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The Variational Quantum Eigensolver (VQE) is a promising algorithm for quantum computing applications in chemistry and materials science, particularly in addressing the limitations of classical methods for complex systems. This study…

Quantum Physics · Physics 2025-02-25 Nia Pollard , Kamal Choudhary

Classical simulation of molecular systems is limited by exponential scaling, a hurdle quantum algorithms like Variational Quantum Eigensolvers (VQEs) aim to overcome. Although ADAPT-VQE enhances VQEs by dynamically building ans\"atze, it…

Quantum Physics · Physics 2025-06-23 Tatiana A. Bespalova , Oumaya Ladhari , Guido Masella

Even a minor boost in solving combinatorial optimization problems can greatly benefit multiple industries. Quantum computers, with their unique information processing capabilities, hold promise for delivering such enhancements. The…

Quantum Physics · Physics 2025-05-15 Gabriel Marin-Sanchez , David Amaro

The Variational Quantum Eigensolver (VQE) algorithm is gaining interest for its potential use in near-term quantum devices. In the VQE algorithm, parameterized quantum circuits (PQCs) are employed to prepare quantum states, which are then…

Quantum Physics · Physics 2023-12-29 Atsushi Matsuo , Yudai Suzuki , Ikko Hamamura , Shigeru Yamashita

Quantum computing brings a promise of new approaches into computational quantum chemistry. While universal, fault-tolerant quantum computers are still not available, we want to utilize today's noisy quantum processors. One of their flagship…

Quantum-selected configuration interaction (QSCI) has emerged as a feasible approach for approximating electronic ground states on noisy quantum devices toward large-system demonstrations. In QSCI, Slater determinants are sampled from a…

Quantum Physics · Physics 2026-04-14 Ryota Kemmoku , Qi Gao , Shu Kanno , Kimberlee Keithley , Ikko Hamamura , Naoki Yamamoto , Kouhei Nakaji

Variational Quantum Eigensolver (VQE) is a promising algorithm for near-term quantum machines. It can be used to estimate the ground state energy of a molecule by performing separate measurements of $O(N^4)$ terms. Several recent papers…

Quantum Physics · Physics 2019-09-02 Pranav Gokhale , Frederic T. Chong

We present and benchmark a type of variational quantum eigensolver (VQE), which we denote $\sigma$-VQE. It is designed to target mid-spectrum eigenstates and prepare quantum many-body scar states. The approach leverages the fact that noisy…

Quantum Physics · Physics 2026-05-18 Eoin Carolan , Nathan Keenan , Gabriele Cenedese , Giuliano Benenti

We present a distributed algorithm and implementation of the variational quantum eigensolver (VQE), termed distributed VQE (DVQE). DVQE, provided as an open-source Python package, enables the execution of parameterized quantum circuits…

Quantum Physics · Physics 2025-08-29 Milad Hasanzadeh , Amin Kargarian

This work studies the variational quantum eigensolver algorithm, designed to determine the ground state of a quantum mechanical system by combining classical and quantum hardware. Methods of reducing the number of required qubit…

Quantum Physics · Physics 2022-03-01 R. J. P. T. de Keijzer , V. E. Colussi , B. Škorić , S. J. J. M. F. Kokkelmans

Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled cluster ansatz, we demonstrate that…

While ground-state preparation is expected to be a primary application of quantum computers, it is also an essential subroutine for many fault-tolerant algorithms. In early fault-tolerant regimes, logical measurements remain costly,…

Quantum Physics · Physics 2026-02-20 Jona Erle , Balint Koczor

Variational quantum eigensolvers (VQEs) are one of the most important and effective applications of quantum computing, especially in the current noisy intermediate-scale quantum (NISQ) era. There are mainly two ways for VQEs:…

Quantum Physics · Physics 2024-11-19 Xin Wang , Bo Qi , Yabo Wang , Daoyi Dong

The utility of effective model spaces in quantum simulations of non-relativistic quantum many-body systems is explored in the context of the Lipkin-Meshkov-Glick model of interacting fermions. We introduce an iterative…

Quantum Physics · Physics 2023-08-25 Caroline E. P. Robin , Martin J. Savage

We present a novel quantum algorithm for approximating the ground-state in quantum many-body systems, particularly suited for Noisy Intermediate-Scale Quantum (NISQ) devices. Our approach integrates Variational Quantum Eigensolvers (VQE)…

Quantum Physics · Physics 2024-03-18 Yihao Liu , Min-Quan He , Z. D. Wang

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…

Quantum simulators offer the potential to utilize the quantum nature of a physical system to study another physical system. In contrast to conventional simulation, which experiences an exponential increase in computational complexity,…

Quantum Physics · Physics 2024-07-24 Xuliang Du , Yang Shen , Zipeng Wu , Bei Zeng , Sen Yang

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

Bethe equations, whose solutions determine exact eigenvalues and eigenstates of corresponding integrable Hamiltonians, are generally hard to solve. We implement a Variational Quantum Eigensolver (VQE) approach to estimating Bethe roots of…

Quantum Physics · Physics 2025-01-28 David Raveh , Rafael I. Nepomechie

Within the evolving domain of quantum computational chemistry, the Variational Quantum Eigensolver (VQE) has been developed to explore not only the ground state but also the excited states of molecules. In this study, we compare the…

Quantum Physics · Physics 2024-06-18 I-Chi Chen , Nouhaila Innan , Suman Kumar Roy , Jason Saroni
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