A quantum reservoir network using GHZ-state preparation achieves an order-of-magnitude RMSE improvement over prior QRN designs on latent-space prediction of the Kuramoto-Sivashinsky equation.
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2026 2representative citing papers
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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Leveraging Metrologically Useful States in Quantum Reservoir Networks
A quantum reservoir network using GHZ-state preparation achieves an order-of-magnitude RMSE improvement over prior QRN designs on latent-space prediction of the Kuramoto-Sivashinsky equation.
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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.