Quantum reservoir computing with a single nonlinear oscillator

Realizing the promise of quantum information processing remains a daunting task given omnipresence noise and error. Adapting noise-resilient classical computing modalities to mechanics may be viable path towards near-term applications in noisy intermediate-scale era. Here, we propose continuous variable reservoir single nonlinear oscillator. Through numerical simulation our model demonstrate quantum-classical performance improvement identify its likely source: nonlinearity measurement. Beyond computing, this result impact interpretation results across machine learning. We study how depends on Hilbert space dimension, it is impacted by injected noise, briefly comment experimental implementation. Our show that oscillator an attractive modality for hardware.Received 7 May 2020Accepted January 2021DOI:https://doi.org/10.1103/PhysRevResearch.3.013077Published American Physical Society under terms Creative Commons Attribution 4.0 International license. Further distribution work must maintain attribution author(s) published article's title, journal citation, DOI.Published SocietyPhysics Subject Headings (PhySH)Research AreasMachine learningQuantum computationQuantum with variablesQuantum InformationCondensed Matter, Materials & Applied PhysicsStatistical PhysicsInterdisciplinary PhysicsGeneral Physics