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Quantum algorithms have the potential to provide exponential speedups over some of the best known classical algorithms. These speedups may enable quantum devices to solve currently intractable problems such as those in the fields of…

Quantum Physics · Physics 2018-12-13 Ciarán Ryan-Anderson

We introduce hybrid classical-quantum algorithms for problems involving a large classical data set X and a space of models Y such that a quantum computer has superposition access to Y but not X. These algorithms use data reduction…

Quantum Physics · Physics 2020-04-07 Aram W. Harrow

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

In modelling complex processes, the potential past data that influence future expectations are immense. Models that track all this data are not only computationally wasteful but also shed little light on what past data most influence the…

Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, including gate optimization, quantum-assisted compiling, quantum…

Quantum Physics · Physics 2024-11-27 Vu Tuan Hai , Nguyen Tan Viet , Jesus Urbaneja , Nguyen Vu Linh , Lan Nguyen Tran , Le Bin Ho

Quantum computers can execute algorithms that dramatically outperform classical computation. As the best-known example, Shor discovered an efficient quantum algorithm for factoring integers, whereas factoring appears to be difficult for…

Quantum Physics · Physics 2010-01-19 Andrew M. Childs , Wim van Dam

In this thesis, I present several results on quantum statistical inference in the following two directions. Firstly, I demonstrate that quantum algorithms can be applied to enhance the computing and training of Gaussian processes (GPs), a…

Quantum Physics · Physics 2018-12-13 Zhikuan Zhao

Quantum machine learning has the potential for broad industrial applications, and the development of quantum algorithms for improving the performance of neural networks is of particular interest given the central role they play in machine…

Quantum Physics · Physics 2019-09-09 Jonathan Allcock , Chang-Yu Hsieh , Iordanis Kerenidis , Shengyu Zhang

Generic quantum search algorithm searches for target entity in an unsorted database by repeatedly applying canonical Grover's quantum rotation transform to reach near the vicinity of the target entity represented by a basis state in the…

Databases · Computer Science 2011-02-14 Ashish Mani , C Patvardhan

We study some extensions of Grover's quantum searching algorithm. First, we generalize the Grover iteration in the light of a concept called amplitude amplification. Then, we show that the quadratic speedup obtained by the quantum searching…

Quantum Physics · Physics 2017-01-03 Gilles Brassard , Peter Hoyer , Alain Tapp

Quantum computing promises to provide the next step up in computational power for diverse application areas. In this review, we examine the science behind the quantum hype, and the breakthroughs required to achieve true quantum advantage in…

Quantum Physics · Physics 2025-09-26 R. Au-Yeung , B. Camino , O. Rathore , V. Kendon

Advances in quantum technologies are accelerating the demand for optical quantum state sensors that combine high precision, versatility, and scalability within a unified hardware platform. Quantum reservoir computing offers a powerful route…

Quantum computers are believed to bring computational advantages in simulating quantum many body systems. However, recent works have shown that classical machine learning algorithms are able to predict numerous properties of quantum systems…

Quantum Physics · Physics 2024-12-23 Riccardo Molteni , Casper Gyurik , Vedran Dunjko

State-of-the-art quantum algorithms routinely tune dynamically parametrized cost functionals for combinatorics, machine learning, equation-solving, or energy minimization. However, large search complexity often demands many (noisy) quantum…

Quantum Physics · Physics 2022-01-12 Mogens Dalgaard , Felix Motzoi , Jacob Sherson

Understanding the capabilities of classical simulation methods is key to identifying where quantum computers are advantageous. Not only does this ensure that quantum computers are used only where necessary, but also one can potentially…

The main approach to hybrid quantum-classical neural networks (QNN) is employing quantum computing to build a neural network (NN) that has quantum features, which is then optimized classically. Here, we propose a different strategy: to use…

Quantum Physics · Physics 2025-04-22 Stefan-Alexandru Jura , Mihai Udrescu

The intensive pursuit for quantum advantage in terms of computational complexity has further led to a modernized crucial question: {\it When and how will quantum computers outperform classical computers?} The next milestone is undoubtedly…

Quantum Physics · Physics 2024-05-07 Nobuyuki Yoshioka , Tsuyoshi Okubo , Yasunari Suzuki , Yuki Koizumi , Wataru Mizukami

Quantum computing has made remarkable strides in recent years, as demonstrated by quantum supremacy experiments and the realization of high-fidelity, fault-tolerant gates. However, a major obstacle persists: practical real-world…

A novel class of hybrid quantum-classical algorithms based on the variational approach have recently emerged from separate proposals addressing, for example, quantum chemistry and combinatorial problems. These algorithms provide an…

Quantum Physics · Physics 2017-01-09 Gian Giacomo Guerreschi , Mikhail Smelyanskiy

A careful study of the classical/quantum connection with the aid of coherent states offers new insights into various technical problems. This analysis includes both canonical as well as closely related affine quantization procedures. The…

High Energy Physics - Theory · Physics 2015-06-12 John R. Klauder
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