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Exit time tails from pairwise decorrelation in hidden Markov chains, with applications to dynamical percolation


 
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1. Title Title of document Exit time tails from pairwise decorrelation in hidden Markov chains, with applications to dynamical percolation
 
2. Creator Author's name, affiliation, country Alan Hammond; University of Oxford; United Kingdom
 
2. Creator Author's name, affiliation, country Elchanan Mossel; University of California, Berkeley; United States
 
2. Creator Author's name, affiliation, country Gábor Pete; Technical University of Budapest; Hungary
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) decorrelation, hidden Markov chains, hitting and exit times, spectral gap, dynamical percolation, exceptional times, scaling limits
 
3. Subject Subject classification 60J25; 60K35; 82B43
 
4. Description Abstract

Consider a Markov process $\omega_t$ at stationarity and some event $\mathcal{C}$ (a subset of the state-space of the process). A natural measure of correlations in the process is the pairwise correlation $\mathbb{P}[\omega_0,\omega_t \in \mathcal{C}] - \mathbb{P}[\omega_0 \in \mathcal{C}]^2$. A second natural measure is the probability of the continual occurrence event $\big\{ \omega_s \in \mathcal{C}, \, \forall \, s \in [0,t] \big\}$. We show that for reversible Markov chains, and any event $\mathcal{C}$, pairwise decorrelation of the event $\mathcal{C}$ implies a decay of the probability of the continual occurrence event $\big\{ \omega_s \in \mathcal{C}\, \forall \, s \in [0,t] \big\}$ as $t \to \infty$. We provide examples showing that our results are often sharp.

Our main applications are to dynamical critical percolation. Let $\mathcal{C}$ be the left-right crossing event of a large box, and let us scale time so that the expected number of changes to $\mathcal{C}$ is order 1 in unit time. We show that the continual connection event has superpolynomial decay. Furthermore, on the infinite lattice without any time scaling, the first exceptional time with an infinite cluster appears with an exponential tail.

 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s) EPSRC, NSF, ISF, DOD ONR, NSERC, EU Marie Curie Actions
 
7. Date (YYYY-MM-DD) 2012-08-22
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://ejp.ejpecp.org/article/view/2229
 
10. Identifier Digital Object Identifier 10.1214/EJP.v17-2229
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 17
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
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