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Abstract
We present here a new and universal approach for the study of random and/or trees, unifying in one framework many different models, including some novel ones not yet understood in the literature. An and/or tree is a Boolean expression represented in (one of) its tree shapes. Fix an integer k, take a sequence of random (rooted) trees of increasing size, say (t_{n})_{n≥1}, and label each of these random trees uniformly at random in order to get a random Boolean expression on k variables. We prove that, under rather weak local conditions on the sequence of random trees (t_{n})_{n≥1}, the distribution induced on Boolean functions by this procedure converges as n tends to infinity. In particular, we characterize two different behaviors of this limit distribution depending on the shape of the local limit of (t_{n})_{n≥1} : a degenerate case when the local limit has no leaves; and a non‐degenerate case, which we are able to describe in more details under stronger conditions. In this latter case, we provide a relationship between the probability of a given Boolean function and its complexity. The examples covered by this unified framework include trees that interpolate between models with logarithmic typical distances (such as random binary search trees) and other ones with square root typical distances (such as conditioned Galton–Watson trees).
Original language  English 

Pages (fromto)  15–58 
Number of pages  44 
Journal  Random Structures and Algorithms 
Volume  53 
Issue number  1 
Early online date  11 Jan 2018 
DOIs  
Publication status  Published  1 Aug 2018 
Keywords
 and/or trees
 local limit
 random Boolean functions
 random trees
ASJC Scopus subject areas
 Software
 General Mathematics
 Computer Graphics and ComputerAided Design
 Applied Mathematics
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Dive into the research topics of 'And/or trees: a local limit point of view'. Together they form a unique fingerprint.Projects
 1 Finished

Emergence of Condensation in Stochastic Systems
Morters, P.
Engineering and Physical Sciences Research Council
1/08/13 → 31/08/16
Project: Research council
Profiles

Cecile Mailler
 Department of Mathematical Sciences  Reader
 Probability Laboratory at Bath
 EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
Person: Research & Teaching, Researcher