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Role of coherence in many-body Quantum Reservoir Computing

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arxiv 2409.17734 v1 pith:5T43V3MT submitted 2024-09-26 quant-ph

classification quant-ph
keywords quantumreservoircoherencecomputingeffectsperformancedifferentmany-body
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Energetic Cost of Temporal Information Processing in Quantum Reservoirs

    quant-ph 2026-08 conditional novelty 6.0 of 10

    In weakly interacting quantum reservoirs, the average switching work per input is controlled by the local spin response, while interactions mediate the task-dependent trade-off between memory and nonlinearity.

  2. Quantum reservoir computing in atomic lattices

    quant-ph 2024-11 conditional novelty 6.0 of 10

    A homogeneous one-dimensional Bose-Hubbard chain can act as a quantum reservoir computer, matching or beating disordered chains on memory and nonlinear tasks.

  3. Input-dependence in quantum reservoir computing

    quant-ph 2024-12 conditional novelty 4.0 of 10

    Quantum reservoir filters are injective if the state update is input-invertible at reachable states, reducible to a rank condition in affine quantum systems.

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