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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

In the accompanying paper of arXiv:2505.00697, we have presented a generalized scheme of adaptive quantum gradient estimation (QGE) algorithm, and further proposed two practical variants which not only achieve doubly quantum enhancement in…

Quantum Physics · Physics 2025-05-05 Yuki Koizumi , Kaito Wada , Wataru Mizukami , Nobuyuki Yoshioka

Variational quantum eigensolvers (VQE) are among the most promising approaches for solving electronic structure problems on near-term quantum computers. A critical challenge for VQE in practice is that one needs to strike a balance between…

Quantum computing has recently exhibited great potentials in predicting chemical properties for various applications in drug discovery, material design, and catalyst optimization. Progress has been made in simulating small molecules, such…

The objective to be minimized in the variational quantum eigensolver (VQE) has a restricted form, which allows a specialized sequential minimal optimization (SMO) that requires only a few observations in each iteration. However, the SMO…

We present a scalable, hardware-aware methodology for extending the Variational Quantum Eigensolver (VQE) to large, realistic Dynamic Portfolio Optimization (DPO) problems. Building on the scaling strategy from our previous work, where we…

In this work, we introduce several technical and analytical extensions to our recent state-averaged orbital-optimized variational quantum eigensolver (SA-OO-VQE) algorithm (see Ref. [S. Yalouz et al. ,Quantum Sci. Technol. 6, 024004…

Quantum Physics · Physics 2023-10-19 Saad Yalouz , Emiel Koridon , Bruno Senjean , Benjamin Lasorne , Francesco Buda , Lucas Visscher

The variational quantum eigensolver (VQE) is one of the most prominent algorithms using near-term quantum devices, designed to find the ground state of a Hamiltonian. In VQE, a classical optimizer iteratively updates the parameters in the…

Quantum Physics · Physics 2026-02-12 Chenyu Shi , Vedran Dunjko , Hao Wang

The variational quantum eigensolver (VQE) is a hybrid algorithm that has the potential to provide a quantum advantage in practical chemistry problems that are currently intractable on classical computers. VQE trains parameterized quantum…

Quantum Physics · Physics 2023-11-10 Quoc Hoan Tran , Shinji Kikuchi , Hirotaka Oshima

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware…

Quantum Physics · Physics 2024-05-07 Senwei Liang , Linghua Zhu , Xiaolin Liu , Chao Yang , Xiaosong Li

ADAPT-VQE is one of the leading VQE algorithms which circumvents the choice-of-ansatz conundrum by iteratively growing compact and arbitrarily accurate problem-tailored ans\"atze. However, for hardware-efficient operator pools, the…

Quantum Physics · Physics 2023-10-03 Panagiotis G. Anastasiou , Nicholas J. Mayhall , Edwin Barnes , Sophia E. Economou

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) 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…

Variational quantum algorithms on bosonic quantum processors are an emerging paradigm for quantum chemistry calculations, exploiting the natural alignment between molecular structure and harmonic oscillator-based hardware. We introduce the…

Quantum Physics · Physics 2026-04-21 Marlon F. Jost , Sijia S. Dong

The variational quantum eigensolver (VQE) remains one of the most popular near-term quantum algorithms for solving the electronic structure problem. Yet, for its practicality, the main challenge to overcome is improving the quantum…

Quantum Physics · Physics 2023-05-11 Seonghoon Choi , Artur F. Izmaylov

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

Recent advances in quantum computing and their increased availability has led to a growing interest in possible applications. Among those is the solution of partial differential equations (PDEs) for, e.g., material or flow simulation.…

Quantum Physics · Physics 2023-08-08 Mazen Ali , Matthias Kabel

The Variational Quantum Eigensolver (VQE) is a promising candidate for quantum applications on near-term Noisy Intermediate-Scale Quantum (NISQ) computers. Despite a lot of empirical studies and recent progress in theoretical understanding…

Quantum Physics · Physics 2022-05-26 Xuchen You , Shouvanik Chakrabarti , Xiaodi Wu

The still-maturing noisy intermediate-scale quantum (NISQ) technology faces strict limitations on the algorithms that can be implemented efficiently. In quantum chemistry, the variational quantum eigensolver (VQE) algorithm has become…

Quantum Physics · Physics 2021-06-29 Daniel Claudino , Bo Peng , Nicholas P. Bauman , Karol Kowalski , Travis S. Humble

We propose a variational quantum eigensolver (VQE) algorithm that uses a fault-tolerant gate-set, and is hence suitable for implementation on a future error-corrected quantum computer. VQE quantum circuits are typically designed for…

Quantum Physics · Physics 2023-03-09 Hasan Sayginel , Francois Jamet , Abhishek Agarwal , Dan E. Browne , Ivan Rungger