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Recent research has demonstrated that quantum computers can solve certain types of problems substantially faster than the known classical algorithms. These problems include factoring integers and certain physics simulations. Practical…

Quantum Physics · Physics 2009-10-30 Emanuel Knill , Raymond Laflamme , Wojciech H. Zurek

High-throughput approximations of quantum mechanics calculations and combinatorial experiments have been traditionally used to reduce the search space of possible molecules, drugs and materials. However, the interplay of structural and…

Quantum Physics · Physics 2019-10-29 Alain Tchagang , Julio Valdés

We put forward a Quantum Amplitude Estimation algorithm delivering superior performance (lower quantum computational complexity and faster classical computation parts) compared to the approaches available to-date. The algorithm does not…

Quantum Physics · Physics 2024-07-25 Alet Roux , Tomasz Zastawniak

Quantum control is an essential tool for the operation of quantum technologies such as quantum computers, simulators, and sensors. Although there are sophisticated theoretical tools for developing quantum control protocols, formulating…

Quantum Physics · Physics 2013-04-02 Hanhan Li , Alireza Shabani , Mohan Sarovar , Birgitta K. Whaley

We report experimental implementation of discrete Fourier transformation(DFT) on a nuclear magnetic resonance(NMR) quantum computer. Experimental results agree with theoretical results. Using the pulse sequences we introduced, DFT can be…

Quantum Physics · Physics 2007-05-23 Liping Fu , Jun Luo , Li Xiao , Xizhi Zeng

Randomized algorithms such as qDRIFT provide an efficient framework for quantum simulation by sampling terms from a decomposition of the system's generator. However, existing error bounds for qDRIFT scale quadratically with the norm of the…

Quantum Physics · Physics 2025-06-23 I. J. David , I. Sinayskiy , F. Petruccione

Quantum Fourier transform is of primary importance in many quantum algorithms. In order to eliminate the destructive effects of decoherence induced by couplings between the quantum system and its environment, we propose a robust scheme for…

Quantum Physics · Physics 2007-05-23 Jian-wu Wu , Chun-wen Li , Re-bing Wu

Quantum key distribution (QKD) and quantum message encryption protocols promise a secure way to distribute information while detecting eavesdropping. However, current protocols may suffer from significantly reduced eavesdropping protection…

Quantum Physics · Physics 2025-05-27 Nicholas J. C. Papadopoulos , Kirby Linvill

High-quality quantum state generation is essential for advanced quantum information processing, including quantum communication, quantum sensing, and quantum computing. In practice, various error sources degrade the quality of quantum…

A book about turning high-degree optimization problems into quadratic optimization problems that maintain the same global minimum (ground state). This book explores quadratizations for pseudo-Boolean optimization, perturbative gadgets used…

Quantum Physics · Physics 2019-09-24 Nike Dattani

The quantum Fourier transform (QFT) is a crucial subroutine in many quantum algorithms. In this paper, we study the exact lower bound problem of CNOT gate complexity for fault-tolerant QFT. First, we consider approximating the ancilla-free…

Quantum Physics · Physics 2024-09-05 Qiqing Xia , Huiqin Xie , Li Yang

Fault-tolerant schemes can use error correction to make a quantum computation arbitrarily ac- curate, provided that errors per physical component are smaller than a certain threshold and in- dependent of the computer size. However in…

Quantum Physics · Physics 2022-02-24 Marco Fellous-Asiani , Jing Hao Chai , Robert S. Whitney , Alexia Auffèves , Hui Khoon Ng

Automatic differentiation is an invaluable feature of machine learning and quantum machine learning software libraries. In this work it is shown how quantum automatic differentiation can be used to solve the condensed-matter problem of…

Quantum Physics · Physics 2022-11-29 Olivia Di Matteo , R. M. Woloshyn

Quantum computing promises the ability to compute properties of quantum systems exponentially faster than classical computers. Quantum advantage is achieved when a practical problem is solved more efficiently on a quantum computer than on a…

Quantum Physics · Physics 2025-12-03 William A. Simon , Peter J. Love

We study the impact of quantum computation on the fundamental problem of testing the property of distributions. In particular, we focus on testing whether two unknown classical distributions are close or far enough, and propose the…

Quantum Physics · Physics 2023-02-14 Lvzhou Li , Jingquan Luo

The implementation and practicality of quantum algorithms highly hinge on the quality of operations within a quantum processor. Therefore, including realistic error models in quantum computing simulation platforms is crucial for testing…

Quantum Physics · Physics 2021-04-12 Ahmed Abid Moueddene , Nader Khammassi , Koen Bertels , Carmen G. Almudever

In this work we study the encoding of smooth, differentiable multivariate functions in quantum registers, using quantum computers or tensor-network representations. We show that a large family of distributions can be encoded as…

Quantum Physics · Physics 2021-04-21 Juan José García-Ripoll

Since simulating quantum computers requires exponentially more classical resources, efficient algorithms are extremely helpful. We analyze algorithms that create single qubit and specific controlled qubit matrix representations of gates.…

Quantum Physics · Physics 2007-05-23 Eric Hsu

We show how the quantum fast Fourier transform (QFFT) can be made exact for arbitrary orders (first for large primes). For most quantum algorithms only the quantum Fourier transform of order $2^n$ is needed, and this can be done exactly.…

Quantum Physics · Physics 2007-05-23 Michele Mosca , Christof Zalka

Given a time series vector, how can we efficiently compute a specified part of Fourier coefficients? Fast Fourier transform (FFT) is a widely used algorithm that computes the discrete Fourier transform in many machine learning applications.…

Machine Learning · Computer Science 2020-08-31 Yong-chan Park , Jun-Gi Jang , U Kang