TL;DR
This paper explores Markovian random networks, focusing on their structure, associated fields, flows, and maps, providing insights into their properties and behaviors.
Contribution
It introduces a novel analysis of Eulerian networks generated by Markov loops, linking probabilistic and combinatorial aspects.
Findings
Characterization of Markovian Eulerian networks
Analysis of associated fields and flows
Insights into network structure and behavior
Abstract
We investigate random Eulerian networks defined by Markov loops and the associated fields, flows and maps.
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Taxonomy
TopicsData Management and Algorithms · Stochastic processes and statistical mechanics · Mathematical Dynamics and Fractals