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Atomic nuclei are important laboratories for exploring and testing new insights into the universe, such as experiments to directly detect dark matter or explore properties of neutrinos. The targets of interest are often heavy, complex…

High Energy Physics - Theory · Physics 2021-09-21 Michael J. Cervia , A. B. Balantekin , S. N. Coppersmith , Calvin W. Johnson , Peter J. Love , C. Poole , K. Robbins , M. Saffman

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

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

The Variational Quantum Eigensolver (VQE) algorithm, as applied to finding the ground state of a Hamiltonian, is particularly well-suited for deployment on noisy intermediate-scale quantum (NISQ) devices. Here we utilize the VQE algorithm…

Quantum Physics · Physics 2024-11-28 Younes Javanmard , Ugne Liaubaite , Tobias J. Osborne , Xusheng Xu , Man-Hong Yung

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…

We present a novel quantum algorithm for approximating the ground-state in quantum many-body systems, particularly suited for Noisy Intermediate-Scale Quantum (NISQ) devices. Our approach integrates Variational Quantum Eigensolvers (VQE)…

Quantum Physics · Physics 2024-03-18 Yihao Liu , Min-Quan He , Z. D. Wang

Variational Quantum Eigensolvers (VQEs) are a powerful class of hybrid quantum-classical algorithms designed to approximate the ground state of a quantum system described by its Hamiltonian. VQEs hold promise for various applications,…

Quantum Physics · Physics 2025-02-04 Kim A. Nicoli , Luca J. Wagner , Lena Funcke

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 Variational Quantum Eigensolver (VQE) is one of the most promising and widely used algorithms for exploiting the capabilities of current Noisy Intermediate-Scale Quantum (NISQ) devices. However, VQE algorithms suffer from a plethora of…

We use the Lipkin-Meshkov-Glick (LMG) model and the valence-space nuclear shell model to examine the likely performance of variational quantum eigensolvers in nuclear-structure theory. The LMG model exhibits both a phase transition and…

Nuclear Theory · Physics 2022-06-30 A. M. Romero , J. Engel , Ho Lun Tang , Sophia E. Economou

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…

Variational quantum algorithms exploit the features of superposition and entanglement to optimize a cost function efficiently by manipulating the quantum states. They are suitable for noisy intermediate-scale quantum (NISQ) computers that…

Quantum Physics · Physics 2023-08-29 Yunya Liu , Jiakun Liu , Jordan R. Raney , Pai Wang

We simulate the Lipkin-Meshkov-Glick (LMG) model using the Variational-Quantum-Eigensolver (VQE) algorithm on a neutral atom quantum computer. We test the ground-state energy of spin systems with up to 15 spins. Two different encoding…

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

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm for preparing ground states in the current era of noisy devices. The classical component of the algorithm requires a large number of measurements on…

Quantum Physics · Physics 2025-03-27 Akib Karim , Shaobo Zhang , Muhammad Usman

The Variational Quantum Eigensolver (VQE) is a promising algorithm for quantum computing applications in chemistry and materials science, particularly in addressing the limitations of classical methods for complex systems. This study…

Quantum Physics · Physics 2025-02-25 Nia Pollard , Kamal Choudhary

In this work, we introduce a new qubit mapping strategy for the Variational Quantum Eigensolver (VQE) applied to nuclear shell model calculations, where each Slater determinant (SD) is mapped to a qubit, rather than assigning qubits to…

Nuclear Theory · Physics 2026-04-14 Chandan Sarma , Paul Stevenson

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

Variational quantum eigensolver (VQE) emerged as a first practical algorithm for near-term quantum computers. Its success largely relies on the chosen variational ansatz, corresponding to a quantum circuit that prepares an approximate…

Quantum Physics · Physics 2020-07-10 D. Chivilikhin , A. Samarin , V. Ulyantsev , I. Iorsh , A. R. Oganov , O. Kyriienko
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