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Quantum error correction and quantum error detection necessitate syndrome measurements to detect errors. Performing syndrome measurements for each stabilizer generator can be a significant overhead, considering the fact that the readout…

Quantum Physics · Physics 2023-10-31 Kento Tsubouchi , Yasunari Suzuki , Yuuki Tokunaga , Nobuyuki Yoshioka , Suguru Endo

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

Quantum phase estimation (QPE) is one of the core algorithms for quantum computing. It has been extensively studied and applied in a variety of quantum applications such as the Shor's factoring algorithm, quantum sampling algorithms and the…

The Variational Quantum Eigensolver (VQE) is one the most perspective algorithms for simulation of quantum many body physics that have recently attached a lot of attention and believed would be practical for implementation on the near term…

Quantum Physics · Physics 2021-05-03 Belozerova Polina , Shangareev Arthur , Zotov Yuriy , Yung Manhong , lv Dingshun

Variational quantum circuits build the foundation for various classes of quantum algorithms. In a nutshell, the weights of a parametrized quantum circuit are varied until the empirical sampling distribution of the circuit is sufficiently…

The variational quantum eigensolver (VQE), a variational algorithm to obtain an approximated ground state of a given Hamiltonian, is an appealing application of near-term quantum computers. The original work [A. Peruzzo et al.; \textit{Nat.…

Quantum Physics · Physics 2019-11-06 Ken M Nakanishi , Kosuke Mitarai , Keisuke Fujii

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

Recent advances in quantum computing devices have brought attention to hybrid quantum-classical algorithms like the Variational Quantum Eigensolver (VQE) as a potential route to practical quantum advantage in chemistry. However, it is not…

We present an empirical analysis of the scaling of the minimal quantum circuit depth required for a variational quantum simulation (VQS) method to obtain a solution to the time evolution of a quantum system within a predefined error…

Quantum Physics · Physics 2026-04-14 Mario Ponce , Thomas Cope , Inés de Vega , Martin Leib

Continuous-variable (CV) quantum computing is a promising candidate for quantum computation because it can, even with one mode, utilize infinite-dimensional Hilbert spaces and can efficiently handle continuous values. Although photonic…

The vacuum of the lattice Schwinger model is prepared on up to 100 qubits of IBM's Eagle-processor quantum computers. A new algorithm to prepare the ground state of a gapped translationally-invariant system on a quantum computer is…

Quantum Physics · Physics 2024-04-23 Roland C. Farrell , Marc Illa , Anthony N. Ciavarella , Martin J. Savage

The number of measurements demanded by hybrid quantum-classical algorithms such as the variational quantum eigensolver (VQE) is prohibitively high for many problems of practical value. For such problems, realizing quantum advantage will…

Quantum Physics · Physics 2021-03-24 Guoming Wang , Dax Enshan Koh , Peter D. Johnson , Yudong Cao

In the noisy-intermediate-scale-quantum era, Variational Quantum Eigensolver (VQE) is a promising method to study ground state properties in quantum chemistry, materials science, and condensed physics. However, general quantum eigensolvers…

Quantum Physics · Physics 2023-09-27 Yusen Wu , Zigeng Huang , Jinzhao Sun , Xiao Yuan , Jingbo B. Wang , Dingshun Lv

It has recently been argued that noisy intermediate-scale quantum computers may be used to optimize interpolating operator constructions for lattice quantum field theory (LQFT) calculations on classical computers. Here, two concrete…

High Energy Physics - Lattice · Physics 2023-03-29 A. Avkhadiev , P. E. Shanahan , R. D. Young

The study of spontaneous supersymmetry breaking (SSB) on the lattice is obstructed by a severe sign problem. Quantum computing provides a promising alternative approach. In particular, properties of supersymmetry relate SSB to the…

Quantum Physics · Physics 2026-03-20 John Kerfoot , David Schaich , Emanuele Mendicelli

Variational quantum time evolution allows us to simulate the time dynamics of quantum systems with near-term compatible quantum circuits. Due to the variational nature of this method the accuracy of the simulation is a priori unknown. We…

Quantum Physics · Physics 2023-10-25 Christa Zoufal , David Sutter , Stefan Woerner

Quantum simulation is one of the key applications of quantum computing, which accelerates research and development in the fields such as chemistry and material science. The recent development of noisy intermediate-scale quantum (NISQ)…

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

We extend the quantum geometric tensor from the state space to the operator level,and investigate its properties like the additivity for factorizable models and the splitting of two kinds contributions for the case of stationary reference…

Quantum Physics · Physics 2010-08-31 Xiao-Ming Lu , Xiaoguang Wang

A family of Variational Quantum Eigensolver (VQE) methods is designed to maximize the resource of existing noisy intermediate-scale quantum (NISQ) devices. However, VQE approaches encounter various difficulties in simulating molecules of…

Chemical Physics · Physics 2022-08-16 M. D. Sapova , A. K. Fedorov