Seemingly stable chemical kinetics can be stable, marginally stable, or unstable
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Abstract
We present three examples of chemical reaction networks whose ordinary
differential equation scaling limit are almost identical and in all cases
stable. Nevertheless, the Markov jump processes associated to these reaction
networks display the full range of behaviors: one is stable (positive
recurrent), one is unstable (transient) and one is marginally stable (null
recurrent). We study these differences and characterize the invariant measures
by Lyapunov function techniques. In particular, we design a natural set of such
functions which scale homogeneously to infinity, taking advantage of the same
scaling behavior of the reaction rates.
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Journal articlePermalink
https://hdl.handle.net/10161/18129Collections
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Show full item recordScholars@Duke
Andrea Agazzi
Assistant Research Professor of Mathematics
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Jonathan Christopher Mattingly
Kimberly J. Jenkins Distinguished University Professor of New Technologies
Jonathan Christopher Mattingly grew up in Charlotte, NC where he attended Irwin Ave
elementary and Charlotte Country Day. He graduated from the NC School of Science
and Mathematics and received a BS is Applied Mathematics with a concentration in physics
from Yale University. After two years abroad with a year spent at ENS Lyon studying
nonlinear and statistical physics on a Rotary Fellowship, he returned to the US to
attend Princeton University where he obtained a PhD in Applied and
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