




Publications  Computing the Least Fixed Point of Positive Polynomial Systems





Reference:
Javier Esparza, Stefan Kiefer, and Michael Luttenberger. Computing the least fixed point of positive polynomial systems. Technical report, arXiv.org, January 2010. Available at http://arxiv.org/abs/1001.0340.
Abstract:
We consider equation systems of the form X_1 = f_1(X_1, ..., X_n), ..., X_n = f_n(X_1, ..., X_n) where f_1, ..., f_n are polynomials with positive real coefficients. In vector form we denote such an equation system by X = f(X) and call f a system of positive polynomials, short SPP. Equation systems of this kind appear naturally in the analysis of stochastic models like stochastic contextfree grammars (with numerous applications to natural language processing and computational biology), probabilistic programs with procedures, websurfing models with back buttons, and branching processes. The least nonnegative solution mu f of an SPP equation X = f(X) is of central interest for these models. Etessami and Yannakakis have suggested a particular version of Newton's method to approximate mu f.
We extend a result of Etessami and Yannakakis and show that Newton's method starting at 0 always converges to mu f. We obtain lower bounds on the convergence speed of the method. For socalled strongly connected SPPs we prove the existence of a threshold k_f such that for every i >= 0 the (k_f+i)th iteration of Newton's method has at least i valid bits of mu f. The proof yields an explicit bound for k_f depending only on syntactic parameters of f. We further show that for arbitrary SPP equations Newton's method still converges linearly: there are k_f>=0 and alpha_f>0 such that for every i>=0 the (k_f+alpha_f i)th iteration of Newton's method has at least i valid bits of mu f. The proof yields an explicit bound for alpha_f; the bound is exponential in the number of equations, but we also show that it is essentially optimal. Constructing a bound for k_f is still an open problem. Finally, we also provide a geometric interpretation of Newton's method for SPPs.
Suggested BibTeX entry:
@techreport{EKL10:SICOMPTR,
author = {Javier Esparza and Stefan Kiefer and Michael Luttenberger},
institution = {arXiv.org},
month = {January},
note = {Available at http://arxiv.org/abs/1001.0340},
title = {Computing the Least Fixed Point of Positive Polynomial Systems},
year = {2010}
}




