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Many applications of quantum computing in the near term rely on variational quantum circuits (VQCs). They have been showcased as a promising model for reaching a quantum advantage in machine learning with current noisy intermediate scale…

Quantum Physics · Physics 2022-10-25 Jonas Landman , Slimane Thabet , Constantin Dalyac , Hela Mhiri , Elham Kashefi

The quantum Fourier transform (QFT), a quantum analog of the classical Fourier transform, has been shown to be a powerful tool in developing quantum algorithms. However, in classical computing there is another class of unitary transforms,…

Quantum Physics · Physics 2007-05-23 Amir Fijany , Colin P. Williams

Quantum Fourier transform (QFT) is a widely used building block for quantum algorithms, whose scalable implementation is challenging in experiments. Here, we propose a protocol of quadratic quantum Fourier transform (QQFT), considering cold…

Quantum Physics · Physics 2022-11-02 Pei Wang , Zhijuan Huang , Xingze Qiu , Xiaopeng Li

We discuss the advantages of using the approximate quantum Fourier transform (AQFT) in algorithms which involve periodicity estimations. We analyse quantum networks performing AQFT in the presence of decoherence and show that extensive…

Quantum Physics · Physics 2009-10-30 Adriano Barenco , Artur Ekert , Kalle-Antti Suominen , Päivi Törmä

The quantum Fourier transform (QFT) has emerged as the primary tool in quantum algorithms which achieve exponential advantage over classical computation and lies at the heart of the solution to the abelian hidden subgroup problem, of which…

Quantum Physics · Physics 2007-05-23 Lisa R. Hales

In this work, we describe examples for calculating the 1-D circular convolution of signals represented by 3-qubit superpositions. The case is considered, when the discrete Fourier transform of one of the signals is known and calculated in…

Quantum Physics · Physics 2022-05-13 Artyom M. Grigoryan , Sos S. Agaian

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

In topological quantum computation the geometric details of a particle trajectory are irrelevant; only the topology matters. Taking this one step further, we consider a model of computation that disregards even the topology of the particle…

Quantum Physics · Physics 2011-06-03 Stephen P. Jordan

Algorithms to compute the quantum Fourier transform over a cyclic group are fundamental to many quantum algorithms. This paper describes such an algorithm and gives a proof of its correctness, tightening some claimed performance bounds…

Quantum Physics · Physics 2007-05-23 Chris Lomont

The Quantum Fourier transform (QFT) is a key ingredient in most quantum algorithms. We have compared various spin-based quantum computing schemes to implement the QFT from the point of view of their actual time-costs and the accuracy of the…

Quantum Physics · Physics 2014-08-07 Kavita Dorai , Dieter Suter

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 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

We study permutation groups of given minimal degree without the classical primitivity assumption. We provide sharp upper bounds on the order of a permutation group of minimal degree m and on the number of its elements of any given support.…

Quantum Physics · Physics 2007-05-23 Julia Kempe , Laszlo Pyber , Aner Shalev

We present efficient methods to interpolate data with a quantum computer that complement uploading techniques and quantum post-processing. The quantum algorithms are supported by the efficient Quantum Fourier Transform (QFT) and classical…

Quantum Physics · Physics 2023-01-04 Sergi Ramos-Calderer

A number of elegant approaches have been developed for the identification of quantum circuits which can be efficiently simulated on a classical computer. Recently, these methods have been employed to demonstrate the classical simulability…

Quantum Physics · Physics 2007-06-13 Daniel E. Browne

The quantum permutation algorithm provides computational speed-up over classical algorithms in determining the parity of a given cyclic permutation. For its $n$-qubit implementations, the number of required quantum gates scales…

Quantum Physics · Physics 2018-01-01 İ. Yalçınkaya , Z. Gedik

The fundamental question of how to best simulate quantum systems using conventional computational resources lies at the forefront of condensed matter and quantum computation. It impacts both our understanding of quantum materials and our…

Strongly Correlated Electrons · Physics 2021-09-29 Juan Carrasquilla , Di Luo , Felipe Pérez , Ashley Milsted , Bryan K. Clark , Maksims Volkovs , Leandro Aolita

In this thesis, we investigate whether quantum algorithms can be used in the field of machine learning for both long and near term quantum computers. We will first recall the fundamentals of machine learning and quantum computing and then…

Quantum Physics · Physics 2021-11-08 Jonas Landman

We discuss three applications of efficient quantum algorithms to determining properties of permutations and group automorphisms. The first uses the Bernstein-Vazirani algorithm to determine an unknown homomorphism from $Z_{p-1}^{m}$ to…

Quantum Physics · Physics 2009-11-13 Marianna Bonanome , Mark Hillery , Vladimir Buzek

Solving the intricate quantum behavior of interacting particles is key to unlocking the mysteries of condensed matter, but capturing their complex correlations across different scales remains a monumental challenge. We introduce a neural…