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Combinatorial optimization is widely regarded as a primary application for near-term quantum processors, although a definitive demonstration of the practical quantum advantage remains elusive. Recent studies have reported that both…

Quantum Physics · Physics 2026-05-21 Xian-Zhe Tao , Pavel Mosharev , Man-Hong Yung

Quantum computers promise a qualitative speedup in solving a broad spectrum of practical optimization problems. The latter can be mapped onto the task of finding low-energy states of spin glasses, which is known to be exceedingly difficult.…

Disordered Systems and Neural Networks · Physics 2024-12-31 Hao Zhang , Kelly Boothby , Alex Kamenev

Quantum annealing is an optimization technique which potentially leverages quantum tunneling to enhance computational performance. Existing quantum annealers use superconducting flux qubits with short coherence times, limited primarily by…

By analyzing the characteristics of hardware-native Ising Models and their performance on current and next generation quantum annealers, we provide a framework for determining the prospect of advantage utilizing adiabatic evolution compared…

Quantum Physics · Physics 2024-06-25 Salvatore Certo , Georgios Korpas , Andrew Vlasic , Philip Intallura

Quantum annealing is a proposed combinatorial optimization technique meant to exploit quantum mechanical effects such as tunneling and entanglement. Real-world quantum annealing-based solvers require a combination of annealing and classical…

Quantum Physics · Physics 2015-07-30 Kenneth M. Zick , Omar Shehab , Matthew French

Quantum computing is an information processing paradigm that uses quantum-mechanical properties to speedup computationally hard problems. Although promising, existing gate-based quantum computers consist of only a few dozen qubits and are…

Quantum Physics · Physics 2021-08-26 Ramin Ayanzadeh , Poulami Das , Swamit S. Tannu , Moinuddin Qureshi

One of the problems frequently mentioned as a candidate for quantum advantage is that of selecting a portfolio of financial assets to maximize returns while minimizing risk. In this paper we formulate several real-world constraints for use…

Materials Science · Physics 2022-03-10 Salvatore Certo , Anh Dung Pham , Daniel Beaulieu

Hybrid-quantum classical optimization has emerged as a promising direction for addressing financial decision problems under current quantum hardware constraints. In this work we present a practical end-to-end portfolio optimization pipeline…

Quantum annealing is a general strategy for solving difficult optimization problems with the aid of quantum adiabatic evolution. Both analytical and numerical evidence suggests that under idealized, closed system conditions, quantum…

We present an algorithm for quantum-assisted cluster analysis (QACA) that makes use of the topological properties of a D-Wave 2000Q quantum processing unit (QPU). Clustering is a form of unsupervised machine learning, where instances are…

Quantum Physics · Physics 2018-03-09 Florian Neukart , David Von Dollen , Christian Seidel

Digital-Analog Quantum Computation (DAQC) has recently been proposed as an alternative to the standard paradigm of digital quantum computation. DAQC creates entanglement through a continuous or analog evolution of the whole device, rather…

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics…

We assess the prospects for algorithms within the general framework of quantum annealing (QA) to achieve a quantum speedup relative to classical state of the art methods in combinatorial optimization and related sampling tasks. We argue for…

Quantum Physics · Physics 2021-06-22 E. J. Crosson , D. A. Lidar

Quantum computers leverage the principles of quantum mechanics to do computation with a potential advantage over classical computers. While a single classical computer transforms one particular binary input into an output after applying one…

Emerging Technologies · Computer Science 2025-03-17 Francisco Chicano , Gabiel Luque , Zakaria Abdelmoiz Dahi , Rodrigo Gil-Merino

To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or a quadratic unconstrained binary optimization (QUBO) problem and submit its coefficients to the annealer,…

Quantum Physics · Physics 2023-06-13 Elijah Pelofske , Georg Hahn , Hristo Djidjev

Vigorous optimization of quantum gates has led to bipotent quantum architectures, where the optimized gates are available for some qubits but not for others. However, such gate-level improvements limit the application of user-side…

Quantum Physics · Physics 2023-08-21 Yanjun Ji , Kathrin F. Koenig , Ilia Polian

Current quantum annealing experiments often suffer from restrictions in connectivity in the sense that only certain qubits can be coupled to each other. The most common strategy to overcome connectivity restrictions so far is by combining…

A recent experiment [Lanting et al., PRX, (2014)] claimed to provide evidence of up to $8$-qubit entanglement in a D-Wave quantum annealing device. However, entanglement was measured using qubit tunneling spectroscopy, a technique that…

Quantum Physics · Physics 2015-12-17 Tameem Albash , Itay Hen , Federico M. Spedalieri , Daniel A. Lidar

Recent theoretical and experimental studies have suggested that quantum Monte Carlo (QMC) simulation can behave similarly to quantum annealing (QA). The theoretical analysis was based on calculating transition rates between local minima, in…

Quantum Physics · Physics 2017-03-29 Evgeny Andriyash , Mohammad H. Amin

The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for current and near-term quantum devices. Despite its initial success, there is a lack of understanding involving several of its key aspects. There…

Quantum Physics · Physics 2023-03-22 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen
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