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Quantum Autoencoder-Driven Hamiltonian Reduction for VQE Applications

Ankit Khandelwal, M R Nirmal, M Girish Chandra

Published Jan 1, 2025• 0 citations

Abstract

We propose a quantum machine learning-based method to compress molecular Hamiltonians and efficiently compute ground-state energies (GSEs) using the variational quantum eigensolver (VQE), significantly reducing resource requirements.

DOI: 10.1364/quantum.2025.qtu3a.22

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