Benvenuti nell'Anagrafe della Ricerca d'Ateneo
La valutazione delle attività di ricerca che si svolgono nelle università ha assunto un'importanza rilevante sia per l'intero sistema universitario sia all'interno di ogni singolo ateneo. Roma Tre si è quindi dotata di idonei strumenti informativi in grado di supportare al meglio le azioni di monitoraggio e di valutazione delle attività di ricerca svolte nei propri dipartimentied ha realizzato una Anagrafe della Ricerca di Ateneo.
EnglishWe study the asymptotic hitting time τ(n) of a family of Markov pro- cesses X(n) to a target set G(n) when the process starts from a “trap” defined by very general properties. We give an explicit description of the law of X(n) conditioned to stay within the trap, and from this we deduce the exponen- tial distribution of τ(n). Our approach is very broad—it does not require re- versibility, the target G does not need to be a rare event and the traps and the limit on n can be of very general nature—and leads to explicit bounds on the deviations of τ (n) from exponentially. We provide two nontrivial examples to which our techniques directly apply.
Fernandez, R., Manzo, F., Nardi, F.R., Scoppola, E., & Sohier, J. (2016). Conditioned, quasi-stationary, restricted measures and escape from metastable states. THE ANNALS OF APPLIED PROBABILITY, 26(2), 760-793 [10.1214/15-AAP1102].
| Titolo: | Conditioned, quasi-stationary, restricted measures and escape from metastable states | |
| Autori: | ||
| Data di pubblicazione: | 2016 | |
| Rivista: | ||
| Citazione: | Fernandez, R., Manzo, F., Nardi, F.R., Scoppola, E., & Sohier, J. (2016). Conditioned, quasi-stationary, restricted measures and escape from metastable states. THE ANNALS OF APPLIED PROBABILITY, 26(2), 760-793 [10.1214/15-AAP1102]. | |
| Abstract: | We study the asymptotic hitting time τ(n) of a family of Markov pro- cesses X(n) to a target set G(n) when the process starts from a “trap” defined by very general properties. We give an explicit description of the law of X(n) conditioned to stay within the trap, and from this we deduce the exponen- tial distribution of τ(n). Our approach is very broad—it does not require re- versibility, the target G does not need to be a rare event and the traps and the limit on n can be of very general nature—and leads to explicit bounds on the deviations of τ (n) from exponentially. We provide two nontrivial examples to which our techniques directly apply. | |
| Handle: | http://hdl.handle.net/11590/318444 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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