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Quantum chemistry and materials science are among the most promising areas for demonstrating algorithmic quantum advantage and quantum utility due to their inherent quantum mechanical nature. Still, large-scale simulations of quantum…

Nonequilibrium dynamics of quantum many-body systems is challenging for classical computing, providing opportunities for demonstrating practical quantum computational advantage with analogue quantum simulators. Owing to the intimate…

Quantum computing is a promising technology that harnesses the peculiarities of quantum mechanics to deliver computational speedups for some problems that are intractable to solve on a classical computer. Current generation noisy…

Numerical Analysis · Mathematics 2022-09-16 Daan Camps , Efekan Kökcü , Lindsay Bassman , Wibe A. de Jong , Alexander F. Kemper , Roel Van Beeumen

Quantum Computing allows, in principle, the encoding of the exponentially scaling many-electron wave function onto a linearly scaling qubit register, offering a promising solution to overcome the limitations of traditional quantum chemistry…

Quantum Physics · Physics 2025-10-21 C. Feniou , O. Adjoua , B. Claudon , J. Zylberman , E. Giner , J. -P. Piquemal

Future quantum computers are anticipated to be able to perform simulations of quantum many-body systems and quantum field theories that lie beyond the capabilities of classical computation. This will lead to new insights and predictions for…

Nuclear Theory · Physics 2023-12-14 Martin J. Savage

Recent advances in quantum technologies and related experiments have created a need for highly accurate, versatile, and computationally efficient simulation techniques for the dynamics of open quantum systems. Long-lived correlation effects…

Quantum Physics · Physics 2026-01-09 Meng Xu , Vasilii Vadimov , J. T. Stockburger , J. Ankerhold

The Krylov subspace methods, being one category of the most important classical numerical methods for linear algebra problems, can be much more powerful when generalised to quantum computing. However, quantum Krylov subspace algorithms are…

Quantum Physics · Physics 2024-08-14 Zongkang Zhang , Anbang Wang , Xiaosi Xu , Ying Li

Quantum approximate optimization algorithm (QAOA) is one of the popular quantum algorithms that are used to solve combinatorial optimization problems via approximations. QAOA is able to be evaluated on both physical and virtual quantum…

Quantum Physics · Physics 2023-12-07 Yu-Cheng Lin , Chuan-Chi Wang , Chia-Heng Tu , Shih-Hao Hung

A long-standing open problem in non-Markovian quantum state diffusion (QSD) approach to open quantum systems is to establish the non-Markovian QSD equations for multiple qubit systems. In this paper, we settle this important question by…

Quantum Physics · Physics 2013-12-31 Jun Jing , Xinyu Zhao , J. Q. You , W. T. Strunz , Ting Yu

We show that current noisy quantum computers are ideal platforms for the simulation of quantum many-body dynamics in generic open systems. We demonstrate this using the IBM Quantum Computer as an experimental platform for confirming the…

Quantum Physics · Physics 2021-06-16 Oscar Emil Sommer , Francesco Piazza , David J. Luitz

The current generation of noisy intermediate scale quantum computers introduces new opportunities to study quantum many-body systems. In this paper, we show that quantum circuits can provide a dramatically more efficient representation than…

Quantum Physics · Physics 2021-03-24 Sheng-Hsuan Lin , Rohit Dilip , Andrew G. Green , Adam Smith , Frank Pollmann

Quantum simulation represents the most promising quantum application to demonstrate quantum advantage on near-term noisy intermediate-scale quantum (NISQ) computers, yet available quantum simulation algorithms are prone to errors and thus…

Quantum Physics · Physics 2024-10-01 Shin Sun , Li-Chai Shih , Yuan-Chung Cheng

The past few years have witnessed the concrete and fast spreading of quantum technologies for practical computation and simulation. In particular, quantum computing platforms based on either trapped ions or superconducting qubits have…

Quantum Physics · Physics 2020-04-21 Francesco Tacchino , Alessandro Chiesa , Stefano Carretta , Dario Gerace

In this work we propose to simulate many-body thermodynamics of infinite-size quantum lattice models in one, two, and three dimensions, in terms of few-body models of only O(10) sites, which we coin as quantum entanglement simulators…

Strongly Correlated Electrons · Physics 2019-05-23 Shi-Ju Ran , Bin Xi , Cheng Peng , Gang Su , Maciej Lewenstein

Universal quantum algorithms (UQA) implemented on fault-tolerant quantum computers are expected to achieve an exponential speedup over classical counterparts. However, the deep quantum circuits makes the UQA implausible in the current era.…

Quantum Physics · Physics 2023-04-18 Jin-Min Liang , Qiao-Qiao Lv , Zhi-Xi Wang , Shao-Ming Fei

Quantum computing enables parallelism through superposition and entanglement and offers advantages over classical computing architectures. However, due to the limitations of current quantum hardware in the noisy intermediate-scale quantum…

Quantum Physics · Physics 2025-09-09 Guolong Zhong , Yi Fan , Zhenyu Li

Incremental quantum circuit simulation has emerged as an important tool for simulation-driven quantum applications, such as circuit synthesis, verification, and analysis. When a small portion of the circuit is modified, the simulator must…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-28 Tsung-Wei Huang

We propose quantum-selected configuration interaction (QSCI), a class of hybrid quantum-classical algorithms for calculating the ground- and excited-state energies of many-electron Hamiltonians on noisy quantum devices. Suppose that an…

Quantum Physics · Physics 2023-02-23 Keita Kanno , Masaya Kohda , Ryosuke Imai , Sho Koh , Kosuke Mitarai , Wataru Mizukami , Yuya O. Nakagawa

Owing to their great expressivity and versatility, neural networks have gained attention for simulating large two-dimensional quantum many-body systems. However, their expressivity comes with the cost of a challenging optimization due to…

Disordered Systems and Neural Networks · Physics 2025-03-26 Hannah Lange , Guillaume Bornet , Gabriel Emperauger , Cheng Chen , Thierry Lahaye , Stefan Kienle , Antoine Browaeys , Annabelle Bohrdt