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In this paper we isolate the combinatorial property responsible (at least in part) for the computational speedups recently observed in some quantum walk algorithms. We find that continuous-time quantum walks can exploit the covering space…

Quantum Physics · Physics 2007-05-23 Tobias J. Osborne , Simone Severini

We contribute to fulfil the long-lasting gap in the understanding of the spatial search with multiple marked vertices. The theoretical framework is that of discrete-time quantum walks (QW), \textit{i.e.} local unitary matrices that drive…

Quantum Physics · Physics 2023-01-06 Mathieu Roget , Hachem Kadri , Giuseppe Di Molfetta

We show that a quantum walk process can be used to construct and secure quantum memory. More precisely, we show that a localized quantum walk with temporal disorder can be engineered to store the information of a single, unknown qubit on a…

Quantum Physics · Physics 2015-04-22 C. M. Chandrashekar , Th. Busch

Quantum walks, in virtue of the coherent superposition and quantum interference, possess exponential superiority over its classical counterpart in applications of quantum searching and quantum simulation. The quantum enhanced power is…

In a recent work by Novo et al. (Sci. Rep. 5, 13304, 2015), the invariant subspace method was applied to the study of continuous-time quantum walk (CTQW). The method helps to reduce a graph into a simpler version that allows more…

Quantum Physics · Physics 2018-02-22 Chen-Fu Chiang , Chang-Yu Hsieh

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

Similarity search approaches based on graph walks have recently attained outstanding speed-accuracy trade-offs, taking aside the memory requirements. In this paper, we revisit these approaches by considering, additionally, the memory…

Computer Vision and Pattern Recognition · Computer Science 2018-06-07 Matthijs Douze , Alexandre Sablayrolles , Hervé Jégou

Recently Mc Gettrick [1] introduced and studied a discrete-time 2-state quantum walk (QW) with a memory in one dimension. He gave an expression for the amplitude of the QW by path counting method. Moreover he showed that the return…

Quantum Physics · Physics 2010-11-23 Norio Konno , Takuya Machida

In this paper, we consider the problem of planning a path for a robot to monitor a known set of features of interest in an environment. We represent the environment as a graph with vertex weights and edge lengths. The vertices represent…

Data Structures and Algorithms · Computer Science 2012-10-17 Soroush Alamdari , Elaheh Fata , Stephen L. Smith

A randomly walking quantum particle searches in Grover's $\Theta(\sqrt{N})$ iterations for a marked vertex on the complete graph of $N$ vertices by repeatedly querying an oracle that flips the amplitude at the marked vertex, scattering by a…

Quantum Physics · Physics 2015-09-22 Andris Ambainis , Thomas G. Wong

In this paper, we study the fundamental problem of random walk for network embedding. We propose to use non-Markovian random walk, variants of vertex-reinforced random walk (VRRW), to fully use the history of a random walk path. To solve…

Social and Information Networks · Computer Science 2020-02-12 Wenyi Xiao , Huan Zhao , Vincent W. Zheng , Yangqiu Song

Quantum walks with memory(QWM) are a type of modified quantum walks that record the walker's latest path. As we know, only two kinds of QWM are presented up to now. It is desired to design more QWM for research, so that we can explore the…

Quantum Physics · Physics 2016-04-20 Dan Li , Michael Mc Gettrick , Fei Gao , Jie Xu , Qiao-Yan Wen

In this work, we consider the spatial search for a general marked state on graphs by continuous time quantum walks. As a simplest case, we compute the amplitude expression of the search for the multi-vertex uniform superposition state on…

Mathematical Physics · Physics 2018-04-10 Xi Li , Hanwu Chen , Yue Ruan , Zhihao Liu , Mengke Xu , Jianing Tan

We construct a new type of quantum walks on simplicial complexes as a natural extension of the well-known Szegedy walk on graphs. One can numerically observe that our proposing quantum walks possess linear spreading and localization as in…

Mathematical Physics · Physics 2015-08-05 Kaname Matsue , Osamu Ogurisu , Etsuo Segawa

Based on the Dirac representation of Maxwell equations we present an explicit, discrete space-time, quantum walk-inspired algorithm suitable for simulating the electromagnetic wave propagation and scattering from inhomogeneities within…

Searching for an unknown marked vertex on a given graph (also known as spatial search) is an extensively discussed topic in the area of quantum algorithms, with a plethora of results based on different quantum walk models and targeting…

Quantum Physics · Physics 2025-06-27 Guanzhong Li , Jingquan Luo , Shiguang Feng , Lvzhou Li

We study the discrete quantum walk on a regular graph $X$ that assigns negative identity coins to marked vertices $S$ and Grover coins to the unmarked ones. We find combinatorial bases for the eigenspaces of the transtion matrix, and derive…

Combinatorics · Mathematics 2024-12-19 Amulya Mohan , Hanmeng Zhan

We introduce the Peierls substitution to a two-dimensional discrete-time quantum walk on a square lattice to examine the spreading dynamics and the coin-position entanglement in the presence of an artificial gauge field. We use the ratio of…

Quantum Physics · Physics 2015-10-28 İ. Yalçınkaya , Z. Gedik

Graph clustering is an important technique to understand the relationships between the vertices in a big graph. In this paper, we propose a novel random-walk-based graph clustering method. The proposed method restricts the reach of the…

Social and Information Networks · Computer Science 2016-06-22 Honglei Zhang , Jenni Raitoharju , Serkan Kiranyaz , Moncef Gabbouj

This paper proposes a self-supervised objective for learning representations that localize objects under occlusion - a property known as object permanence. A central question is the choice of learning signal in cases of total occlusion.…

Computer Vision and Pattern Recognition · Computer Science 2022-06-14 Pavel Tokmakov , Allan Jabri , Jie Li , Adrien Gaidon