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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…

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

Quantum computers have the potential to transform the ways in which we tackle some important problems. The efforts by companies like Google, IBM and Microsoft to construct quantum computers have been making headlines for years. Equally…

Quantum Physics · Physics 2018-12-05 Raffaele Miceli , Michael McGuigan

We present a composable design scheme for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. Our object-oriented approach is based on constructing an expressive set of common data…

Quantum chemical calculations have attracted much attention as a practical application of quantum computing. Quantum computers can prepare superpositions of electronic states with various numbers of electrons on qubits. This special feature…

Chemical Physics · Physics 2024-03-29 Soichi Shirai , Takahiro Horiba , Hirotoshi Hirai

We compare the performance of different methodologies for finding the ground state of the molecule BeH2. We implement adaptive, tetris-adaptive variational quantum eigensolver (VQE), and entanglement forging to reduce computational resource…

Quantum Physics · Physics 2024-07-24 Tushar Pandey , Jason Saroni , Abdullah Kazi , Kartik Sharma

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

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…

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

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

We propose a divide-and-conquer method for the quantum-classical hybrid algorithm to solve larger problems with small-scale quantum computers. Specifically, we concatenate a variational quantum eigensolver (VQE) with a reduction in the…

Quantum Physics · Physics 2022-01-26 Keisuke Fujii , Kaoru Mizuta , Hiroshi Ueda , Kosuke Mitarai , Wataru Mizukami , Yuya O. Nakagawa

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…

The hardware requirements of useful quantum algorithms remain unmet by the quantum computers available today. Because it was designed to soften these requirements, the Variational Quantum Eigensolver (VQE) has gained popularity as a…

Quantum Physics · Physics 2022-12-09 Mafalda Ramôa

We introduce the Cyclic Variational Quantum Eigensolver (CVQE), a hardware-efficient framework for accurate ground-state quantum simulation on noisy intermediate-scale quantum (NISQ) devices. CVQE departs from conventional VQE by…

Quantum Physics · Physics 2025-09-17 Hao Zhang , Ayush Asthana

Recently, an adaptive variational algorithm termed Adaptive Derivative-Assembled Pseudo-Trotter ansatz Variational Quantum Eigensolver (ADAPT-VQE) has been proposed by Grimsley et al. (Nat. Commun. 10, 3007) while the number of measurements…

Quantum Physics · Physics 2021-07-28 Jie Liu , Zhenyu Li , Jinlong Yang

The adaptive derivative-assembled pseudo-trotter variational quantum eigensolver (ADAPT-VQE) is a promising hybrid quantum-classical algorithm for molecular ground state energy calculation, yet its practical scalability is hampered by…

Quantum Physics · Physics 2026-02-05 Runhong He , Xin Hong , Qiaozhen Chai , Ji Guan , Junyuan Zhou , Arapat Ablimit , Guolong Cui , Shenggang Ying

The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver (VQE) algorithm aims to prepare the ground state of a…

Quantum Physics · Physics 2022-12-16 Nikita Astrakhantsev , Guglielmo Mazzola , Ivano Tavernelli , Giuseppe Carleo

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) is an efficient computational method promising chemical accuracy in electronic structure calculations on a universal-gate quantum computer. However, such a simple task as computing the electronic energy…

Chemical Physics · Physics 2018-06-04 Ilya G. Ryabinkin , Scott N. Genin , Artur F. Izmaylov

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
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