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Rutas más cortas de orden superior en hipergrafos

Berné L Nortier1,2, Simon Dobson1, Federico Battiston2

  • 1University of St. Andrews, Department of Computer Science, St. Andrews KY16, Scotland.

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PubMed
Resumen
Este resumen es generado por máquina.

Este estudio introduce el tamaño de la ruta para medir la conectividad de orden superior en hipergrafos. Las interacciones no diádicas son vitales para la conectividad del sistema, mientras que los bordes diádicos conectan nodos periféricos, especialmente en sistemas variables en el tiempo.

Palabras clave:
conectividad de orden superiorhipergrafostamaño de la rutalazos no diádicossistemas complejosredes empíricasredes dinámicas

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Área de la Ciencia:

  • Ciencia de Redes
  • Teoría de Grafos
  • Análisis de Datos

Sus antecedentes:

  • Las redes complejas exhiben conectividad emergente a partir de interacciones locales.
  • Los hipergrafos modelan redes con interacciones de orden superior, pero su conectividad está poco estudiada.

Objetivo del estudio:

  • Introducir el tamaño de la ruta para caracterizar la conectividad de orden superior.
  • Cuantificar la relevancia de los lazos no diádicos para rutas más cortas eficientes en redes empíricas.
  • Analizar redes con y sin información temporal.

Principales métodos:

  • Se introdujo el 'tamaño de la ruta' como una métrica novedosa para la conectividad de hipergrafos.
  • Se analizaron diversas redes empíricas, incluidas aquellas con datos temporales.
  • Se compararon los resultados con modelos nulos aleatorizados.

Principales resultados:

  • Los lazos no diádicos son a menudo centrales y vitales para la conectividad general del sistema.
  • Los bordes diádicos siguen siendo cruciales para conectar nodos periféricos.
  • Este efecto es más pronunciado en sistemas variables en el tiempo.

Conclusiones:

  • Las interacciones no diádicas juegan un papel importante en la conectividad de sistemas complejos.
  • El tamaño de la ruta ofrece una herramienta valiosa para comprender las estructuras de hipergrafos.
  • Los hallazgos avanzan la comprensión de sistemas con interacciones de orden superior.