Fragment classification is efficiently learnable by quantum neural networks under suitable conditions but resists known classical dequantization techniques.
Feedback-driven quantum reservoir com- puting for time-series analysis.PRX Quantum, 5: 040325, Nov 2024
6 Pith papers cite this work. Polarity classification is still indexing.
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An algorithm converts topological data of 2D bulk stabilizer codes into 1D boundary subsystem codes via operator algebra and normal forms, enabling automatic generation of boundaries and defects demonstrated on toric, color, and other codes.
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.
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.
Absence of coherent superpositions in the coherent-state basis is a sufficient condition for Wigner function positivity, necessary and sufficient for cat states and limiting cases of higher-order cat states.
Demonstration of dual-chip InP-SiN time-bin BB84 QKD system with QBER below 4% and kbps secret key rates over 150-250 km fiber using finite-key security analysis.
citing papers explorer
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Fragmentation is Efficiently Learnable by Quantum Neural Networks
Fragment classification is efficiently learnable by quantum neural networks under suitable conditions but resists known classical dequantization techniques.
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Operator algebra and algorithmic construction of boundaries and defects in (2+1)D topological Pauli stabilizer codes
An algorithm converts topological data of 2D bulk stabilizer codes into 1D boundary subsystem codes via operator algebra and normal forms, enabling automatic generation of boundaries and defects demonstrated on toric, color, and other codes.
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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.
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Operational criterion for Wigner function negativity
Absence of coherent superpositions in the coherent-state basis is a sufficient condition for Wigner function positivity, necessary and sufficient for cat states and limiting cases of higher-order cat states.
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Time-Bin BB84 QKD System Using Indium Phosphide and Silicon Nitride Photonic Integrated Circuits
Demonstration of dual-chip InP-SiN time-bin BB84 QKD system with QBER below 4% and kbps secret key rates over 150-250 km fiber using finite-key security analysis.