A randomized algorithm recovers the exact Pauli decomposition of k-sparse n-qubit matrices in poly(n, k, log(1/δ)) time with high probability under sparse query access.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Hybrid quantum reservoir and projected kernel models report 37-62% MAE reductions versus classical baselines for multi-output energy time-series on NISQ hardware and simulators.
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An efficient Pauli decomposition algorithm for structured matrices
A randomized algorithm recovers the exact Pauli decomposition of k-sparse n-qubit matrices in poly(n, k, log(1/δ)) time with high probability under sparse query access.
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Hybrid Quantum-Classical Machine Learning Algorithms for Multi-Output Time-Series Forecasting at Utility Scale
Hybrid quantum reservoir and projected kernel models report 37-62% MAE reductions versus classical baselines for multi-output energy time-series on NISQ hardware and simulators.