Graph distances in scale-free percolation: the logarithmic case

Hao, Nannan and Heydenreich, Markus (2022): Graph distances in scale-free percolation: the logarithmic case. In: Journal of Applied Probability, Vol. 60, No. 1: pp. 295-313

Abstract

Scale-free percolation is a stochastic model for complex networks. In this spatial random graph model, vertices x, y is an element of Z(d) are linked by an edge with probability depending on independent and identically distributed vertex weights and the Euclidean distance vertical bar x - y vertical bar. Depending on the various parameters involved, we get a rich phase diagram. We study graph distance and compare it to the Euclidean distance of the vertices. Our main attention is on a regime where graph distances are (poly-)logarithmic in the Euclidean distance. We obtain improved bounds on the logarithmic exponents. In the light tail regime, the correct exponent is identified.

• Item Type: Journal article
• Faculties: Mathematics, Computer Science and Statistics > Computer Science
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science
• ISSN: 0021-9002
• Language: English
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 386248531