NONEXTENSIVE CONDENSATION IN REINFORCED BRANCHING PROCESSES
成果类型:
Article
署名作者:
Dereich, Steffen; Mailler, Cecile; Morters, Peter
署名单位:
University of Munster; University of Bath
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
DOI:
10.1214/16-AAP1268
发表日期:
2017
页码:
2539-2568
关键词:
preferential attachment
摘要:
We study a class of branching processes in which a population consists of immortal individuals equipped with a fitness value. Individuals produce offspring with a rate given by their fitness, and offspring may either belong to the same family, sharing the fitness of their parent, or be founders of new families, with a fitness sampled from a fitness distribution mu. Examples that can be embedded in this class are stochastic house-of-cards models, urn models with reinforcement and the preferential attachment tree of Bianconi and Barabasi. Our focus is on the case when the fitness distribution mu has bounded support and regularly varying tail at the essential supremum. In this case, there exists a condensation phase, in which asymptotically a proportion of mass in the empirical fitness distribution of the overall population condenses in the maximal fitness value. Our main results describe the asymptotic behaviour of the size and fitness of the largest family at a given time. In particular, we show that as time goes to infinity the size of the largest family is always negligible compared to the overall population size. This implies that condensation, when it arises, is nonextensive and emerges as a collective effort of several families none of which can create a condensate on its own. Our result disproves claims made in the physics literature in the context of preferential attachment trees.