Integral decimation builds spectral tensor train representations of integrands via quantum gate sequences to achieve polynomial-time evaluation of high-dimensional integrals for statistical mechanics and quantum dynamics.
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Quantum-inspired deep neural networks extract Compton form factors from JLab data with higher predictive accuracy and tighter uncertainties than classical DNNs on pseudodata benchmarks, then applied to real measurements.
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The Integral Decimation Method for Quantum Dynamics and Statistical Mechanics
Integral decimation builds spectral tensor train representations of integrands via quantum gate sequences to achieve polynomial-time evaluation of high-dimensional integrals for statistical mechanics and quantum dynamics.
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Compton Form Factor Extraction using Quantum Deep Neural Networks
Quantum-inspired deep neural networks extract Compton form factors from JLab data with higher predictive accuracy and tighter uncertainties than classical DNNs on pseudodata benchmarks, then applied to real measurements.