, Miguel C. Soriano, Roberta Zambrini

Proceedings Volume PC13118, Emerging Topics in Artificial Intelligence (ETAI) 2024; PC131180R (2024) https://doi.org/10.1117/12.3028007
Event: Nanoscience + Engineering, 2024, San Diego, California, United States

Abstract

Reservoir computing (RC) is a neuromorphic machine learning paradigm that is ideal for temporal signal processing and is suitable for analog implementations in physical substrates, including photonic devices. RC has been extended to quantum systems due to the enhanced capabilities provided by an enlarged Hilbert space. In that regard, quantum reservoir computing (QRC) has the advantage of avoiding barren plateaus during training. Photonic architectures have already been studied for QRC applications. In our research, we propose a scalable quantum photonic platform for QRC that is suitable for solving temporal tasks. The physical substrate of our reservoir is an optical pulse, which recirculates through an optical cavity with losses, thus creating a quantum memory. The dissipation device (a beam-splitter) also allows the injection of external information and the weak monitoring of the reservoir. Our work focuses on the ability to process classical signals in real time by creating a physical ensemble of identical pulses inside a fiber and the noise robustness of our architecture by tuning the squeezing produced inside the optical cavity.

Conference Presentation

Citation Download Citation

Jorge Garcia-Beni, Gian Luca Giorgi, Miguel C. Soriano, and Roberta Zambrini "Quantum neuro-inspired computing with loop-based photonic arquitectures", Proc. SPIE PC13118, Emerging Topics in Artificial Intelligence (ETAI) 2024, PC131180R (4 October 2024); https://doi.org/10.1117/12.3028007

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KEYWORDS

Quantum computing

Reservoir computing

Optical computing

Photonic quantum computing

Signal processing

Quantum enhancement

Quantum noise

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