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We present a theoretical framework for the analysis of amplitude transfer in Quantum Variational Algorithms (QVAs) for combinatorial optimisation with mixing unitaries defined by vertex-transitive graphs, based on their continuous-time…

Quantum Physics · Physics 2024-06-24 Edric Matwiejew , Jingbo B. Wang

It was recently shown that continuous-time quantum walks on dynamic graphs, i.e., sequences of static graphs whose edges change at specific times, can implement a universal set of quantum gates. This result treated all isolated vertices as…

Quantum Physics · Physics 2019-12-25 Thomas G. Wong

Quantum walks, both discrete (coined) and continuous time, form the basis of several recent quantum algorithms. Here we use numerical simulations to study the properties of discrete, coined quantum walks. We investigate the variation in the…

Quantum Physics · Physics 2008-04-21 Ivens Carneiro , Meng Loo , Xibai Xu , Mathieu Girerd , Viv Kendon , Peter L. Knight

We introduce quantum walks with a time-dependent coin, and show how they include, as a particular case, the generalized quantum walk recently studied by Wojcik et al. {[}Phys. Rev. Lett. \textbf{93}, 180601(2004){]} which exhibits…

Quantum Physics · Physics 2009-11-11 M. C. Banuls , C. Navarrete , A. Perez , Eugenio Roldan , J. C. Soriano

In this paper we demonstrate that the efficiency of quantum algorithms can be significantly altered by malicious manipulation of the input data. We exemplify the possibility of attacks on quantum spatial search based on Szegedy walk. We…

Quantum Physics · Physics 2019-09-27 Adam Glos , Jarosław Adam Miszczak

This paper proposes a computational procedure that applies a quantum algorithm to train classical artificial neural networks. The goal of the procedure is to apply quantum walk as a search algorithm in a complete graph to find all synaptic…

Quantum Physics · Physics 2021-09-06 Luciano S. de Souza , Jonathan H. A. de Carvalho , Tiago A. E. Ferreira

Random walks are a fundamental primitive used in many machine learning algorithms with several applications in clustering and semi-supervised learning. Despite their relevance, the first efficient parallel algorithm to compute random walks…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-12-02 Michael Kapralov , Silvio Lattanzi , Navid Nouri , Jakab Tardos

The quantum walk dynamics obey the laws of quantum mechanics with an extra locality constraint, which demands that the evolution operator is local in the sense that the walker must visit the neighboring locations before endeavoring to…

Quantum Physics · Physics 2023-05-23 Caue F. T. Silva , Daniel Posner , Renato Portugal

Graph representations are a powerful concept for solving complex problems across natural science, as patterns of connectivity can give rise to a multitude of emergent phenomena. Graph-based approaches have proven particularly fruitful in…

We study the phase discrimination problem, in which we want to decide whether the eigenphase $\theta\in(-\pi,\pi]$ of a given eigenstate $|\psi\rangle$ with eigenvalue $e^{i\theta}$ is zero or not, using applications of the unitary $U$…

Quantum Physics · Physics 2025-04-22 Guanzhong Li , Lvzhou Li , Jingquan Luo

In this work, we generalize the recently-introduced graph composition framework to the non-boolean setting. A quantum algorithm in this framework is represented by a hypergraph, where each hyperedge is adjacent to multiple vertices. The…

Quantum Physics · Physics 2025-10-07 Arjan Cornelissen

This paper examines the performance of spatial search where the Grover diffusion operator is replaced by continuous-time quantum walks on a class of interdependent networks. We prove that for a set of optimal quantum walk times and marked…

Quantum Physics · Physics 2021-08-26 S. Marsh , J. B. Wang

Quantum walk serves as a versatile tool for universal quantum computing and algorithmic research. However, the implementation of discrete-time quantum walks (DTQWs) with superconducting circuits is still constrained by some limitations such…

The question of whether quantum spatial search in two dimensions can be made optimal has long been an open problem. We report progress towards its resolution by showing that the oracle complexity for target location can be made optimal, by…

Quantum Physics · Physics 2020-01-07 Abhijith J. , Apoorva Patel

Graph embedding, representing local and global neighborhood information by numerical vectors, is a crucial part of the mathematical modeling of a wide range of real-world systems. Among the embedding algorithms, random walk-based algorithms…

Social and Information Networks · Computer Science 2022-07-06 Sarmad N. Mohammed , Semra Gündüç

The Scattering Quantum Random Walk scheme has found success as a basis for search algorithms on highly symmetric graph structures. In this paper we examine its effectiveness at locating a specially marked vertex on square grid graphs,…

Quantum Physics · Physics 2019-01-23 Daniel Koch

We introduce a new framework to analyze quantum algorithms with the renormalization group (RG). To this end, we present a detailed analysis of the real-space RG for discrete-time quantum walks on fractal networks and show how deep insights…

Quantum Physics · Physics 2018-01-16 Stefan Boettcher , Shanshan Li

In this survey paper we give an intuitive treatment of the discrete time quantization of classical Markov chains. Grover search and the quantum walk based search algorithms of Ambainis, Szegedy and Magniez et al. will be stated as quantum…

Quantum Physics · Physics 2008-08-04 Miklos Santha

We propose a modified version of the quantum walk-based search algorithm created by Shenvi, Kempe and Whaley, also known as the SKW algorithm. In our version of the algorithm, we modified the evolution operator of the system so that it is…

Advances in recent years have made it possible to explore quantum dots as a viable technology for scalable quantum information processing. Charge qubits for example can be realized in the lowest bound states of coupled quantum dots and the…

Quantum Physics · Physics 2009-11-13 K Manouchehri , J. B. Wang