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Bibliographic Details
Main Authors: Benedetti, Claudia, Gianani, Ilaria
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2301.13842
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author Benedetti, Claudia
Gianani, Ilaria
author_facet Benedetti, Claudia
Gianani, Ilaria
contents Control and characterization of networks is a paramount step for the development of many quantum technologies. Even for moderate-sized networks, this amounts to explore an extremely vast parameters space in search for the couplings defining the network topology. Here we explore the use of a genetic algorithm to retrieve the topology of a network from the measured probability distribution obtained from the evolution of a continuous-time quantum walk on the network. Our result shows that the algorithm is capable of efficiently retrieving the required information even in the presence of noise.
format Preprint
id arxiv_https___arxiv_org_abs_2301_13842
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Identifying network topologies via quantum walk distributions
Benedetti, Claudia
Gianani, Ilaria
Quantum Physics
Control and characterization of networks is a paramount step for the development of many quantum technologies. Even for moderate-sized networks, this amounts to explore an extremely vast parameters space in search for the couplings defining the network topology. Here we explore the use of a genetic algorithm to retrieve the topology of a network from the measured probability distribution obtained from the evolution of a continuous-time quantum walk on the network. Our result shows that the algorithm is capable of efficiently retrieving the required information even in the presence of noise.
title Identifying network topologies via quantum walk distributions
topic Quantum Physics
url https://arxiv.org/abs/2301.13842