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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 computers can be used to calculate the electronic structure and estimate the ground state energy of many-electron molecular systems. In the present study, we implement the Variational Quantum Eigensolver (VQE) algorithm, as a hybrid…

Quantum Physics · Physics 2024-11-11 Hamid Reza Naeij , Erfan Mahmoudi , Hossein Davoodi Yeganeh , Mohsen Akbari

The variational quantum eigensolver (or VQE) uses the variational principle to compute the ground state energy of a Hamiltonian, a problem that is central to quantum chemistry and condensed matter physics. Conventional computing methods are…

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

Variational Quantum Eigensolver (VQE) provides a lucrative platform to determine molecular energetics in near-term quantum devices. While the VQE is traditionally tailored to determine the ground state wavefunction with the underlying…

Quantum Physics · Physics 2023-08-22 Dibyendu Mondal , Rahul Maitra

The accurate prediction and understanding of molecular energy and chemical reactivity are fundamental pursuits in the field of molecular quantum chemistry. With the limitations of the current noisy intermediate scale quantum computer (NISQ)…

Chemical Physics · Physics 2023-04-04 Abdul Kalam , Ashok Kumar , Prasanta K. Panigrahi

Quantum computing presents a promising path toward precise quantum chemical simulations, particularly for systems that challenge classical methods. This work investigates the performance of the Variational Quantum Eigensolver (VQE) in…

Quantum Physics · Physics 2025-10-28 Zakaria Boutakka , Nouhaila Innan , Muhammed Shafique , Mohamed Bennai , Z. Sakhi

Quantum systems have historically been formidable to simulate using classical computational methods, particularly as the system size grows. In recent years, advancements in quantum computing technology have offered new opportunities for…

Quantum Physics · Physics 2023-09-06 Jinao Wang , Rimika Jaiswal

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), a variational algorithm to obtain an approximated ground state of a given Hamiltonian, is an appealing application of near-term quantum computers. The original work [A. Peruzzo et al.; \textit{Nat.…

Quantum Physics · Physics 2019-11-06 Ken M Nakanishi , Kosuke Mitarai , Keisuke Fujii

The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There…

Quantum Physics · Physics 2023-03-22 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

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

The variational quantum eigensolver (VQE) algorithm, designed to calculate the energy of molecular ground states on near-term quantum computers, requires specification of symmetries that describe the system, e.g. spin state and number of…

Quantum Physics · Physics 2020-06-18 Gabriel Greene-Diniz , David Muñoz Ramo

Variational Quantum Eigensolvers (VQEs) represent a promising approach to computing molecular ground states and energies on modern quantum computers. These approaches use a classical computer to optimize the parameters of a trial wave…

Solving interacting multi-particle systems is a central challenge in quantum chemistry and condensed matter physics. In this work, we investigate the computation of ground states and ground-state energies for the He-H+ and H2O molecules…

Quantum Physics · Physics 2026-01-08 Luca Ion , Adam Smith

The problem of finding the ground state energy of a Hamiltonian using a quantum computer is currently solved using either the quantum phase estimation (QPE) or variational quantum eigensolver (VQE) algorithms. For precision $\epsilon$, QPE…

Quantum Physics · Physics 2019-04-16 Daochen Wang , Oscar Higgott , Stephen Brierley

By design, the variational quantum eigensolver (VQE) strives to recover the lowest-energy eigenvalue of a given Hamiltonian by preparing quantum states guided by the variational principle. In practice, the prepared quantum state is…

Quantum Physics · Physics 2021-06-29 Daniel Claudino , Jerimiah Wright , Alexander J. McCaskey , Travis S. Humble

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…

While numerical simulations are presented in most papers introducing new methods to enhance the VQE performance, comprehensive, comparative, and applied studies remain relatively rare. We present a comprehensive, yet concise guide for the…

Reflecting the increasing interest in quantum computing, the variational quantum eigensolver (VQE) has attracted much attentions as a possible application of near-term quantum computers. Although the VQE has often been applied to quantum…

Quantum Physics · Physics 2022-12-07 Yasutaka Nishida , Fumihiko Aiga
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