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SUMMARY:Andrea Agazzi (Duke University)
DTSTART:20211209T160000Z
DTEND:20211209T163000Z
DTSTAMP:20260421T123835Z
UID:MoRN/39
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/MoRN/39/">La
 rge Deviations for Degenerate Markov Jump Processes</a>\nby Andrea Agazzi 
 (Duke University) as part of Seminar on the Mathematics of Reaction Networ
 ks\n\n\nAbstract\nThe dynamics of a network of chemical reactions under th
 e laws of mass action kinetics are typically modeled as a system of couple
 d ordinary differential equations. This macroscopic model can be recovered
 \, under the appropriate scaling\, as the functional law of large numbers 
 for a family of jump Markov processes capturing the discrete nature of the
  underlying\, microscopic dynamical model. The large deviations behavior o
 f these models has been recently investigated under relatively strong assu
 mptions on the existence of reactions with rates bounded away from 0\, all
 owing to guarantee the nondegeneracy of the Markov process being investiga
 ted. We show that these assumptions\, which are violated by many models of
  interest\, can be significantly relaxed\, establishing large deviations p
 rinciples for a large class of degenerate jump Markov processes.\n
LOCATION:https://researchseminars.org/talk/MoRN/39/
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