Large Deviation Theory for Markov Jump Models of Chemical Reaction Networks
This talk will be the introduction to a talk Andrea Agazzi will give on
Feb 17 in the probability seminar. It deals with work I have done together
with him, and with Amir Dembo.
In my talk, I intend to explain how people deal with the differential
equations describing networks of chemical reactions. I then describe how
the discrete particle approximation is obtained. Finally, I will describe
how one derives a large class of sufficient conditions on chemical
networks, for which we were able to prove a large deviations result. This
means that there is a functional which describes accurately the
probability of transiting from one stable regime (of the continuum limit
system) to another, when the number of molecules is finite. No proofs
will be given, as they will then be explained in Agazzi's talk.