2,605 research outputs found

    Connectivity in Sub-Poisson Networks

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    We consider a class of point processes (pp), which we call {\em sub-Poisson}; these are pp that can be directionally-convexly (dcxdcx) dominated by some Poisson pp. The dcxdcx order has already been shown useful in comparing various point process characteristics, including Ripley's and correlation functions as well as shot-noise fields generated by pp, indicating in particular that smaller in the dcxdcx order processes exhibit more regularity (less clustering, less voids) in the repartition of their points. Using these results, in this paper we study the impact of the dcxdcx ordering of pp on the properties of two continuum percolation models, which have been proposed in the literature to address macroscopic connectivity properties of large wireless networks. As the first main result of this paper, we extend the classical result on the existence of phase transition in the percolation of the Gilbert's graph (called also the Boolean model), generated by a homogeneous Poisson pp, to the class of homogeneous sub-Poisson pp. We also extend a recent result of the same nature for the SINR graph, to sub-Poisson pp. Finally, as examples we show that the so-called perturbed lattices are sub-Poisson. More generally, perturbed lattices provide some spectrum of models that ranges from periodic grids, usually considered in cellular network context, to Poisson ad-hoc networks, and to various more clustered pp including some doubly stochastic Poisson ones.Comment: 8 pages, 10 figures, to appear in Proc. of Allerton 2010. For an extended version see http://hal.inria.fr/inria-00497707 version

    A random version of Sperner's theorem

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    Let P(n)\mathcal{P}(n) denote the power set of [n][n], ordered by inclusion, and let P(n,p)\mathcal{P}(n,p) be obtained from P(n)\mathcal{P}(n) by selecting elements from P(n)\mathcal{P}(n) independently at random with probability pp. A classical result of Sperner asserts that every antichain in P(n)\mathcal{P}(n) has size at most that of the middle layer, (nn/2)\binom{n}{\lfloor n/2 \rfloor}. In this note we prove an analogous result for P(n,p)\mathcal{P} (n,p): If pnpn \rightarrow \infty then, with high probability, the size of the largest antichain in P(n,p)\mathcal{P}(n,p) is at most (1+o(1))p(nn/2)(1+o(1)) p \binom{n}{\lfloor n/2 \rfloor}. This solves a conjecture of Osthus who proved the result in the case when pn/lognpn/\log n \rightarrow \infty. Our condition on pp is best-possible. In fact, we prove a more general result giving an upper bound on the size of the largest antichain for a wider range of values of pp.Comment: 7 pages. Updated to include minor revisions and publication dat

    Finite Boolean Algebras for Solid Geometry using Julia's Sparse Arrays

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    The goal of this paper is to introduce a new method in computer-aided geometry of solid modeling. We put forth a novel algebraic technique to evaluate any variadic expression between polyhedral d-solids (d = 2, 3) with regularized operators of union, intersection, and difference, i.e., any CSG tree. The result is obtained in three steps: first, by computing an independent set of generators for the d-space partition induced by the input; then, by reducing the solid expression to an equivalent logical formula between Boolean terms made by zeros and ones; and, finally, by evaluating this expression using bitwise operators. This method is implemented in Julia using sparse arrays. The computational evaluation of every possible solid expression, usually denoted as CSG (Constructive Solid Geometry), is reduced to an equivalent logical expression of a finite set algebra over the cells of a space partition, and solved by native bitwise operators.Comment: revised version submitted to Computer-Aided Geometric Desig

    Counting inequivalent monotone Boolean functions

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    Monotone Boolean functions (MBFs) are Boolean functions f:0,1n0,1f: {0,1}^n \rightarrow {0,1} satisfying the monotonicity condition xyf(x)f(y)x \leq y \Rightarrow f(x) \leq f(y) for any x,y0,1nx,y \in {0,1}^n. The number of MBFs in n variables is known as the nnth Dedekind number. It is a longstanding computational challenge to determine these numbers exactly - these values are only known for nn at most 8. Two monotone Boolean functions are inequivalent if one can be obtained from the other by renaming the variables. The number of inequivalent MBFs in nn variables was known only for up to n=6n = 6. In this paper we propose a strategy to count inequivalent MBF's by breaking the calculation into parts based on the profiles of these functions. As a result we are able to compute the number of inequivalent MBFs in 7 variables. The number obtained is 490013148
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