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This paper explores the potential contribution of quantum computing, specifically the Variational Quantum Eigensolver (VQE), into atmospheric physics research and application problems using as an example the Lorenz system, a paradigm of…

Quantum Physics · Physics 2024-01-09 V. Armaos , Athanassios A. Argiriou , Ioannis Kioutsioukis

The quantum-classical hybrid Variational Quantum Eigensolver (VQE) algorithm is recognized to be the most suitable approach to obtain ground state energies of quantum many-body systems in the noisy intermediate scale quantum era. In this…

Atomic Physics · Physics 2023-04-12 K. R. Swain , V. S. Prasannaa , Kenji Sugisaki , B. P. Das

The variational quantum eigen solver (VQE), has been widely used to find the ground state energy of different Hamiltonians with no analytical solutions and are classically difficult to compute. In our work, we have used VQE to identify the…

Quantum Physics · Physics 2026-01-08 Mrinal Dev , Shraddha Sharma

Quantum critical point is one key concept for studying many-body physics but its investigation may be resource-demanding even for a quantum computer due to the intrinsic complexity. In this paper, we propose an approach based on variational…

Quantum Physics · Physics 2023-02-22 Zhi-Quan Shi , Fang-Gang Duan , Dan-Bo Zhang

The ground and excited state calculations at key geometries, such as the Frank-Condon (FC) and the conical intersection (CI) geometries, are essential for understanding photophysical properties. To compute these geometries on noisy…

Quantum Physics · Physics 2023-01-02 Shigeki Gocho , Hajime Nakamura , Shu Kanno , Qi Gao , Takao Kobayashi , Taichi Inagaki , Miho Hatanaka

Great efforts have been dedicated in recent years to explore practical applications for noisy intermediate-scale quantum (NISQ) computers, which is a fundamental and challenging problem in quantum computing. As one of the most promising…

We present a hybrid classical-quantum algorithm to solve optimization problems in current quantum computers, whose basic idea is to assist variational quantum eigensolvers (VQE) with adiabatic change of the Hamiltonian. The rational for…

Quantum Physics · Physics 2018-06-07 A. Garcia-Saez , J. I. Latorre

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.…

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

The cascaded variational quantum eigensolver (CVQE) circumvents the need for iterative communication between the quantum and classical processing units that is necessary in the conventional VQE algorithm. While CVQE offers complete freedom…

Quantum Physics · Physics 2026-05-04 Yi-Hua Lai , John P. T. Stenger , Gloria Bazargan , Igor V. Schweigert , Daniel Gunlycke

We propose an efficient circuit structure of variational quantum circuit \textit{Ans\"{a}tze} used for the variational quantum eigensolver (VQE) algorithm in calculating gapped topological phases on the currently feasible noisy…

Quantum Physics · Physics 2023-08-21 Rong-Yang Sun , Tomonori Shirakawa , Seiji Yunoki

Quantum chemistry and materials is one of the most promising applications of quantum computing. Yet much work is still to be done in matching industry-relevant problems in these areas with quantum algorithms that can solve them. Most…

We study an adiabatic variant of the variational quantum eigensolver (VQE) in which VQE is performed iteratively for a sequence of Hamiltonians along an adiabatic path. We derive the conditions under which gradient-based optimization…

Quantum Physics · Physics 2026-02-20 Bojan Žunkovič , Marco Ballarin , Lewis Wright , Michael Lubasch

The quantum-classical hybrid variational quantum eigensolver (VQE) algorithm is arguably the most popular noisy intermediate-scale quantum (NISQ) era approach to quantum chemistry. We consider the underexplored quantum annealing eigensolver…

We propose a variational quantum eigensolver (VQE) for the simulation of strongly-correlated quantum matter based on a multi-scale entanglement renormalization ansatz (MERA) and gradient-based optimization. This MERA quantum eigensolver can…

Quantum Physics · Physics 2023-09-04 Qiang Miao , Thomas Barthel

The variational quantum eigensolver (VQE) is currently the flagship algorithm for solving electronic structure problems on near-term quantum computers. This hybrid quantum/classical algorithm involves implementing a sequence of…

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

A quantum computing algorithm is proposed to obtain low-lying excited states in many-body interacting systems. The approximate eigenstates are obtained by using a quantum space diagonalization method in a subspace of states selected from…

Quantum Physics · Physics 2025-06-30 Jing Zhang , Denis Lacroix

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

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