AI Bibliography
AI Bibliography |
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Govia, L., Ribeill, G., Rowlands, G., Krovi, H., & Ohki, T. (2021). Quantum reservoir computing with a single nonlinear oscillator. Physical Review Research, 3(1), 13077. |
| Resource type: Journal Article BibTeX citation key: Govia2021 View all bibliographic details  |
Categories: Artificial Intelligence, Biological Science, Cognitive Science, Complexity Science, Computer Science, Decision Theory, Engineering, General, Innovation, Military Science, Nanotechnology, Neuroscience Subcategories: Autonomous systems, Chaos theory, Decision making, Edge AI, Fog computing, Machine intelligence, Machine learning, Military research, Neural nets, Neurosymbolic, Quantum computing Creators: Govia, Krovi, Ohki, Ribeill, Rowlands Publisher: Collection: Physical Review Research |
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| Abstract |
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Realizing the promise of quantum information processing remains a daunting task given the omnipresence of noise and error. Adapting noise-resilient classical computing modalities to quantum mechanics may be a viable path towards near-term applications in the noisy intermediate-scale quantum era. Here, we propose continuous variable quantum reservoir computing in a single nonlinear oscillator. Through numerical simulation of our model we demonstrate quantum-classical performance improvement and identify its likely source: the nonlinearity of quantum measurement. Beyond quantum reservoir computing, this result may impact the interpretation of results across quantum machine learning. We study how the performance of our quantum reservoir depends on Hilbert space dimension, how it is impacted by injected noise, and briefly comment on its experimental implementation. Our results show that quantum reservoir computing in a single nonlinear oscillator is an attractive modality for quantum computing on near-term hardware.
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