Role of coherence in many-body Quantum Reservoir Computing

Abstract

Quantum Reservoir Computing (QRC) offers potential advantages over classical reservoir computing, including inherent processing of quantum inputs and a vast Hilbert space for state exploration. Yet, the relation between the performance of reservoirs based on complex and many-body quantum systems and non-classical state features is not established. Through an extensive analysis of QRC based on a transverse-field Ising model we show how different quantum effects, such as quantum coherence and correlations, contribute to improving the performance in temporal tasks, as measured by the Information Processing Capacity. Additionally, we critically assess the impact of finite measurement resources and noise on the reservoir's dynamics in different regimes, quantifying the limited ability to exploit quantum effects for increasing damping and noise strengths. Our results reveal a monotonic relationship between reservoir performance and coherence, along with the importance of quantum effects in the ergodic regime.

19 pages (9 main article + 10 references and appendix), 17 figures (7 main article + 10 appendix)

References in corpus (43)

• Quantum Computing in the NISQ era and beyond
• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• A computable measure of entanglement
• Supervised learning with quantum enhanced feature spaces
• Machine learning and the physical sciences
• Many-body localization, thermalization, and entanglement
• Noisy intermediate-scale quantum (NISQ) algorithms
• Quantum Coherence as a Resource
• The distribution of the ratio of consecutive level spacings in random matrix ensembles
• A high-bias, low-variance introduction to Machine Learning for physicists
• Many-body localization in a quantum simulator with programmable random disorder
• Dephasing assisted transport: Quantum networks and biomolecules
• Unified View of Quantum and Classical Correlations
• Quantum Simulators: Architectures and Opportunities
• Harnessing disordered quantum dynamics for machine learning
• Quantum Coherence and Ergotropy
• Spectral features of a many-body localized system weakly coupled to a heat bath
• Opportunities in Quantum Reservoir Computing and Extreme Learning Machines
• The role of quantum coherence in non-equilibrium entropy production
• Robustness of many-body localization in the presence of dissipation
• Dynamics of a Many-Body-Localized System Coupled to a Bath
• The role of coherence in the non-equilibrium thermodynamics of quantum systems
• Experimental quantum memristor
• Quantum reservoir computing with a single nonlinear oscillator
• Dynamical phase transitions in quantum reservoir computing
• Quantum neuromorphic computing
• Time Series Quantum Reservoir Computing with Weak and Projective Measurements
• Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing
• Finite-Time Quantum Landauer Principle and Quantum Coherence
• Information Processing Capacity of Spin-Based Quantum Reservoir Computing Systems
• Scalable photonic platform for real-time quantum reservoir computing
• Demonstrating quantum coherence and metrology that is resilient to transversal noise
• Quantum coherence as a signature of chaos
• Dissipation as a resource for Quantum Reservoir Computing
• Learning Nonlinear Input-Output Maps with Dissipative Quantum Systems
• The Reservoir Learning Power across Quantum Many-Boby Localization Transition
• Quantum reservoir computation utilising scale-free networks
• Quantum coherence and the localization transition
• Quantum reservoir computing in finite dimensions
• Exploring quantum mechanical advantage for reservoir computing
• Tackling Sampling Noise in Physical Systems for Machine Learning Applications: Fundamental Limits and Eigentasks
• Quantum Coherence in Ergodic and Many-Body Localized Systems
• Hallmarking quantum states: unified framework for coherence and correlations

Cited by in corpus (6)

• On fundamental aspects of quantum extreme learning machines
• Practical Few-Atom Quantum Reservoir Computing
• Input-dependence in quantum reservoir computing
• Optimal quantum reservoir learning in proximity to universality
• Edge of Many-Body Quantum Chaos in Quantum Reservoir Computing
• Quantum coherence and counterdiabatic quantum computing