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We consider a random bistochastic matrix of size of the form where is a uniformly distributed permutation matrix and is a given bistochastic matrix. Under mild sparsity and regularity assumptions on , we prove that the second largest eigenvalue of is essentially bounded by the normalized Hilbert-Schmidt norm of when grows large. We apply this result to random walks on random regular digraphs and to shuffle-and-fold maps of the unit interval popularized in fluid mixing protocols.

生成讲解博客的中文版本

生成AI智能校验的中文版本