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We developed a quantum eigensolver (QE) which is based on an extension of optimized binary configurations measured by quantum annealing (QA) on a D-Wave Quantum Annealer (D-Wave QA). This approach performs iterative QA measurements to…

量子物理 · 物理学 2024-06-06 Hayun Park , Hunpyo Lee

We demonstrate that the performance of a quantum annealer on hard random Ising optimization problems can be substantially improved using quantum annealing correction (QAC). Our error correction strategy is tailored to the D-Wave Two device.…

量子物理 · 物理学 2015-04-03 Kristen L. Pudenz , Tameem Albash , Daniel A. Lidar

Quantum chemistry is regarded to be one of the first disciplines that will be revolutionized by quantum computing. Although universal quantum computers of practical scale may be years away, various approaches are currently being pursued to…

量子物理 · 物理学 2021-01-29 Alexander Teplukhin , Brian K. Kendrick , Sergei Tretiak , Pavel A. Dub

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…

The possibility of using quantum computers for electronic structure calculations has opened up a promising avenue for computational chemistry. Towards this direction, numerous algorithmic advances have been made in the last five years. The…

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…

原子物理 · 物理学 2021-08-23 Sumeet , V. S. Prasannaa , B. P. Das , B. K. Sahoo

We present the results of our quantum annealing computations of the permanent electric dipole moments of several molecules. By applying an electric field as a perturbation and measuring the corresponding energy responses, the molecular…

量子物理 · 物理学 2025-12-08 Pradyot Pritam Sahoo , V. S. Prasannaa , B. P. Das

Quantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods. However, due to the limited number of…

量子物理 · 物理学 2025-04-09 Seongmin Kim , Sang-Woo Ahn , In-Saeng Suh , Alexander W. Dowling , Eungkyu Lee , Tengfei Luo

Despite rapid progress in the development of quantum algorithms in quantum computing as well as numerical simulation methods in classical computing for atomic and molecular applications, no systematic and comprehensive electronic structure…

Quantum annealers (QAs) are specialized quantum computers that minimize objective functions over discrete variables by physically exploiting quantum effects. Current QA platforms allow for the optimization of quadratic objectives defined…

新兴技术 · 计算机科学 2018-11-07 Zhengbing Bian , Fabian Chudak , William Macready , Aidan Roy , Roberto Sebastiani , Stefano Varotti

We investigate the computational efficiency and thermodynamic cost of the D-Wave quantum annealer under reverse-annealing with and without pausing. Our experimental results demonstrate that the combination of reverse-annealing and pausing…

量子物理 · 物理学 2024-02-27 Tomasz Śmierzchalski , Zakaria Mzaouali , Sebastian Deffner , Bartłomiej Gardas

Quantum variational algorithms (QVAs) are increasingly potent tools for simulating quantum many-body systems on noisy intermediate-scale quantum (NISQ) devices. This work examines the application of the Variational Quantum Eigensolver (VQE)…

核理论 · 物理学 2026-01-28 Dhritimalya Roy , Somnath Nag

Quantum annealing is a heuristic optimization algorithm that exploits quantum evolution to approximately find lowest energy states. Quantum annealers have scaled up in recent years to tackle increasingly larger and more highly connected…

量子物理 · 物理学 2025-07-04 Humberto Munoz Bauza , Daniel A. Lidar

Quantum optimization algorithms offer a promising route to finding the ground states of target Hamiltonians on near-term quantum devices. None the less, it remains necessary to limit the evolution time and circuit depth as much as possible,…

量子物理 · 物理学 2022-11-01 Chenfeng Cao , Yunlong Yu , Zipeng Wu , Nic Shannon , Bei Zeng , Robert Joynt

The performance of open-system quantum annealing is adversely affected by thermal excitations out of the ground state. While the presence of energy gaps between the ground and excited states suppresses such excitations, error correction…

量子物理 · 物理学 2017-02-09 Shunji Matsuura , Hidetoshi Nishimori , Walter Vinci , Tameem Albash , Daniel A. Lidar

We present a quantum information-inspired ansatz for the variational quantum eigensolver (VQE) and demonstrate its efficacy in calculating ground-state energies of atomic systems. Instead of adopting a heuristic approach, we start with an…

量子物理 · 物理学 2025-08-19 Abdul Kalam , Prasenjit Deb , Akitada Sakurai , B. K. Sahoo , V. S. Prasannaa , B. P. Das

Solving Helmholtz problems using finite elements leads to the resolution of a linear system which is challenging to solve for classical computers. In this paper, we investigate how quantum annealers could address this challenge. We first…

量子物理 · 物理学 2026-01-29 Arnaud Rémi , François Damanet , Christophe Geuzaine

Many problems of industrial interest are NP-complete, and quickly exhaust resources of computational devices with increasing input sizes. Quantum annealers (QA) are physical devices that aim at this class of problems by exploiting quantum…

The computation of electronic structure properties at the quantum level is a crucial aspect of modern physics research. However, conventional methods can be computationally demanding for larger, more complex systems. To address this issue,…

量子物理 · 物理学 2023-12-05 Nouhaila Innan , Muhammad Al-Zafar Khan , Mohamed Bennai

Quantum annealing has been demonstrated with superconducting qubits. Such a quantum annealer has been used to solve combinatorial optimization problems. Moreover, it serves as a quantum simulator for investigating the properties of quantum…

量子物理 · 物理学 2025-07-16 Takashi Imoto , Yuki Susa , Ryoji Miyazaki , Yuichiro Matsuzaki
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