Quantum reservoir computing with a single nonlinear oscillator

Abstract

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.

9 pages, 5 figures

References in corpus (21)

• Quantum Computing in the NISQ era and beyond
• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Charge insensitive qubit design derived from the Cooper pair box
• A Quantum Engineer's Guide to Superconducting Qubits
• Quantum machine learning in feature Hilbert spaces
• Quantum Error Correction for Quantum Memories
• Optoelectronic Reservoir Computing
• Quantum information processing with circuit quantum electrodynamics
• Roads towards fault-tolerant universal quantum computation
• Strong and Tunable Nonlinear Optomechanical Coupling in a Low-Loss System
• Nonlinear and Quantum Optics with Whispering Gallery Resonators
• Harnessing disordered quantum dynamics for machine learning
• Demonstration of quantum advantage in machine learning
• Enhanced nonlinear interactions in quantum optomechanics via mechanical amplification
• Quantum reservoir processing
• Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers
• Boosting computational power through spatial multiplexing in quantum reservoir computing
• Reservoir computing with a single time-delay autonomous Boolean node
• Temporal Information Processing on Noisy Quantum Computers
• Nonlinear nanomechanical resonators for quantum optoelectromechanics
• Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems

Cited by in corpus (47)

• Opportunities in Quantum Reservoir Computing and Extreme Learning Machines
• Dynamical phase transitions in quantum reservoir computing
• Time Series Quantum Reservoir Computing with Weak and Projective Measurements
• Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing
• Natural quantum reservoir computing for temporal information processing
• Hybrid quantum-classical reservoir computing of thermal convection flow
• Learning temporal data with variational quantum recurrent neural network
• A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning
• Scalable photonic platform for real-time quantum reservoir computing
• Reservoir Computing Approach to Quantum State Measurement
• Dissipation as a resource for Quantum Reservoir Computing
• Learning Temporal Quantum Tomography
• Feedback-driven quantum reservoir computing for time-series analysis
• Quantum reservoir computation utilising scale-free networks
• Exploring quantum mechanical advantage for reservoir computing
• Microwave signal processing using an analog quantum reservoir computer
• Machine Learning Potential of a Single Pendulum
• Optimizing quantum noise-induced reservoir computing for nonlinear and chaotic time series prediction
• Reduced-order modeling of two-dimensional turbulent Rayleigh-Bénard flow by hybrid quantum-classical reservoir computing
• Harnessing Quantum Extreme Learning Machines for image classification
• Solving the time-complexity problem and tuning the performance of quantum reservoir computing by artificial memory restriction
• Role of coherence in many-body Quantum Reservoir Computing
• Superpolynomial Quantum Enhancement in Polaritonic Neuromorphic Computing
• Extending echo state property for quantum reservoir computing
• Quantum associative memory with a single driven-dissipative nonlinear oscillator
• Benchmarking the role of particle statistics in Quantum Reservoir Computing
• State estimation with quantum extreme learning machines beyond the scrambling time
• Practical Few-Atom Quantum Reservoir Computing
• Beating the classical phase precision limit using a quantum neuromorphic platform
• Quantum neuromorphic approach to efficient sensing of gravity-induced entanglement
• Neuromorphic computing with a single qudit
• Quantum memories for squeezed and coherent superpositions in a driven-dissipative nonlinear oscillator
• Oscillations enhance time-series prediction in reservoir computing with feedback
• Quantum Next-Generation Reservoir Computing and Its Quantum Optical Implementation
• Neuronal diversity can improve machine learning for physics and beyond
• Liouvillian skin effect in quantum neural networks
• Quantum reservoir probing: an inverse paradigm of quantum reservoir computing for exploring quantum many-body physics
• Estimating many properties of a quantum state via quantum reservoir processing
• Quantum Reservoir Computing for Realized Volatility Forecasting
• Enhanced Predictive Capability for Chaotic Dynamics by Modified Quantum Reservoir Computing
• Harnessing Quantum Dynamics for Robust and Scalable Quantum Extreme Learning Machines
• Neural networks with quantum states of light
• Quantum Transport Reservoir Computing
• Physical reservoir computing using finitely-sampled quantum systems
• Quantum reservoir computing in Jaynes-Cummings models: Nonlinear memory and time-series prediction
• Connection between memory performance and optical absorption in quantum reservoir computing
• The Role of Entanglement in Quantum Reservoir Computing with Coupled Kerr Nonlinear Oscillators