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The presence of a bias field, encoding some information about the target state, can enhance the performance of quantum optimization methods. Here we investigate the effect of such a bias field on the outcome of quantum annealing sampling,…

Quantum Physics · Physics 2022-10-19 Tobias Graß

We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to the optimal state. Quantum fluctuations cause transitions between states and thus play the same role as thermal…

Statistical Mechanics · Physics 2009-10-31 Tadashi Kadowaki , Hidetoshi Nishimori

Quantum annealing method has been widely attracted attention in statistical physics and information science since it is expected to be a powerful method to obtain the best solution of optimization problem as well as simulated annealing. The…

Disordered Systems and Neural Networks · Physics 2017-08-23 Shu Tanaka , Ryo Tamura

In this work we investigate the capabilities of a hybrid quantum-classical procedure to explore the solution space using the D-Wave $2000Q^{TM}$ Quantum Annealer device. Here we study the ability of the Quantum hardware to solve the Number…

Quantum Physics · Physics 2020-03-10 Luca Asproni , Davide Caputo , Blanca Silva , Giovanni Fazzi , Marco Magagnini

Quantum annealing is a contender to solve combinatorial optimization problems based on quantum dynamics. While significant efforts have been undertaken to investigate the quality of the solutions and the required runtimes, much less…

Statistical Mechanics · Physics 2023-06-05 Artem Rakcheev , Andreas M. Läuchli

Quantum annealers are specialized quantum computers for solving combinatorial optimization problems using special characteristics of quantum computing (QC), such as superposition, entanglement, and quantum tunneling. Theoretically, quantum…

Software Engineering · Computer Science 2024-07-29 Xinyi Wang , Asmar Muqeet , Tao Yue , Shaukat Ali , Paolo Arcaini

Quantum annealing is a generic name of quantum algorithms to use quantum-mechanical fluctuations to search for the solution of optimization problem. It shares the basic idea with quantum adiabatic evolution studied actively in quantum…

Quantum Physics · Physics 2009-11-13 Satoshi Morita , Hidetoshi Nishimori

We study the spin-boson model (SBM) with two spins in staggered biases by a numerically exact method based on variational matrix product states. Several observables such as the magnetization, the entanglement entropy between the two spins…

Statistical Mechanics · Physics 2021-05-05 Yan-Zhi Wang , Shu He , Liwei Duan , Qing-Hu Chen

Quantum annealing is a type of analog computation that aims to use quantum mechanical fluctuations in search of optimal solutions of QUBO (quadratic unconstrained binary optimization) or, equivalently, Ising problems. Since NP-hard problems…

Quantum Physics · Physics 2023-04-14 Elijah Pelofske , Georg Hahn , Hristo N. Djidjev

An electron inside liquid helium forms a bubble of 17 \AA in radius. In an external magnetic field, the two-level system of a spin 1/2 electron is ideal for the implementation of a qubit for quantum computing. The electron spin is well…

Other Condensed Matter · Physics 2007-05-23 Weijun Yao

Quantum annealing is getting increasing attention in combinatorial optimization. The quantum processing unit by D-Wave is constructed to approximately solve Ising models on so-called Chimera graphs. Ising models are equivalent to quadratic…

Data Structures and Algorithms · Computer Science 2019-04-30 Michael Juenger , Elisabeth Lobe , Petra Mutzel , Gerhard Reinelt , Franz Rendl , Giovanni Rinaldi , Tobias Stollenwerk

We introduce and review briefly the phenomenon of quantum annealing and analog computation. The role of quantum fluctuation (tunneling) in random systems with rugged (free) energy landscapes having macroscopic barriers are discussed to…

Statistical Mechanics · Physics 2023-10-16 Bikas K Chakrabarti , Sudip Mukherjee

Quantum annealing provides a promising route for the development of quantum optimization devices, but the usefulness of such devices will be limited in part by the range of implementable problems as dictated by hardware constraints. To…

Quantum Physics · Physics 2015-10-14 Walter Vinci , Tameem Albash , Gerardo Paz-Silva , Itay Hen , Daniel A. Lidar

Quantum Annealing (QA) is one of the most promising frameworks for quantum optimization. Here, we focus on the problem of minimizing complex classical cost functions associated with prototypical discrete neural networks, specifically the…

Quantum Physics · Physics 2023-05-17 Guglielmo Lami , Pietro Torta , Giuseppe E. Santoro , Mario Collura

Quantum-classical hybrid algorithms offer a promising strategy for tackling computationally challenging problems, such as the maximum independent set (MIS) problem that plays a crucial role in areas like network design and data analysis.…

Quantum Physics · Physics 2025-06-17 Seokho Jeong , Juyoung Park , Jaewook Ahn

Entanglement forging based variational algorithms leverage the bi-partition of quantum systems for addressing ground state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous…

Coherent states offer a promising path for near-term quantum computing due to their inherent protection against bit-flip noise. However, their large photon numbers can be challenging for numerical simulation. This paper introduces an…

We study the low energy states of finite spin chains with isotropic (Heisenberg) and anisotropic (XY and Ising-like) exchange interaction with uniform and non-uniform coupling constants. We show that for an odd number of sites a spin…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 Florian Meier , Jeremy Levy , Daniel Loss

We demonstrate how quantum field theory problems can be embedded on quantum annealers. The general method we use is a discretisation of the field theory problem into a general Ising model, with the continuous field values being encoded into…

High Energy Physics - Phenomenology · Physics 2021-01-20 Steven Abel , Nicholas Chancellor , Michael Spannowsky

We present a classical algorithm to find approximate solutions to instances of quadratic unconstrained binary optimisation. The algorithm can be seen as an analogue of quantum annealing under the restriction of a product state space, where…

Quantum Physics · Physics 2023-02-14 Joseph Bowles , Alexandre Dauphin , Patrick Huembeli , José Martinez , Antonio Acín