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The Variational Quantum Eigensolver (VQE) is widely regarded as a promising algorithm for calculating ground states of quantum systems that are intractable for classical computers. This promise is typically motivated by the hope of…

Quantum Physics · Physics 2026-04-13 Manuel Hagelueken , David A. Kreplin , Florian Wieland , Marco F. Huber , Marco Roth

To understand the properties and interactions of materials, and determining the ground state energies is one of the important challenges in quantum chemistry, materials science, and quantum mechanics, where quantum computing can play an…

Quantum Physics · Physics 2025-04-15 Badie Ghavami , Forouzan Mirmasoudi

Quantum computing has emerged as a promising technology for solving problems that are intractable for classical computers. In this study, we introduce quantum computing and implement the Variational Quantum Eigensolver (VQE) algorithm using…

Quantum Physics · Physics 2023-05-12 Maomin Qing , Wei Xie

In the noisy-intermediate-scale-quantum era, Variational Quantum Eigensolver (VQE) is a promising method to study ground state properties in quantum chemistry, materials science, and condensed physics. However, general quantum eigensolvers…

Quantum Physics · Physics 2023-09-27 Yusen Wu , Zigeng Huang , Jinzhao Sun , Xiao Yuan , Jingbo B. Wang , Dingshun Lv

The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-classical computational approach to find eigenvalues and eigenvalues of a Hamiltonian. VQE has been proposed as an alternative to fully quantum algorithms such…

Quantum Physics · Physics 2021-09-01 Dmitry A. Fedorov , Bo Peng , Niranjan Govind , Yuri Alexeev

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-term quantum computers. Although the eigenenergies are…

Quantum Physics · Physics 2020-02-12 Kosuke Mitarai , Yuya O. Nakagawa , Wataru Mizukami

The variational quantum eigensolver (VQE), a type of variational quantum algorithm, is a hybrid quantum-classical algorithm to find the lowest-energy eigenstate of a particular Hamiltonian. We investigate ways to optimize the VQE solving…

Quantum Physics · Physics 2024-10-30 Adam Hutchings , Eric Yarnot , Xinpeng Li , Qiang Guan , Ning Xie , Shuai Xu , Vipin Chaudhary

Current quantum computers are limited in the number of qubits and coherence time, constraining the algorithms executable with sufficient fidelity. The variational quantum eigensolver (VQE) is an algorithm to find an approximate ground state…

Quantum Physics · Physics 2023-01-24 Luca Erhart , Kosuke Mitarai , Wataru Mizukami , Keisuke Fujii

Hybrid quantum-classical algorithms have been proposed as a potentially viable application of quantum computers. A particular example - the variational quantum eigensolver, or VQE - is designed to determine a global minimum in an energy…

Quantum Physics · Physics 2020-08-05 Alexey Uvarov , Jacob Biamonte , Dmitry Yudin

Variational quantum eigensolvers (VQEs) are among the most promising quantum algorithms for solving electronic structure problems in quantum chemistry, particularly during the Noisy Intermediate-Scale Quantum (NISQ) era. In this study, we…

Quantum Physics · Physics 2026-05-07 Abel Carreras , David Casanova , Román Orús

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 active research area is the construction of a parametrized trial…

Quantum mechanics has introduced a new theoretical framework for the study of molecules, enabling the prediction of properties and dynamics through the solution of the Schr\"odinger equation applied to these systems. However, solving this…

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-date, experimental demonstrations of algorithms such as…

Chemical Physics · Physics 2023-10-18 Joel Bierman , Yingzhou Li , Jianfeng Lu

The ability of near-term quantum computers to represent classically-intractable quantum states has brought much interest in using such devices for estimating the ground and excited state energies of fermionic Hamiltonians. The usefulness of…

Quantum Physics · Physics 2021-06-10 Maxwell D. Radin , Peter Johnson

We use the Variational Quantum Eigensolver (VQE) as implemented in the Qiskit software package to compute the ground state energy of small molecules derived from water, H$_2$O, and hydrogen cyanide, HCN. The work aims to benchmark…

Quantum Physics · Physics 2021-07-07 P. Lolur , M. Rahm , M. Skogh , L. García-Álvarez , G. Wendin

The variational quantum eigensolver (VQE) has emerged as one of the leading quantum algorithms for solving electronic structure problems on near-term noisy intermediate-scale quantum devices. However, its practical application to quantum…

Chemical Physics · Physics 2026-03-24 Yanxian Tao , Lingyun Wan , Jie Liu

Harnessing the full power of nascent quantum processors requires the efficient management of a limited number of quantum bits with finite lifetime. Hybrid algorithms leveraging classical resources have demonstrated promising initial results…

A family of Variational Quantum Eigensolver (VQE) methods is designed to maximize the resource of existing noisy intermediate-scale quantum (NISQ) devices. However, VQE approaches encounter various difficulties in simulating molecules of…

Chemical Physics · Physics 2022-08-16 M. D. Sapova , A. K. Fedorov

The variational quantum eigensolver (VQE) is a hybrid quantum-classical variational algorithm that produces an upper-bound estimate of the ground-state energy of a Hamiltonian. As quantum computers become more powerful and go beyond the…

The Variational Quantum Eigensolver (VQE) is a promising hybrid algorithm, utilizing both quantum and classical computers to obtain the ground state energy of molecules. In this context, this study applies VQE to investigate the ground…