[HTML][HTML] The variational quantum eigensolver: a review of methods and best practices

J Tilly, H Chen, S Cao, D Picozzi, K Setia, Y Li, E Grant… - Physics Reports, 2022 - Elsevier
The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

A review on quantum approximate optimization algorithm and its variants

K Blekos, D Brand, A Ceschini, CH Chou, RH Li… - Physics Reports, 2024 - Elsevier
Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

Quantum computing of the nucleus via ordered unitary coupled clusters

O Kiss, M Grossi, P Lougovski, F Sanchez… - Physical Review C, 2022 - APS
The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited
state energy of quantum many-body systems. A key component of the algorithm and an …

On circuit-based hybrid quantum neural networks for remote sensing imagery classification

A Sebastianelli, DA Zaidenberg… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
This article aims to investigate how circuit-based hybrid quantum convolutional neural
networks (QCNNs) can be successfully employed as image classifiers in the context of …