309 research outputs found
Stability of the stochastic matching model
We introduce and study a new model that we call the {\em matching model}.
Items arrive one by one in a buffer and depart from it as soon as possible but
by pairs. The items of a departing pair are said to be {\em matched}. There is
a finite set of classes \maV for the items, and the allowed matchings depend
on the classes, according to a {\em matching graph} on \maV. Upon arrival, an
item may find several possible matches in the buffer. This indeterminacy is
resolved by a {\em matching policy}. When the sequence of classes of the
arriving items is i.i.d., the sequence of buffer-contents is a Markov chain,
whose stability is investigated. In particular, we prove that the model may be
stable if and only if the matching graph is non-bipartite
Uniform and Bernoulli measures on the boundary of trace monoids
Trace monoids and heaps of pieces appear in various contexts in
combinatorics. They also constitute a model used in computer science to
describe the executions of asynchronous systems. The design of a natural
probabilistic layer on top of the model has been a long standing challenge. The
difficulty comes from the presence of commuting pieces and from the absence of
a global clock. In this paper, we introduce and study the class of Bernoulli
probability measures that we claim to be the simplest adequate probability
measures on infinite traces. For this, we strongly rely on the theory of trace
combinatorics with the M\"obius polynomial in the key role. These new measures
provide a theoretical foundation for the probabilistic study of concurrent
systems.Comment: 34 pages, 5 figures, 27 reference
Randomly growing braid on three strands and the manta ray
Consider the braid group and the nearest neighbor
random walk defined by a probability with support
. The rate of escape of the walk is explicitly expressed
in function of the unique solution of a set of eight polynomial equations of
degree three over eight indeterminates. We also explicitly describe the
harmonic measure of the induced random walk on quotiented by its center.
The method and results apply, mutatis mutandis, to nearest neighbor random
walks on dihedral Artin groups.Comment: Published at http://dx.doi.org/10.1214/105051606000000754 in the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
Probabilistic cellular automata and random fields with i.i.d. directions
Let us consider the simplest model of one-dimensional probabilistic cellular
automata (PCA). The cells are indexed by the integers, the alphabet is {0, 1},
and all the cells evolve synchronously. The new content of a cell is randomly
chosen, independently of the others, according to a distribution depending only
on the content of the cell itself and of its right neighbor. There are
necessary and sufficient conditions on the four parameters of such a PCA to
have a Bernoulli product invariant measure. We study the properties of the
random field given by the space-time diagram obtained when iterating the PCA
starting from its Bernoulli product invariant measure. It is a non-trivial
random field with very weak dependences and nice combinatorial properties. In
particular, not only the horizontal lines but also the lines in any other
direction consist in i.i.d. random variables. We study extensions of the
results to Markovian invariant measures, and to PCA with larger alphabets and
neighborhoods
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