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Related papers: A Coherent Quantum Annealer with Rydberg Atoms

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A novel quantum-classical hybrid scheme is proposed to efficiently solve large-scale combinatorial optimization problems. The key concept is to introduce a Hamiltonian dynamics of the classical flux variables associated with the quantum…

Quantum Physics · Physics 2021-04-28 Hirotaka Irie , Haozhao Liang , Takumi Doi , Shinya Gongyo , Tetsuo Hatsuda

Quantum computing has the potential to accelerate various domains: scientific computation, machine learning, and optimization. Recently, Rydberg atom quantum computing has emerged as a promising quantum computing technology, especially with…

Quantum Physics · Physics 2024-12-11 Jason Zev Ludmir , Yuqian Huo , Nicholas S. DiBrita , Tirthak Patel

Strong interactions can amplify quantum effects such that they become important on macroscopic scales. Controlling these coherently on a single particle level is essential for the tailored preparation of strongly correlated quantum systems…

Quantum computation is a promising emerging technology, and by utilizing the principles of quantum mechanics, it is expected to achieve faster computations than classical computers for specific problems. There are two distinct architectures…

Quantum Physics · Physics 2025-03-13 Takashi Imoto , Yuki Susa , Ryoji Miyazaki , Yuichiro Matsuzaki

We investigate a hybrid modeling framework in which a quantum annealer is used to simulate magnetic interactions in molecular qubit lattices inspired by experimentally realizable systems. Using phthalocyanine assemblies as a structurally…

Quantum Physics · Physics 2025-07-28 Alejandro Lopez-Bezanilla , Pavel A. Dub , Avadh Saxena

Quantum simulation of interacting many-body spin systems is routinely performed with cold trapped ions, and systems with hundreds of spins have been studied in one and two dimensions. In the most common realizations of these platforms, spin…

Quantum Physics · Physics 2026-01-06 Wilson S. Martins , Markus Hennrich , Ferdinand Schmidt-Kaler , Igor Lesanovsky

Quantum phenomena have the potential to speed up the solution of hard optimization problems. For example quantum annealing, based on the quantum tunneling effect, has recently been shown to scale exponentially better with system size as…

Quantum Physics · Physics 2017-04-27 Simon E. Nigg , Niels Loerch , Rakesh P. Tiwari

We propose and experimentally demonstrate sequential quantum computing (SQC), a paradigm that utilizes multiple homogeneous or heterogeneous quantum processors in hybrid classical-quantum workflows. In this manner, we are able to overcome…

Laser-cooled and trapped atomic ions form an ideal standard for the simulation of interacting quantum spin models. Effective spins are represented by appropriate internal energy levels within each ion, and the spins can be measured with…

Neutral atom arrays have recently emerged as a promising platform for quantum information processing. One important remaining roadblock for the large-scale application of these systems is the ability to perform error-corrected quantum…

The logistic network design is an abstract optimization problem that, under the assumption of minimal cost, seeks the optimal configuration of the supply chain's infrastructures and facilities based on customer demand. Key economic…

Quantum Physics · Physics 2021-02-04 Yongcheng Ding , Xi Chen , Lucas Lamata , Enrique Solano , Mikel Sanz

Although a universal quantum computer is still far from reach, the tremendous advances in controllable quantum devices, in particular with solid-state systems, make it possible to physically implement "quantum simulators". Quantum…

Quantum Physics · Physics 2016-06-08 Zhixin Wang , Xiu Gu , Lian-Ao Wu , Yu-xi Liu

Large scale quantum annealing dynamics of Ising spin glasses were recently implemented on D-Wave's Advantage$2$ system on a range of lattices. Following extensive comparison to existing numerical methods, these experiments were claimed to…

Quantum Physics · Physics 2026-05-29 Joseph Tindall , Antonio Mello , Matt Fishman , Miles Stoudenmire , Dries Sels

Single atoms in dipole microtraps or optical tweezers have recently become a promising platform for quantum computing and simulation. Here we report a detailed theoretical analysis of the physics underlying an implementation of a Rydberg…

We present Learning-Driven Annealing (LDA), a framework that links individual quantum annealing evolutions into a global solution strategy to mitigate hardware constraints such as short annealing times and integrated control errors. Unlike…

Quantum Physics · Physics 2025-10-29 Sebastian Schulz , Dennis Willsch , Kristel Michielsen

Experimentally observed quantum few-body dynamics of neutral atoms excited to a Rydberg state are numerically analyzed with Lindblad master equation formalism. For this, up to five rubidium atoms are trapped with optical tweezers, arranged…

Atomic Physics · Physics 2019-04-17 Woojun Lee , Minhyuk Kim , Hanlae Jo , Yunheung Song , Jaewook Ahn

Analog models of quantum information processing, such as adiabatic quantum computation and analog quantum simulation, require the ability to subject a system to precisely specified Hamiltonians. Unfortunately, the hardware used to implement…

Quantum Physics · Physics 2014-02-25 Kevin C. Young , Robin Blume-Kohout , Daniel A. Lidar

Quantum spin liquids are elusive but paradigmatic examples of strongly correlated quantum states that are characterized by long-range quantum entanglement. Recently, the direct signatures of a gapped topological $\mathbb{Z}_2$ spin liquid…

The ability to perform entangling quantum operations with low error rates in a scalable fashion is a central element of useful quantum information processing. Neutral atom arrays have recently emerged as a promising quantum computing…

Quantum annealing (QA) has the potential to significantly improve solution quality and reduce time complexity in solving combinatorial optimization problems compared to classical optimization methods. However, due to the limited number of…

Quantum Physics · Physics 2025-04-09 Seongmin Kim , Sang-Woo Ahn , In-Saeng Suh , Alexander W. Dowling , Eungkyu Lee , Tengfei Luo