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In this work we seek to generalize the connection between traversable wormholes and quantum channels. We do this via a connection between traversable wormholes and graph geometries on which we can perform quantum random walks for signal…

High Energy Physics - Theory · Physics 2019-06-06 Ning Bao , Vincent P. Su , Mykhaylo Usatyuk

Topological quantum computation is a promising technique to achieve large-scale, error-corrected computation. Quantum hardware is used to create a large, 3-dimensional lattice of entangled qubits while performing computation requires…

Quantum Physics · Physics 2014-04-04 Alexandru Paler , Simon J. Devitt , Kae Nemoto , Ilia Polian

High-energy physics simulations traditionally rely on classical Monte Carlo methods to model complex particle interactions, often incurring significant computational costs. In this paper, we introduce a novel quantum-enhanced simulation…

Quantum Physics · Physics 2025-02-28 Euimin Lee , Sangmin Lee , Shiho Kim

Quantum computing (QC) is a new computational paradigm whose foundations relate to quantum physics. Notable progress has been made, driving the birth of a series of quantum-based algorithms that take advantage of quantum computational…

Quantum Physics · Physics 2022-02-22 Yehui Tang , Junchi Yan , Hancock Edwin

We demonstrate an implementation of the hitting time of a discrete time quantum random walk on cubelike graphs using IBM's Qiskit platform. Our implementation is based on efficient circuits for the Grover and Shift operators. We verify the…

Quantum Physics · Physics 2021-09-01 Jaideep Mulherkar , Rishikant Rajdeepak , V Sunitha

We consider to what extent quantum walks can constitute models of thermalization, analogously to how classical random walks can be models for classical thermalization. In a quantum walk over a graph, a walker moves in a superposition of…

Quantum Physics · Physics 2024-06-03 Shyam Dhamapurkar , Oscar Dahlsten

The aim of this work is to develop a framework for realising quantum network algorithms with the use of prior knowledge about the structure of the network. We seek to obtain computational methods that allows us to locally determine network…

Quantum Physics · Physics 2017-01-30 Przemysław Sadowski

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

Several research groups are giving special attention to quantum walks recently, because this research area have been used with success in the development of new efficient quantum algorithms. A general simulator of quantum walks is very…

Quantum Physics · Physics 2012-05-18 F. L. Marquezino , R. Portugal

Quantum walks provide a framework for understanding and designing quantum algorithms that is both intuitive and universal. To leverage the computational power of these walks, it is important to be able to programmably modify the graph a…

Quantum Physics · Physics 2022-09-07 Aaron W. Young , William J. Eckner , Nathan Schine , Andrew M. Childs , Adam M. Kaufman

Several models have been proposed to build evolution operators to perform quantum walks in a theoretical way, although when wanting to map the resulting evolution operators into quantum circuits to run them in quantum computers, it is often…

Quantum Physics · Physics 2023-04-05 Allan Wing-Bocanegra , Salvador E. Venegas-Andraca

Quantum Cryptography is a rapidly developing field of research that benefits from the properties of Quantum Mechanics in performing cryptographic tasks. Quantum walks are a powerful model for quantum computation and very promising for…

Quantum Physics · Physics 2016-02-04 C. Vlachou , J. Rodrigues , P. Mateus , N. Paunković , A. Souto

In this work, Transition Probability Matrix (TPM) is proposed as a new method for extracting the features of nodes in the graph. The proposed method uses random walks to capture the connectivity structure of a node's close neighborhood. The…

Machine Learning · Computer Science 2023-03-07 Sarmad N. Mohammed , Semra Gündüç

This work focuses on understanding the quantum message complexity of two central problems in distributed computing, namely, leader election and agreement in synchronous message-passing communication networks. We show that quantum…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-12 Fabien Dufoulon , Frédéric Magniez , Gopal Pandurangan

We present an introduction to coined quantum walks on regular graphs, which have been developed in the past few years as an alternative to quantum Fourier transforms for underpinning algorithms for quantum computation. We then describe our…

Quantum Physics · Physics 2018-03-28 Viv Kendon , Ben Tregenna

This paper surveys the field of quantum computer algorithms. It gives a taste of both the breadth and the depth of the known algorithms for quantum computers, focusing on some of the more recent results. It begins with a brief review of…

Quantum Physics · Physics 2010-01-07 Jamie Smith , Michele Mosca

Diverse facets Of the Theory of Quantum Walks on Graph are reviewed Till now .In specific, Quantum network routing, Quantum Walk Search Algorithm, Element distinctness associated to the eigenvalues of Graphs and the use of these relation…

Data Structures and Algorithms · Computer Science 2018-02-01 Tewabe Chekole

Graph-structured data arise in wide applications, such as computer vision, bioinformatics, and social networks. Quantifying similarities among graphs is a fundamental problem. In this paper, we develop a framework for computing graph…

Machine Learning · Statistics 2018-09-11 Zhen Zhang , Mianzhi Wang , Yijian Xiang , Yan Huang , Arye Nehorai

Multi-dimensional quantum walks can exhibit highly non-trivial topological structure, providing a powerful tool for simulating quantum information and transport systems. We present a flexible implementation of a 2D optical quantum walk on a…

Random walk kernels have been introduced in seminal work on graph learning and were later largely superseded by kernels based on the Weisfeiler-Leman test for graph isomorphism. We give a unified view on both classes of graph kernels. We…

Machine Learning · Computer Science 2023-01-18 Nils M. Kriege
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