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Efficient sampling from a classical Gibbs distribution is an important computational problem with applications ranging from statistical physics over Monte Carlo and optimization algorithms to machine learning. We introduce a family of…

Quantum Physics · Physics 2021-09-08 Dominik S. Wild , Dries Sels , Hannes Pichler , Cristian Zanoci , Mikhail D. Lukin

Recent advancements in quantum computing suggest the potential to revolutionize computational algorithms across various scientific domains including oceanography and atmospheric science. The field is still relatively young and quantum…

Quantum Physics · Physics 2026-03-24 Takuro Matsuta , Ryo Furue

Quantum computation represents an emerging framework to solve lattice gauge theories (LGT) with arbitrary gauge groups, a general and long-standing problem in computational physics. While quantum computers may encode LGT using only…

Quantum Physics · Physics 2022-01-21 Giulia Mazzola , Simon V. Mathis , Guglielmo Mazzola , Ivano Tavernelli

We present a quantum annealing-based solution method for topology optimization (TO). In particular, we consider TO in a more general setting, i.e., applied to structures of continuum domains where designs are represented as distributed…

Numerical Analysis · Mathematics 2023-01-30 Zisheng Ye , Xiaoping Qian , Wenxiao Pan

The Schwinger model, which describes lattice quantum electrodynamics in $1+1$ space-time dimensions, provides a valuable framework to investigate fundamental aspects of quantum field theory, and a stepping stone towards non-Abelian gauge…

Quantum Physics · Physics 2026-01-19 Angus Kan , Jessica Lemieux , Olga Okrut , Burak Şahinoğlu

The Fermi-Hubbard model is one of the central paradigms in the physics of strongly-correlated quantum many-body systems. Here we propose a quantum circuit algorithm based on the $\mathrm{Z}_2$ lattice gauge theory (LGT) representation of…

Quantum Physics · Physics 2023-11-09 Uliana E. Khodaeva , Dmitry L. Kovrizhin , Johannes Knolle

An important and difficult problem in optimization is the high-order unconstrained binary optimization, which can represent many optimization problems more efficient than quadratic unconstrained binary optimization, but how to quickly solve…

Quantum Physics · Physics 2025-03-19 Bi-Ying Wang , Xiaopeng Cui , Qingguo Zeng , Yemin Zhan , Man-Hong Yung , Yu Shi

In these proceedings, we review recent advances in applying quantum computing to lattice field theory. Quantum computing offers the prospect to simulate lattice field theories in parameter regimes that are largely inaccessible with the…

High Energy Physics - Lattice · Physics 2023-08-10 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn

Quantum simulation with adiabatic annealing can provide insight into difficult problems that are impossible to study with classical computers. However, it deteriorates when the systems scale up due to the shrinkage of the excitation gap and…

The main objective of quantum simulation is an in-depth understanding of many-body physics. It is important for fundamental issues (quantum phase transitions, transport, . . . ) and for the development of innovative materials. Analytic…

We provide practical simulation methods for scalar field theories on a quantum computer that yield improved asymptotics as well as concrete gate estimates for the simulation and physical qubit estimates using the surface code. We achieve…

Discrete combinatorial optimization consists in finding the optimal configuration that minimizes a given discrete objective function. An interpretation of such a function as the energy of a classical system allows us to reduce the…

Quantum Physics · Physics 2015-06-22 Sergio Boixo , Gerardo Ortiz , Rolando Somma

One of the methods proposed in the last years for studying non-perturbative gauge theory physics is quantum simulation, where lattice gauge theories are mapped onto quantum devices which can be built in the laboratory, or quantum computers.…

High Energy Physics - Lattice · Physics 2024-04-02 Judy Shir , Erez Zohar

Lattice gauge theories (LGTs) provide a framework for describing dynamical systems ranging from nuclei to materials. LGTs that host concatenated conservation laws can exhibit Hilbert space fragmentation, where each subspace may be labeled…

Quantum Physics · Physics 2026-02-24 Prithvi Raj Datla , Luheng Zhao , Wen Wei Ho , Natalie Klco , Huanqian Loh

We analyze the performance of quantum annealing as a heuristic optimization method to find the absolute minimum of various continuous models, including landscapes with only two wells and also models with many competing minima and with…

Statistical Mechanics · Physics 2015-11-25 E. M. Inack , S. Pilati

Search-based software engineering (SBSE) addresses critical optimization challenges in software engineering, including the next release problem (NRP) and feature selection problem (FSP). While traditional heuristic approaches and integer…

Software Engineering · Computer Science 2025-07-01 Shuchang Wang , Xiaopeng Qiu , Yingxing Xue , Yanfu Li , Wei Yang

We explore the application of quantum optimal control (QOC) techniques to state preparation of lattice field theories on quantum computers. As a first example, we focus on the Schwinger model, quantum electrodynamics in 1+1 dimensions. We…

Quantum Physics · Physics 2025-02-12 Jack Y. Araz , Siddhanth Bhowmick , Matt Grau , Thomas J. McEntire , Felix Ringer

We show how to implement a Rydberg-atom quantum simulator to study the non-equilibrium dynamics of an Abelian (1+1)-D lattice gauge theory. The implementation locally codifies the degrees of freedom of a $\mathbf{Z}_3$ gauge field, once the…

Quantum Gases · Physics 2020-03-18 Simone Notarnicola , Mario Collura , Simone Montangero

Quantum annealing with the D-Wave Advantage system in the random Ising model on a cubic lattice is simulated using a three-dimensional (3D) tensor network. The Hamiltonian is driven across a quantum phase transition from a paramagnetic…

Quantum Physics · Physics 2026-03-18 Jacek Dziarmaga

The accurate treatment of electron correlation in extended molecular systems remains computationally challenging using classical electronic structure methods. Hybrid quantum-classical algorithms offer a potential route to overcome these…