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The variational quantum-classical algorithms are the most promising approach for achieving quantum advantage on near-term quantum simulators. Among these methods, the variational quantum eigensolver has attracted a lot of attention in…

Quantum Physics · Physics 2023-01-24 Chufan Lyu , Xusheng Xu , Man-Hong Yung , Abolfazl Bayat

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

The variational quantum eigensolver is one of the most promising approaches for performing chemistry simulations using noisy intermediate-scale quantum (NISQ) processors. The efficiency of this algorithm depends crucially on the ability to…

We propose a scheme to restore spatial symmetry of Hamiltonian in the variational-quantum-eigensolver (VQE) algorithm for which the quantum circuit structures used usually break the Hamiltonian symmetry. The symmetry-adapted VQE scheme…

Quantum Physics · Physics 2020-06-01 Kazuhiro Seki , Tomonori Shirakawa , Seiji Yunoki

The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm for quantum simulation that can be run on near-term quantum hardware. A challenge in VQE -- as well as any other heuristic algorithm for finding ground states…

Exploiting inherent symmetries is a common and effective approach to speed up the simulation of quantum systems. However, efficiently accounting for non-Abelian symmetries, such as the $SU(2)$ total-spin symmetry, remains a major challenge.…

Quantum Physics · Physics 2024-12-20 Anthony Gandon , Alberto Baiardi , Max Rossmannek , Werner Dobrautz , Ivano Tavernelli

The variational quantum eigensolver (or VQE) uses the variational principle to compute the ground state energy of a Hamiltonian, a problem that is central to quantum chemistry and condensed matter physics. Conventional computing methods are…

Quantum systems have historically been formidable to simulate using classical computational methods, particularly as the system size grows. In recent years, advancements in quantum computing technology have offered new opportunities for…

Quantum Physics · Physics 2023-09-06 Jinao Wang , Rimika Jaiswal

Quantum computing is a promising approach to harnessing strong correlation in molecular systems; however, current devices only allow for hybrid quantum-classical algorithms with a shallow circuit depth, such as the variational quantum…

Quantum Physics · Physics 2023-10-02 Takashi Tsuchimochi , Masaki Taii , Taisei Nishimaki , Seiichiro L. Ten-no

Determining the ground state of a many-body Hamiltonian is a central problem across physics, chemistry, and combinatorial optimization, yet it is often classically intractable due to the exponential growth of Hilbert space with system size.…

Quantum Physics · Physics 2026-02-24 Jungyun Lee , Daniel K. Park

Simulating complex spin systems, known for high frustration and entanglement, presents significant challenges due to their intricate energy landscapes. This study focuses on the $J_{1}-J_{2}$ Heisenberg model, renowned for its rich phase…

Quantum Physics · Physics 2024-07-02 Dylan Sheils , Trevor David Rhone

The ground state properties of the two-dimensional $J_1-J_2$-model are very challenging to analyze via classical numerical methods due to the high level of frustration. This makes the model a promising candidate where quantum computers…

Quantum Physics · Physics 2023-04-27 Verena Feulner , Michael J. Hartmann

Variational algorithms for strongly correlated chemical and materials systems are one of the most promising applications of near-term quantum computers. We present an extension to the variational quantum eigensolver that approximates the…

Quantum Physics · Physics 2020-08-26 William J. Huggins , Joonho Lee , Unpil Baek , Bryan O'Gorman , K. Birgitta Whaley

This thesis explores the application of the Symmetry-Breaking/Symmetry-Restoration methodology on quantum computers to better approximate a Hamiltonian's ground state energy within a variational framework in many-body physics. This involves…

Quantum Physics · Physics 2023-11-10 Andres Ruiz

We propose an extended version of the symmetry-adapted variational-quantum-eigensolver (VQE) and apply it to a two-component Fermi-Hubbard model on a bipartite lattice. In the extended symmetry-adapted VQE method, the Rayleigh quotient for…

Quantum Physics · Physics 2022-03-11 Kazuhiro Seki , Seiji Yunoki

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)…

Nuclear Theory · Physics 2026-01-28 Dhritimalya Roy , Somnath Nag

Quantum spin systems may offer the first opportunities for beyond-classical quantum computations of scientific interest. While general quantum simulation algorithms likely require error-corrected qubits, there may be applications of…

We consider some classical and frustrated lattice spin models with global O(3) spin symmetry. There is no general analytical method to find a ground-state if the spin dependence of the Hamiltonian is more than quadratic (i.e. beyond the…

Strongly Correlated Electrons · Physics 2015-03-17 Laura Messio , Claire Lhuillier , Grégoire Misguich

Quantum chemistry calculations on a quantum computer frequently suffer from symmetry breaking: the situation when a state of assumed spin and number of electrons is contaminated with contributions of undesired symmetry. The situation may…

Quantum Physics · Physics 2018-12-27 Ilya G. Ryabinkin , Scott N. Genin

Variational quantum algorithms are among the most promising approaches for simulating interacting quantum many-body systems on noisy intermediate-scale quantum (NISQ) devices. However, the practical success of variational quantum…

Quantum Physics · Physics 2026-01-01 Rudraksh Sharma
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