1,843 research outputs found
Trickle-down processes and their boundaries
It is possible to represent each of a number of Markov chains as an evolving
sequence of connected subsets of a directed acyclic graph that grow in the
following way: initially, all vertices of the graph are unoccupied, particles
are fed in one-by-one at a distinguished source vertex, successive particles
proceed along directed edges according to an appropriate stochastic mechanism,
and each particle comes to rest once it encounters an unoccupied vertex.
Examples include the binary and digital search tree processes, the random
recursive tree process and generalizations of it arising from nested instances
of Pitman's two-parameter Chinese restaurant process, tree-growth models
associated with Mallows' phi model of random permutations and with
Schuetzenberger's non-commutative q-binomial theorem, and a construction due to
Luczak and Winkler that grows uniform random binary trees in a Markovian
manner. We introduce a framework that encompasses such Markov chains, and we
characterize their asymptotic behavior by analyzing in detail their Doob-Martin
compactifications, Poisson boundaries and tail sigma-fields.Comment: 62 pages, 8 figures, revised to address referee's comment
Limit Laws for Functions of Fringe trees for Binary Search Trees and Recursive Trees
We prove limit theorems for sums of functions of subtrees of binary search
trees and random recursive trees. In particular, we give simple new proofs of
the fact that the number of fringe trees of size in the binary search
tree and the random recursive tree (of total size ) asymptotically has a
Poisson distribution if , and that the distribution is
asymptotically normal for . Furthermore, we prove similar
results for the number of subtrees of size with some required property , for example the number of copies of a certain fixed subtree . Using
the Cram\'er-Wold device, we show also that these random numbers for different
fixed subtrees converge jointly to a multivariate normal distribution. As an
application of the general results, we obtain a normal limit law for the number
of -protected nodes in a binary search tree or random recursive tree.
The proofs use a new version of a representation by Devroye, and Stein's
method (for both normal and Poisson approximation) together with certain
couplings
Regular resolution for CNF of bounded incidence treewidth with few long clauses
We demonstrate that Regular Resolution is FPT for two restricted families of
CNFs of bounded incidence treewidth. The first includes CNFs having at most
clauses whose removal results in a CNF of primal treewidth at most . The
parameters we use in this case are and . The second class includes CNFs
of bounded one-sided (incidence) treewdth, a new parameter generalizing both
primal treewidth and incidence pathwidth. The parameter we use in this case is
the one-sided treewidth
Solving Non-homogeneous Nested Recursions Using Trees
The solutions to certain nested recursions, such as Conolly's C(n) =
C(n-C(n-1))+C(n-1-C(n-2)), with initial conditions C(1)=1, C(2)=2, have a
well-established combinatorial interpretation in terms of counting leaves in an
infinite binary tree. This tree-based interpretation, which has a natural
generalization to a k-term nested recursion of this type, only applies to
homogeneous recursions, and only solves each recursion for one set of initial
conditions determined by the tree. In this paper, we extend the tree-based
interpretation to solve a non-homogeneous version of the k-term recursion that
includes a constant term. To do so we introduce a tree-grafting methodology
that inserts copies of a finite tree into the infinite k-ary tree associated
with the solution of the corresponding homogeneous k-term recursion. This
technique can also be used to solve the given non-homogeneous recursion with
various sets of initial conditions.Comment: 14 page
On the enumeration of tanglegrams and tangled chains
Tanglegrams are a special class of graphs appearing in applications
concerning cospeciation and coevolution in biology and computer science. They
are formed by identifying the leaves of two rooted binary trees. We give an
explicit formula to count the number of distinct binary rooted tanglegrams with
matched vertices, along with a simple asymptotic formula and an algorithm
for choosing a tanglegram uniformly at random. The enumeration formula is then
extended to count the number of tangled chains of binary trees of any length.
This includes a new formula for the number of binary trees with leaves. We
also give a conjecture for the expected number of cherries in a large randomly
chosen binary tree and an extension of this conjecture to other types of trees
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