Analysis of top-swap shuffling for genome rearrangements
Nayantara Bhatnagar, Pietro Caputo, Prasad Tetali, Eric Vigoda
Abstract
We study Markov chains which model genome rearrangements. These models are useful for studying the equilibrium distribution of chromosomal lengths, and are used in methods for estimating genomic distances. The primary Markov chain studied in this paper is the top-swap Markov chain. The top-swap chain is a card-shuffling process with n cards divided over k decks, where the cards are ordered within each deck. A transition consists of choosing a random pair of cards, and if the cards lie in different decks, we cut each deck at the chosen card and exchange the tops of the two decks. We prove precise bounds on the relaxation time (inverse spectral gap) of the top-swap chain. In particular, we prove the relaxation time is Θ(n+k). This resolves an open question of Durrett.
Create a lesson
Related papers
Distribution-constrained optimal multiple stopping: the Root-type solution
Shuoqing Deng, Daxin Huang
Universality and sharp thresholds for ellipsoid fitting
Frederic Koehler, Youngtak Sohn
Local Laws and Edge Universality for Noncentral Sample Covariance Matrices
Can Hu, Jiang Hu, Zhidong Bai
Well-posedness and regularity of stochastic heat equations on moving domains
Chongyang Ren, Tusheng Zhang
Traveling Waves in Equity Markets with Rank-Based Entry and Exit
Graeme Baker, Caroline Smyth
An approximate zero bias transformation for random sums: Applications to sampling with outliers, auto insurance, and generative AI
Wasamon Jantai, Nathakhun Wiroonsri