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Lazy random walks on the weighted pseudofractal scale-free networks with a perfect trap.

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Title: Lazy random walks on the weighted pseudofractal scale-free networks with a perfect trap.
Authors: Chen, Yun1 (AUTHOR) yunc_c2233@163.com, Wu, Bo2 (AUTHOR), Peng, Qingsong1 (AUTHOR), Liu, Wei1 (AUTHOR), Cao, Shanyong1 (AUTHOR)
Source: International Journal of Modern Physics C: Computational Physics & Physical Computation. Jul2026, Vol. 37 Issue 7, p1-13. 13p.
Subjects: Random walks, Scale-free network (Statistical physics), Network performance, Fractals, Particle dynamics, Computer simulation, Weighted graphs
Abstract: This paper investigates the average trapping time problem of particles performing lazy random walks on a weighted scale-free pseudofractal network. We introduced three different parameters, namely, the weight r of the edge during iteration, the probability p of particles jumping at the old node position, and the probability q of particles jumping at the new node position. By analyzing the behavior of particles at different node positions, the analytical expression for the average trapping time was obtained. Based on the analytical expression, numerical simulation graph is drawn for different parameters, and the results showed that particles using lazy random walks can improve transmission efficiency. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 189732929
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PubTypeId: academicJournal
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  Label: Title
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  Data: Lazy random walks on the weighted pseudofractal scale-free networks with a perfect trap.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Yun%22">Chen, Yun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yunc_c2233@163.com</i><br /><searchLink fieldCode="AR" term="%22Wu%2C+Bo%22">Wu, Bo</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Peng%2C+Qingsong%22">Peng, Qingsong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Wei%22">Liu, Wei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cao%2C+Shanyong%22">Cao, Shanyong</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Modern+Physics+C%3A+Computational+Physics+%26+Physical+Computation%22">International Journal of Modern Physics C: Computational Physics & Physical Computation</searchLink>. Jul2026, Vol. 37 Issue 7, p1-13. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Random+walks%22">Random walks</searchLink><br /><searchLink fieldCode="DE" term="%22Scale-free+network+%28Statistical+physics%29%22">Scale-free network (Statistical physics)</searchLink><br /><searchLink fieldCode="DE" term="%22Network+performance%22">Network performance</searchLink><br /><searchLink fieldCode="DE" term="%22Fractals%22">Fractals</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+dynamics%22">Particle dynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Weighted+graphs%22">Weighted graphs</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper investigates the average trapping time problem of particles performing lazy random walks on a weighted scale-free pseudofractal network. We introduced three different parameters, namely, the weight r of the edge during iteration, the probability p of particles jumping at the old node position, and the probability q of particles jumping at the new node position. By analyzing the behavior of particles at different node positions, the analytical expression for the average trapping time was obtained. Based on the analytical expression, numerical simulation graph is drawn for different parameters, and the results showed that particles using lazy random walks can improve transmission efficiency. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1142/S0129183125501189
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 13
        StartPage: 1
    Subjects:
      – SubjectFull: Random walks
        Type: general
      – SubjectFull: Scale-free network (Statistical physics)
        Type: general
      – SubjectFull: Network performance
        Type: general
      – SubjectFull: Fractals
        Type: general
      – SubjectFull: Particle dynamics
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Weighted graphs
        Type: general
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      – TitleFull: Lazy random walks on the weighted pseudofractal scale-free networks with a perfect trap.
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            NameFull: Chen, Yun
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            NameFull: Wu, Bo
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            NameFull: Peng, Qingsong
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            NameFull: Liu, Wei
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            NameFull: Cao, Shanyong
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            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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            – TitleFull: International Journal of Modern Physics C: Computational Physics & Physical Computation
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