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Related papers: Analog-Digital Quantum Computing with Quantum Anne…

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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…

Demonstrations of quantum advantage for certain sampling problems have generated considerable excitement for quantum computing and have further spurred the development of circuit-model quantum computers, which represent quantum programs as…

Quantum Physics · Physics 2025-06-19 Javier Gonzalez-Conde , Zachary Morrell , Marc Vuffray , Tameem Albash , Carleton Coffrin

Quantum information processing offers dramatic speedups, yet is famously susceptible to decoherence, the process whereby quantum superpositions decay into mutually exclusive classical alternatives, thus robbing quantum computers of their…

Quantum Physics · Physics 2014-08-21 Kristen L. Pudenz , Tameem Albash , Daniel A. Lidar

Quantum computing can provide speedups in solving many problems as the evolution of a quantum system is described by a unitary operator in an exponentially large Hilbert space. Such unitary operators change the phase of their eigenstates…

Quantum Physics · Physics 2024-01-23 Youle Wang , Lei Zhang , Zhan Yu , Xin Wang

The development of quantum annealing machines (QAMs) based on superconducting qubits has progressed greatly in recent years and these machines are now widely used in both academia and commerce. On the other hand, QAMs based on semiconductor…

Quantum Physics · Physics 2019-03-27 Tetsufumi Tanamoto , Yoshifumi Nishi , Jun Deguchi

Quantum hardware has the potential to efficiently solve computationally difficult problems in physics and chemistry to reap enormous practical rewards. Analogue quantum simulation accomplishes this by using the dynamics of a controlled…

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…

Although quantum computing hardware has evolved significantly in recent years, spurred by increasing industrial and government interest, the size limitation of current generation quantum computers remains an obstacle when applying these…

Quantum Physics · Physics 2020-01-20 Gideon Bass , Max Henderson , Joshua Heath , Joseph Dulny

Scaling the number of qubits while maintaining high-fidelity quantum gates remains a key challenge for quantum computing. Presently, superconducting quantum processors with >50-qubits are actively available. For such systems,…

Analog quantum simulation is widely considered a step on the path to fault tolerant quantum computation. If based on current noisy hardware, the accuracy of an analog simulator will degrade after just a few time steps, especially when…

Quantum Physics · Physics 2020-07-01 Nathan K. Lysne , Kevin W. Kuper , Pablo M. Poggi , Ivan H. Deutsch , Poul S. Jessen

The ability to engineer parallel, programmable operations between desired qubits within a quantum processor is central for building scalable quantum information systems. In most state-of-the-art approaches, qubits interact locally,…

The past few years have witnessed the concrete and fast spreading of quantum technologies for practical computation and simulation. In particular, quantum computing platforms based on either trapped ions or superconducting qubits have…

Quantum Physics · Physics 2020-04-21 Francesco Tacchino , Alessandro Chiesa , Stefano Carretta , Dario Gerace

Simulating quantum many-body systems is a highly demanding task since the required resources grow exponentially with the dimension of the system. In the case of fermionic systems, this is even harder since nonlocal interactions emerge due…

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

Drawing independent samples from high-dimensional probability distributions represents the major computational bottleneck for modern algorithms, including powerful machine learning frameworks such as deep learning. The quest for discovering…

Quantum Physics · Physics 2022-10-13 Marc Vuffray , Carleton Coffrin , Yaroslav A. Kharkov , Andrey Y. Lokhov

Quantum Hamiltonian Computing is a recent approach that uses quantum systems, in particular a single molecule, to perform computational tasks. Within this approach, we present explicit methods to construct logic gates using two different…

Quantum Physics · Physics 2019-06-18 Omid Faizy Namarvar , Olivier Giraud , Bertrand Georgeot , Christian Joachim

Quantum computers are expected to be able to solve mathematical problems that cannot be solved using conventional computers. Many of these problems are of practical importance, especially in the areas of cryptography and secure…

Quantum Physics · Physics 2007-05-23 T. B. Pittman , B. C. Jacobs , J. D. Franson

Quantum machine learning is one of the fields where quantum computers are expected to bring advantages over classical methods. However, the limited size of current computers restricts the exploitation of the full potential of quantum…

Quantum Physics · Physics 2025-11-10 Juan C. Boschero , Ward van der Schoot , Niels M. P. Neumann

Quantum computing is no longer a nascent field. Programmable quantum annealing devices with more that 1000 qubits are commercially available. How does one know that a putative quantum annealing device is indeed quantum? How should one go…

Quantum Physics · Physics 2017-06-23 Joshua Job , Daniel Lidar

Quantum annealing allows for quantum fluctuations to be used used to assist in finding the solution to some of the worlds most challenging computational problems. Recently, this field has attracted much interest because of the construction…

Quantum Physics · Physics 2022-07-26 Nicholas Chancellor