The original variational quantum eigensolver (VQE) typically minimizes energy with hybrid
quantum-classical optimization that aims to find the ground state. Here, we propose a VQE …

A variational quantum eigensolver (VQE) optimizes parametrized eigenstates of a
Hamiltonian on a quantum processor by updating parameters with a classical computer …

The variational quantum eigensolver (VQE), a variational algorithm to obtain an
approximated ground state of a given Hamiltonian, is an appealing application of near-term …

Variational quantum eigensolvers (VQEs) represent a powerful class of hybrid quantum-
classical algorithms for computing molecular energies. Various numerical issues exist for …

Near-term quantum computers will be limited in the number of qubits on which they can
process information as well as the depth of the circuits that they can coherently carry out. To …

The variational quantum eigensolver (VQE) stands as a prominent quantum-classical hybrid
algorithm for near-term quantum computers to obtain the ground states of molecular …

We present a hybrid classical-quantum algorithm to solve optimization problems in current
quantum computers, whose basic idea is to assist variational quantum eigensolvers (VQE) …

The variational quantum eigensolver (VQE) is a promising algorithm to compute eigenstates
and eigenenergies of a given quantum system that can be performed on a near-term …

Variational quantum eigensolvers (VQEs) show promise for tackling complex quantum
chemistry challenges and realizing quantum advantages. However, in VQE, the …

The variational quantum eigensolver (VQE) and its variants, which is a method for finding
eigenstates and eigenenergies of a given Hamiltonian, are appealing applications of near …