Author

Quoc-Hoan Tran

2 papers indexed here

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#machine learning Preprint Mar 2025

Reducing QPU Calls in Variational Quantum Algorithms via Classical Offloading of Gradient Computation

This work evaluates ground-state estimation of 6- to 18-qubit Hamiltonians using the Variational Quantum Eigensolver (VQE) and quantum phase classification for Hamiltonians up to 12 qubits and uses these methods as a warm-start pretraining strategy for Hamiltonians with exponential-dimensional dynamical Lie algebras.

Rahul Bhowmick, Harsh Wadhwa, Avinash Singh et al. · 4 citations

#machine learning Preprint Sep 2025

Provably scalable learning from quantum many-body data via locality

A scalable ML framework that efficiently learns from quantum many-body data by leveraging the exponential decay of correlations prevalent in noncritical systems is proposed, and it is rigorously proved that the GLQK substantially improves the sample complexity in the system size $n$ over the existing shadow kernel.

Koki Chinzei, Quoc-Hoan Tran, Norifumi Matsumoto et al. · 2 citations