Homología persistente de redes complejas
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El análisis topológico de datos y de estructuras complejas con un alto número de unidades interdependientes se ha convertido en una de las ramas más activas de las matemáticas. Las enormes cantidades de datos que se manejan en la actualidad y el descubrimiento de nuevos tipos de redes en biología, informática y ciencias sociales han obligado a desarrollar técnicas novedosas de procesamiento que permitan revelar las estructuras topológicas subyacentes. La homología persistente es una de ellas y sirve para identificar las propiedades topológicas relevantes en una nube de datos o para codificar un grafo y descartar aquellas características que son simplemente ruido o no sobreviven a un análisis más fino. En este trabajo presentamos las definiciones básicas de homología persistente,
su codificación mediante unos diagramas, conocidos como códigos de barras, que muestran visualmente aquellas características topológicas que perduran a lo largo del tiempo, y damos algunas aplicaciones para el estudio de diversos tipos de grafos importantes en el análisis de redes complejas.
Topological data and complex structure analysis with a high number of interdependent units have become one of the most active branches of mathematics. Nowadays, huge quantities of data are handled, and so the discovery of new types of networks in biology, computing and social science has led to the de velopment of newfangled processing techniques so as to reveal the underlying topological structures. Persistent homology is one of these techniques and allows the identification of relevant topological properties within a data cloud or the codification of a graph in order to dismiss noisy features or the ones that do not survive to a more refined analysis. Basic definitions are introduced to deal with persistent homology, as well as certain diagrams, known as barcodes, which help on the visualization of those topological features that persist through time, and some applications are given to study different types of graphs in complex network analysis.
Topological data and complex structure analysis with a high number of interdependent units have become one of the most active branches of mathematics. Nowadays, huge quantities of data are handled, and so the discovery of new types of networks in biology, computing and social science has led to the de velopment of newfangled processing techniques so as to reveal the underlying topological structures. Persistent homology is one of these techniques and allows the identification of relevant topological properties within a data cloud or the codification of a graph in order to dismiss noisy features or the ones that do not survive to a more refined analysis. Basic definitions are introduced to deal with persistent homology, as well as certain diagrams, known as barcodes, which help on the visualization of those topological features that persist through time, and some applications are given to study different types of graphs in complex network analysis.
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Traballo de Fin de Máster en Matemáticas. Curso 2015-2016
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