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Observing rapid developments of both the number of qubits and quantum volume, especially with recent advances in ion-trap quantum computers, it is no doubt that Fault-Tolerant-Quantum-Computer (FTQC) will be realized in the near future.…

Quantum Physics · Physics 2023-05-18 Hikaru Wakaura , Andriyan Bayu Suksmono

The emerging field of quantum simulation of many-body systems is widely recognized as a very important application of quantum computing. A crucial step towards its realization in the context of many-electron systems requires a rigorous…

Atomic Physics · Physics 2021-08-23 Sumeet , V. S. Prasannaa , B. P. Das , B. K. Sahoo

Variational quantum algorithms (VQAs) are a modern family of quantum algorithms designed to solve optimization problems using a quantum computer. Typically VQAs rely on a feedback loop between the quantum device and a classical optimization…

Quantum Physics · Physics 2022-08-26 Alexey Uvarov

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) is one of the most promising quantum algorithms for the near-term noisy intermediate-scale quantum (NISQ) devices. The VQE typically involves finding the minimum energy of a quantum Hamiltonian…

Quantum Physics · Physics 2024-02-16 Qidong Xu , Kanav Setia

Quantum computing promises to efficiently and accurately solve many important problems in quantum chemistry which elude classical solvers, such as the electronic structure problem of highly correlated materials. Two leading methods in…

Quantum Physics · Physics 2025-12-17 Sean Thrasher , Ioannis Kolotouros , Julien Michel , Petros Wallden

Variational quantum eigensolver (VQE) is an appealing candidate for the application of near-term quantum computers. A technique introduced in [Higgot et al., Quantum 3, 156 (2019)], which is named variational quantum deflation (VQD), has…

By leveraging the Variational Quantum Eigensolver (VQE), the ``quantum equation of motion" (qEOM) method established itself as a promising tool for quantum chemistry on near term quantum computers, and has been used extensively to estimate…

Quantum Physics · Physics 2024-09-04 Daniele Morrone , N. Walter Talarico , Marco Cattaneo , Matteo A. C. Rossi

Quantum chemistry is one of the most promising applications of quantum computers in the near future. For noisy intermediate-scale quantum devices, the quantum-classical hybrid framework based on the variational quantum eigensolver (VQE) has…

The electronic structure problem is one of the main problems in modern theoretical chemistry. While there are many already-established methods both for the problem itself and its applications like semi-classical or quantum dynamics, it…

Quantum Physics · Physics 2024-10-25 Martin Beseda , Silvie Illésová , Saad Yalouz , Bruno Senjean

Near-term quantum computers are expected to facilitate material and chemical research through accurate molecular simulations. Several developments have already shown that accurate ground-state energies for small molecules can be evaluated…

Variational quantum eigensolver (VQE) is demonstrated to be the promising methodology for quantum chemistry based on near-term quantum devices. However, many problems are yet to be investigated for this methodology, such as the influences…

Chemical Physics · Physics 2021-01-18 Xian-Hu Zha , Chao Zhang , Dengdong Fan , Pengxiang Xu , Shiyu Du , Rui-Qin Zhang , Chen Fu

Combinatorial optimization on near-term quantum devices is a promising path to demonstrating quantum advantage. However, the capabilities of these devices are constrained by high noise or error rates. In this paper, we propose an iterative…

Quantum Physics · Physics 2022-05-12 Xiaoyuan Liu , Anthony Angone , Ruslan Shaydulin , Ilya Safro , Yuri Alexeev , Lukasz Cincio

Integration of quantum chemistry simulations, machine learning techniques, and optimization calculations is expected to accelerate material discovery by making large chemical spaces amenable to computational study; a challenging task for…

The ground state search problem is central to quantum computing, with applications spanning quantum chemistry, condensed matter physics, and optimization. The Variational Quantum Eigensolver (VQE) has shown promise for small systems but…

Quantum Physics · Physics 2026-03-26 Alexander Holden , Moinul Hossain Rahat , Nii Osae Osae Dade

Quantum computers are reaching one crucial milestone after another. Motivated by their progress in quantum chemistry, we have performed an extensive series of simulations of quantum-computer runs that were aimed at inspecting best-practice…

Quantum Physics · Physics 2022-01-27 Ivana Miháliková , Martin Friák , Matej Pivoluska , Martin Plesch , Martin Saip , Mojmír Šob

Excited state properties play a pivotal role in various chemical and physical phenomena, such as charge separation and light emission. However, the primary focus of most existing quantum algorithms has been the ground state, as seen in…

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…

Accurate quantum chemistry simulations remain challenging on classical computers for problems of industrially relevant sizes and there is reason for hope that quantum computing may help push the boundaries of what is technically feasible.…

Quantum Physics · Physics 2021-03-17 Vincent E. Elfving , Marta Millaruelo , José A. Gámez , Christian Gogolin

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
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