Quantum algorithms achieve polynomial advantage for synchronization estimation and super-polynomial advantage for no-phase-locking certification in higher-order simplicial Kuramoto models under stated assumptions.
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Framework using Butterfly circuits, layer-wise training and parallel parameter-shift reduces QNN training cost to O(log n) circuit evaluations, validated on MIMIC-III clinical data with hardware execution at 16 qubits and simulation at 32.
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Efficient Quantum Algorithms for Higher-Order Coupled Oscillators
Quantum algorithms achieve polynomial advantage for synchronization estimation and super-polynomial advantage for no-phase-locking certification in higher-order simplicial Kuramoto models under stated assumptions.
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Scalable On-Hardware Training of Quantum Neural Networks and Application to Clinical Data Imputation
Framework using Butterfly circuits, layer-wise training and parallel parameter-shift reduces QNN training cost to O(log n) circuit evaluations, validated on MIMIC-III clinical data with hardware execution at 16 qubits and simulation at 32.
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