A central limit theorem for a one-dimensional polymer measure

被引:0
|
作者
Konig, W
机构
来源
ANNALS OF PROBABILITY | 1996年 / 24卷 / 02期
关键词
central limit theorem; self-avoiding and self-repellent random walk; ergodic Markov chains; large deviations;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Let (S-n)n is an element of N-0 be a random walk on the integers having bounded steps. The self-repellent (resp., self-avoiding) walk is a sequence of transformed path measures which discourage (resp., forbid) self-intersections. This is used as a model for polymers. Previously, we proved a law of large numbers; that is, we showed the convergence of \S-n\/n toward a positive number Theta under the polymer measure. The present paper proves a classical central limit theorem for the self-repellent and self-avoiding walks; that is, we prove the asymptotic normality of (S-n - Theta n)/root n for large n. The proof refines and continues results and techniques developed previously.
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页码:1012 / 1035
页数:24
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