Hybrid quantum-classical reservoir computing enables nonlinear temporal processing of quantum states and outperforms pure quantum or classical reservoirs in both full-tomography and single-axis measurement regimes.
Nonlinear input transformations are ubiquitous in quantum reservoir computing.Neuromorphic Com- puting and Engineering, 2(1):014008, feb 2022
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Introduces tunable partial-SWAP for controllable memory capacity in quantum reservoir networks, modeled as controlled amplitude-damping and validated via STMC and NARMA-5 benchmarks on simulators and IBM QPUs.
A quantum echo-state network is implemented on NISQ superconducting qubits and shown to predict long chaotic trajectories from the Lorenz system with memory persisting over 100 times the median T1/T2 time.
citing papers explorer
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Temporal processing of quantum states with hybrid quantum-classical reservoirs
Hybrid quantum-classical reservoir computing enables nonlinear temporal processing of quantum states and outperforms pure quantum or classical reservoirs in both full-tomography and single-axis measurement regimes.
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Controllable Quantum Memory Capacity in Quantum Reservoir Networks with Tunable partial-SWAPs
Introduces tunable partial-SWAP for controllable memory capacity in quantum reservoir networks, modeled as controlled amplitude-damping and validated via STMC and NARMA-5 benchmarks on simulators and IBM QPUs.
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Quantum Observers: A NISQ Hardware Demonstration of Chaotic State Prediction Using Quantum Echo-state Networks
A quantum echo-state network is implemented on NISQ superconducting qubits and shown to predict long chaotic trajectories from the Lorenz system with memory persisting over 100 times the median T1/T2 time.