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Quantum Information Processing

Quantum transport on large-scale sparse regular networks by using continuous-time quantum walk

  • 01-08-2020
Published in:
Authors
Xi Li
Hanwu Chen
Mingyou Wu
Yue Ruan
Zhihao Liu
Jianing Tan
Published in
Quantum Information Processing | Issue 8/2020

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Abstract

A large-scale sparse regular network (LSSRN) is a type of sparse regular graph that has been broadly studied in the field of complex networks. The conventional approach of eigendecomposition cannot be used to achieve quantum transport based on continuous-time quantum walks (CTQW) on LSSRNs. This work proposes a new approach, namely the counting of walks on an LSSRN, to investigate the characteristics of quantum transport based on CTQW. The estimations of transport probability indicate that (1) it is more likely for a node to return to itself in quantum transport than in classical transport, (2) with the increase in the network degree, the return probability decays more quickly and (3) the transport probability starting from a given vertex to another vertex decreases when the distance between them increases.

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previous article Performance improvement of plug-and-play dual-phase-modulated continuous-variable quantum key distribution with quantum catalysis
next article Fault-tolerant quantum error correction code preparation in UBQC
Title
Quantum transport on large-scale sparse regular networks by using continuous-time quantum walk
Authors
Xi Li
Hanwu Chen
Mingyou Wu
Yue Ruan
Zhihao Liu
Jianing Tan
Publication date
01-08-2020
Publisher
Springer US
Published in
Quantum Information Processing / Issue 8/2020
Print ISSN: 1570-0755
Electronic ISSN: 1573-1332
DOI
https://doi.org/10.1007/s11128-020-02731-4
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