10 papers
The rank and layer distributions in random recursive trees
Huck Stepanyants, P. L. Krapivsky, Harrison Hartle +1
The distribution of node depths in a network is crucial for analyzing network structure. Two measures, rank and layer, quantify how deep inside a network a node is. The rank is the…
Universal fluctuations of first discoveries in competitive exploration
Arthur Plaud, P. L. Krapivsky, S. Redner +1
Random exploration is usually quantified by how fast new space is found, from the range of a single walker to the territory collectively covered by many walkers. In competitive exp…
Anomalous scaling in redirection networks
Harrison Hartle, P. L. Krapivsky, S. Redner +1
In networks that grow by isotropic redirection (IR), a new node selects an initial target node uniformly at random and attaches to a randomly chosen neighbor of the target. The eme…
Self-reinforcing cascades: A spreading model for beliefs or products of varying intensity or quality
Laurent Hébert-Dufresne, Juniper Lovato, Giulio Burgio +3
Models of how things spread often assume that transmission mechanisms are fixed over time. However, social contagions--the spread of ideas, beliefs, innovations--can lose or gain i…
Finite-time consensus in a compromise process
P. L. Krapivsky, A. Yu. Plakhov
A compromise process describes the evolution of opinions through binary interactions. Opinions are real numbers, and at each step, two randomly selected agents reach a compromise b…
Growing unlabeled networks
Harrison Hartle, Brennan Klein, Dmitri Krioukov +1
Models of growing networks are a central topic in network science. In these models, vertices are usually labeled by their arrival time, distinguishing even those node pairs whose s…