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Quantum computers can efficiently solve problems which are widely believed to lie beyond the reach of classical computers. In the near-term, hybrid quantum-classical algorithms, which efficiently embed quantum hardware in classical…

Quantum Physics · Physics 2026-05-07 Ananda Roy , Robert M. Konik , David Rogerson

The quest for quantum computers is motivated by their potential for solving problems that defy existing, classical, computers. The theory of computational complexity, one of the crown jewels of computer science, provides a rigorous…

Statistical Mechanics · Physics 2010-09-10 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi

The ability to extract relevant information is critical to learning. An ingenious approach as such is the information bottleneck, an optimisation problem whose solution corresponds to a faithful and memory-efficient representation of…

Quantum Physics · Physics 2023-03-08 Masahito Hayashi , Yuxiang Yang

Fault-tolerant quantum computations require alternating quantum and classical computations, where the classical computations prove vital in detecting and correcting errors in the quantum computation. Recently, interest in using these…

Quantum Physics · Physics 2025-09-09 Niels M. P. Neumann

It is shown how consistent histories quantum cosmology can be realised through Isham's Histories Projection Operator consistent histories scheme. This is done by using an affine algebra instead of a canonical one and also by using cocycle…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Smaragda Kessari

As quantum computers mature, the applicability in practice becomes more important. Many uses of quantum computers will be hybrid, with classical computers still playing an important role in operating and using the quantum computer. The term…

Quantum Physics · Physics 2023-11-15 Frank Phillipson , Niels Neumann , Robert Wezeman

A broad class of hybrid quantum-classical algorithms known as "variational algorithms" have been proposed in the context of quantum simulation, machine learning, and combinatorial optimization as a means of potentially achieving a quantum…

Quantum Physics · Physics 2021-04-09 Aram Harrow , John Napp

Quantum machine learning algorithms could provide significant speed-ups over their classical counterparts; however, whether they could also achieve good generalization remains unclear. Recently, two quantum perceptron models which give a…

Quantum Physics · Physics 2022-06-22 Mathieu Roget , Giuseppe Di Molfetta , Hachem Kadri

A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal…

Quantum Physics · Physics 2017-04-19 Jun Li , Xiaodong Yang , Xinhua Peng , Chang-Pu Sun

We consider classical and quantum algorithms which have a duality property: roughly, either the algorithm provides some nontrivial improvement over random or there exist many solutions which are significantly worse than random. This enables…

Quantum Physics · Physics 2019-11-13 M. B. Hastings

We introduce an optimisation method for variational quantum algorithms and experimentally demonstrate a 100-fold improvement in efficiency compared to naive implementations. The effectiveness of our approach is shown by obtaining…

Simulating quantum circuits using classical computers lets us analyse the inner workings of quantum algorithms. The most complete type of simulation, strong simulation, is believed to be generally inefficient. Nevertheless, several…

Quantum Physics · Physics 2013-02-25 T. H. Johnson , J. D. Biamonte , S. R. Clark , D. Jaksch

In a recent paper Griffiths claims that the consistent histories interpretation of quantum mechanics gives rise to results that contradict those obtained from the Bohm interpretation. This is in spite of the fact that both claim to provide…

Quantum Physics · Physics 2007-05-23 B. J. Hiley , O. J. E. Maroney

While it seems possible that quantum computers may allow for algorithms offering a computational speed-up over classical algorithms for some problems, the issue is poorly understood. We explore this computational speed-up by investigating…

Quantum Physics · Physics 2010-06-09 Alastair A. Abbott , Cristian S. Calude

It is known that quantum computers yield a speed-up for certain discrete problems. Here we want to know whether quantum computers are useful for continuous problems. We study the computation of the integral of functions from the classical…

Quantum Physics · Physics 2013-04-16 Erich Novak

Hybrid variational quantum algorithms are promising for solving practical problems, such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and quantum error correction on noisy quantum computers.…

In the last couple of decades, the world has seen several stunning instances of quantum algorithms that provably outperform the best classical algorithms. For most problems, however, it is currently unknown whether quantum algorithms can…

We reconsider the Decoherent Histories approach to Quantum Mechanics and we analyze some problems related to its interpretation which, according to us, have not been adequately clarified by its proponents. We put forward some assumptions…

Quantum Physics · Physics 2007-05-23 Angelo Bassi , GianCarlo Ghirardi

Numerical simulation of quantum systems is crucial to further our understanding of natural phenomena. Many systems of key interest and importance, in areas such as superconducting materials and quantum chemistry, are thought to be described…

Quantum Physics · Physics 2010-11-17 Katherine L Brown , William J Munro , Vivien M Kendon

Variational quantum algorithms (VQAs) provide a promising approach to achieve quantum advantage in the noisy intermediate-scale quantum era. In this era, quantum computers experience high error rates and quantum error detection and…

Emerging Technologies · Computer Science 2021-09-07 Salonik Resch , Anthony Gutierrez , Joon Suk Huh , Srikant Bharadwaj , Yasuko Eckert , Gabriel Loh , Mark Oskin , Swamit Tannu
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