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The variational quantum eigensolver (VQE) is one of the most promising algorithms to find eigenvalues and eigenvectors of a given Hamiltonian on noisy intermediate-scale quantum (NISQ) devices. A particular application is to obtain ground…

The Variational Quantum Eigensolver (VQE) is a promising algorithm for future Noisy Intermediate-Scale Quantum (NISQ) devices to simulate chemical systems. In this paper, we consider the classical simulation of the iterative Qubit Coupled…

Quantum Physics · Physics 2025-02-27 Damian S. Steiger , Thomas Häner , Scott N. Genin , Helmut G. Katzgraber

Molecular quantum-dot Cellular Automata (QCA) may provide low-power, high-speed computational hardware for processing classical information. Simulation and modeling play an important role in the design of QCA circuits because fully-coherent…

Quantum Physics · Physics 2025-10-15 Nischal Binod Gautam , Enrique P. Blair

The realization of quantum advantage with noisy-intermediate-scale quantum (NISQ) machines has become one of the major challenges in computational sciences. Maintaining coherence of a physical system with more than ten qubits is a critical…

Here we present a quantum algorithm for clustering data based on a variational quantum circuit. The algorithm allows to classify data into many clusters, and can easily be implemented in few-qubit Noisy Intermediate-Scale Quantum (NISQ)…

Quantum Physics · Physics 2024-01-08 Pablo Bermejo , Roman Orus

The Variational Quantum Eigensolver (VQE) is a promising quantum algorithm for applications in chemistry within the Noisy Intermediate-Scale Quantum (NISQ) era. The ability for a quantum computer to simulate electronic structures with high…

The state-of-the-art quantum computing hardware has entered the noisy intermediate-scale quantum (NISQ) era. Having been constrained by the limited number of qubits and shallow circuit depth, NISQ devices have nevertheless demonstrated the…

Quantum Physics · Physics 2022-06-23 Guanglei Xu , Yi-Bin Guo , Xuan Li , Zong-Sheng Zhou , Hai-Jun Liao , T. Xiang

Solving electronic structure problems is considered one of the most promising applications of quantum computing. However, due to limitations imposed by the coherence time of qubits in the Noisy Intermediate Scale Quantum (NISQ) era or the…

Quantum Physics · Physics 2025-03-20 Shuo Sun , Chandan Kumar , Kevin Shen , Elvira Shishenina , Christian B. Mendl

The variational quantum eigensolver (VQE) is one of the most representative quantum algorithms in the noisy intermediate-size quantum (NISQ) era, and is generally speculated to deliver one of the first quantum advantages for the…

Quantum Physics · Physics 2022-04-13 Shi-Xin Zhang , Zhou-Quan Wan , Chee-Kong Lee , Chang-Yu Hsieh , Shengyu Zhang , Hong Yao

The Variational Quantum Eigensolver (VQE) algorithm has been developed to target near term Noisy Intermediate Scale Quantum (NISQ) computers as a method to find the eigenvalues of Hamiltonians. Unlike fully quantum algorithms such as…

Quantum Physics · Physics 2026-02-13 Taylor Harville , Rishu Khurana , Vitor F. Grizzi , Cong Liu

Variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for noisy intermediate-scale quantum (NISQ) computers. It is promising for quantum chemical calculations (QCC) because it can calculate the ground-state…

Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled cluster ansatz, we demonstrate that…

Variational quantum eigensolver (VQE) for electronic structure calculations is believed to be one major potential application of near term quantum computing. Among all proposed VQE algorithms, the unitary coupled cluster singles and doubles…

Quantum Physics · Physics 2020-10-13 Rongxin Xia , Sabre Kais

The variational quantum eigensolver (VQE) algorithm combines the ability of quantum computers to efficiently compute expectation values with a classical optimization routine in order to approximate ground state energies of quantum systems.…

The Variational Quantum Algorithms (VQAs) are hybrid quantum-classical algorithms and they can be used in the Nosiy Intermadiate Scale Quantum (NISQ) devises. The Variational Quantum Eigensolver (VQE) was suggested as a first VQA. VQE is…

Quantum Physics · Physics 2026-03-09 Murat Kurt , Ayda Kaltehei , Selçuk Çakmak , Azmi Gençten

Variational quantum algorithms have been one of the most intensively studied applications for near-term quantum computing applications. The noisy intermediate-scale quantum (NISQ) regime, where small enough algorithms can be run…

Quantum Physics · Physics 2023-01-19 Sebastian Brandhofer , Simon Devitt , Ilia Polian

Understanding complex chemical systems -- such as biomolecules, catalysts, and novel materials -- is a central goal of quantum simulations. Near-term strategies hinge on the use of variational quantum eigensolver (VQE) algorithms combined…

Quantum Physics · Physics 2023-08-02 Joshua Goings , Luning Zhao , Jacek Jakowski , Titus Morris , Raphael Pooser

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

Current noisy intermediate-scale quantum (NISQ) devices remain limited in their ability to perform accurate quantum chemistry simulations due to restricted numbers of high-fidelity qubits and short coherence times. To overcome these…

Quantum Physics · Physics 2026-04-23 Yuhan Zheng , Yibin Guo , Huili Zhang , Jie Liu , Xiongzhi Zeng , Xiaoxia Cai , Zhenyu Li , Jinlong Yang

Variational quantum eigensolver (VQE) is promising to show quantum advantage on near-term noisy-intermediate-scale quantum (NISQ) computers. One central problem of VQE is the effect of noise, especially the physical noise on realistic…

Quantum Physics · Physics 2021-09-30 Jinfeng Zeng , Zipeng Wu , Chenfeng Cao , Chao Zhang , Shiyao Hou , Pengxiang Xu , Bei Zeng
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