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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

Quantum advantage is well-established in centralized computing, where quantum algorithms can solve certain problems exponentially faster than classical ones. In the distributed setting, significant progress has been made in…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-17 Francesco d'Amore

The simulation of the spectra measured in nuclear magnetic resonance (NMR) spectroscopy experiments is a computationally non-trivial problem which, due to its natural interpretation as a quantum spin problem, maps in a straightforward way…

While recent breakthroughs have proven the ability of noisy intermediate-scale quantum (NISQ) devices to achieve quantum advantage in classically-intractable sampling tasks, the use of these devices for solving more practically relevant…

Quantum computers represent a radical technological breakthrough in information processing by leveraging the principles of quantum mechanics to solve highly complex problems beyond the reach of classical systems. However, in the current…

Quantum Physics · Physics 2025-08-26 Marcos Guillermo Lammers , Federico Hernán Holik , Alejandro Fernández

Recently developed quantum algorithms suggest that quantum computers can solve certain problems and perform certain tasks more efficiently than conventional computers. Among other reasons, this is due to the possibility of creating…

Quantum Physics · Physics 2007-05-23 Rolando D. Somma

Quantum computers hold the promise to solve certain computational task much more efficiently than classical computers. We review the recent experimental advancements towards a quantum computer with trapped ions. In particular, various…

Quantum Physics · Physics 2008-11-20 H. Haeffner , C. F. Roos , R. Blatt

Quantum kernels are considered as potential resources to illustrate benefits of quantum computing in machine learning. Considering the impact of hyperparameters on the performance of a classical machine learning model, it is imperative to…

Quantum Physics · Physics 2023-08-09 Diksha Sharma , Parvinder Singh , Atul Kumar

Quantum computing has the potential to outperform classical computers and is expected to play an active role in various fields. In quantum machine learning, a quantum computer has been found useful for enhanced feature representation and…

Quantum Physics · Physics 2019-11-26 Masaya Watabe , Kodai Shiba , Masaru Sogabe , Katsuyoshi Sakamoto , Tomah Sogabe

Cloud-accessible quantum processors enable direct execution of quantum algorithms on heterogeneous hardware platforms. Unlike classical systems, however, identical quantum circuits may exhibit substantially different behavior across devices…

Quantum Physics · Physics 2026-01-12 Askar Oralkhan , Temirlan Zhaxalykov

Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and under noiseless conditions, coherent processing of quantum data…

Critical decision-making issues in science, engineering, and industry are based on combinatorial optimization; however, its application is inherently limited by the NP-hard nature of the problem. A specialized paradigm of analogue quantum…

Quantum Physics · Physics 2026-02-04 Rudraksh Sharma , Ravi Katukam , Arjun Nagulapally

Benchmarking quantum computers often deals with the parameters of single qubits or gates and sometimes deals with algorithms run on an entire chip or a noisy simulator of a chip. Here we propose the idea of using protocols to benchmark…

Quantum Physics · Physics 2025-05-27 Dekel Meirom , Tal Mor , Yossi Weinstein

We present a class of hybrid classical systems using quantum co-processors and point out that unlike purely quantum computers, such hybrids can be both universal and Turing complete; we introduce such quantum-classical hybrids as…

Quantum Physics · Physics 2018-08-15 Edward H. "Ned" Allen , Cristian S. Calude

Recent developments in nanoscale experimental techniques made it possible to utilize single molecule junctions as devices for electronics and energy transfer with quantum coherence playing an important role in their thermoelectric…

Mesoscale and Nanoscale Physics · Physics 2018-03-12 Feng Chen , Yi Gao , Michael Galperin

Computational methods are the most effective tools we have besides scientific experiments to explore the properties of complex biological systems. Progress is slowing because digital silicon computers have reached their limits in terms of…

Quantum Physics · Physics 2020-04-03 Viv Kendon

Quantum computing (QC) offers a new computing paradigm that has the potential to provide significant speedups over classical computing. Each additional qubit doubles the size of the computational state space available to a quantum…

Quantum Physics · Physics 2022-05-13 Wei Tang , Margaret Martonosi

As we approach the era of quantum advantage, when quantum computers (QCs) can outperform any classical computer on particular tasks, there remains the difficult challenge of how to validate their performance. While algorithmic success can…

A major thrust in quantum algorithm development over the past decade has been the search for the quantum algorithms that will deliver practical quantum advantage first. Today's quantum computers - and even early fault-tolerant quantum…

Quantum Physics · Physics 2025-01-22 Guoming Wang , Daniel Stilck França , Gumaro Rendon , Peter D. Johnson

We run a selection of algorithms on two state-of-the-art 5-qubit quantum computers that are based on different technology platforms. One is a publicly accessible superconducting transmon device with limited connectivity, and the other is a…

Quantum Physics · Physics 2017-04-03 N. M. Linke , D. Maslov , M. Roetteler , S. Debnath , C. Figgatt , K. A. Landsman , K. Wright , C. Monroe