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Related Experiment Video

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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
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Communicability in temporal networks.

Ernesto Estrada1

  • 1Department of Mathematics and Statistics, Institute of Complex Systems, University of Strathclyde, 26 Richmond Street, Glasgow G11HX, United Kingdom.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|November 16, 2013
PubMed
Summary

This study introduces a new method to measure information flow in temporal networks using quantum random walks. This approach reveals hidden communication patterns and their persistence over time.

Area of Science:

  • Network Science
  • Quantum Physics
  • Information Theory

Background:

  • Temporal networks exhibit complex dynamics crucial for information flow.
  • Quantifying communicability in these networks remains a challenge.
  • Existing methods often overlook temporal dependencies.

Purpose of the Study:

  • To develop a first-principles method for quantifying communicability in temporal networks.
  • To analyze the impact of network structure and time on information perdurability.
  • To uncover hidden communication patterns within temporal and topological network features.

Main Methods:

  • Utilizing the imaginary-time propagator of a quantum random walk.
  • Applying the method to both streaming and nonstreaming temporal networks.

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  • Studying synthetic and real-world network data.

    • Main Results:

    • The proposed method accurately quantifies pairwise communicability.
    • System temperature influences information perdurability.
    • Communicability effectively identifies underlying communication patterns.

    Conclusions:

    • The quantum random walk approach offers a robust framework for analyzing temporal networks.
    • This method provides novel insights into information dynamics and network structure.
    • The findings have implications for understanding complex systems and information diffusion.