Noisy Bayesian optimization for variational quantum eigensolvers
Published: May 16, 2022
Abstract
The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm used to find the ground state of a Hamiltonian using variational methods. In the context of this Lattice symposium, the procedure can be used to study lattice gauge theories (LGTs) in the Hamiltonian formulation. Bayesian optimization (BO) based on Gaussian process regression (GPR) is a powerful algorithm for finding the global minimum of a cost function, e.g. the...
Paper Details
Title
Noisy Bayesian optimization for variational quantum eigensolvers
Published Date
May 16, 2022
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