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We study quantum walks on general graphs from the point of view of scattering theory. For a general finite graph we choose two vertices and attach one half line to each. We are interested in walks that proceed from one half line, through…

Quantum Physics · Physics 2009-11-10 Edgar Feldman , Mark Hillery

Quantum random walks represent a powerful tool for the implementation of various quantum algorithms. We consider a convolution problem for the graphs which provide quantum and classical random walks. We suggest a new method for lattices and…

Quantum Physics · Physics 2025-07-23 Roman Abramov , Leonid Fedichkin , Dmitry Tsarev , Alexander Alodjants

An ideal quantum walk transitions from one vertex to another with perfect fidelity, but in physical systems, the particle may be hindered by potential energy barriers. Then the particle has some amplitude of tunneling through the barriers,…

Quantum Physics · Physics 2016-11-10 Thomas G. Wong

Quantum walks, both discrete (coined) and continuous time, form the basis of several quantum algorithms and have been used to model processes such as transport in spin chains and quantum chemistry. The enhanced spreading and mixing…

Quantum Physics · Physics 2010-12-10 Godfrey Leung , Paul Knott , Joe Bailey , Viv Kendon

A simple random walk on a graph is a sequence of movements from one vertex to another where at each step an edge is chosen uniformly at random from the set of edges incident on the current vertex, and then transitioned to next vertex.…

Probability · Mathematics 2012-02-28 Mohammed Abdullah

A quantum walk algorithm can detect the presence of a marked vertex on a graph quadratically faster than the corresponding random walk algorithm (Szegedy, FOCS 2004). However, quantum algorithms that actually find a marked element…

Quantum Physics · Physics 2019-03-19 Andris Ambainis , András Gilyén , Stacey Jeffery , Martins Kokainis

Continuous-time quantum walks are natural tools for spatial search, where one searches for a marked vertex in a graph. Sometimes, the structure of the graph causes the walker to get trapped, such that the probability of finding the marked…

Quantum Physics · Physics 2016-08-10 Thomas G. Wong , Pascal Philipp

Recently, Ambainis gave an O(N^(2/3))-query quantum walk algorithm for element distinctness, and more generally, an O(N^(L/(L+1)))-query algorithm for finding L equal numbers. We point out that this algorithm actually solves a much more…

Quantum Physics · Physics 2018-12-20 Andrew M. Childs , Jason M. Eisenberg

Novel Markov Chain Monte Carlo (MCMC) methods have enabled the generation of large ensembles of redistricting plans through graph partitioning. However, existing algorithms such as Reversible Recombination (RevReCom) and Metropolized Forest…

Data Structures and Algorithms · Computer Science 2025-10-28 Atticus McWhorter , Daryl DeFord

Quantum computing promises to improve the information processing power to levels unreachable by classical computation. Quantum walks are heading the development of quantum algorithms for searching information on graphs more efficiently than…

The enormous successes have been made by quantum algorithms during the last decade. In this paper, we combine the quantum random walk (QRW) with the problem of data clustering, and develop two clustering algorithms based on the one…

Machine Learning · Computer Science 2008-12-09 Qiang Li , Yan He , Jing-ping Jiang

We study whether the probability distribution of a discrete quantum walk can get arbitrarily close to uniform, given that the walk starts with a uniform superposition of the outgoing arcs of some vertex. We establish a characterization of…

Combinatorics · Mathematics 2024-07-03 Hanmeng Zhan

In this work we study quantum algorithms for Hopcroft's problem which is a fundamental problem in computational geometry. Given $n$ points and $n$ lines in the plane, the task is to determine whether there is a point-line incidence. The…

Quantum Physics · Physics 2024-05-03 Vladimirs Andrejevs , Aleksandrs Belovs , Jevgēnijs Vihrovs

Quantum random walks have received much interest due to their non-intuitive dynamics, which may hold the key to a new generation of quantum algorithms. What remains a major challenge is a physical realization that is experimentally viable…

Quantum Physics · Physics 2009-12-18 K Manouchehri , J. B. Wang

In this paper, we show reduction methods for search algorithms on graphs using quantum walks. By using a graph partitioning method called equitable partition for the the given graph, we determine "effective subspace" for the search…

Quantum Physics · Physics 2018-12-18 Yusuke Ide

We present an algorithm to grow a graph with scale-free structure of {\it in-} and {\it out-links} and variable wiring diagram in the class of the world-wide Web. We then explore the graph by intentional random walks using local…

Statistical Mechanics · Physics 2009-11-10 Bosiljka Tadic

In this paper, we provide faster algorithms for computing various fundamental quantities associated with random walks on a directed graph, including the stationary distribution, personalized PageRank vectors, hitting times, and escape…

Data Structures and Algorithms · Computer Science 2016-11-03 Michael B. Cohen , Jon Kelner , John Peebles , Richard Peng , Aaron Sidford , Adrian Vladu

In all existing quantum walk models, the assumption about a pre-existing fixed background causal structure is always made and has been taken for granted. Nevertheless, in this work we will get rid of this tacit assumption especially by…

Quantum Physics · Physics 2022-02-15 Yuanbo Chen , Yoshihiko Hasegawa

There are presently two models for quantum walks on graphs. The "coined" walk uses discrete time steps, and contains, besides the particle making the walk, a second quantum system, the coin, that determines the direction in which the…

Quantum Physics · Physics 2009-11-10 Mark Hillery , Janos Bergou , Edgar Feldman

Random walk-based node embedding algorithms have attracted a lot of attention due to their scalability and ease of implementation. Previous research has focused on different walk strategies, optimization objectives, and embedding learning…

Machine Learning · Computer Science 2025-01-23 Konstantin Kutzkov
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