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The growth-fragmentation equation describes a system of growing and dividing particles, and arises in models of cell division, protein polymerisation and even telecommunications protocols. Several important questions about the equation concern the asymptotic behaviour of solutions at large times: at what rate do they converge to zero or infinity, and what does the asymptotic profile of the solutions look like? Does the rescaled solution converge to its asymptotic profile at an exponential speed? These questions have traditionally been studied using analytic techniques such as entropy methods or splitting of operators. In this work, we present a probabilistic approach: we use a Feynman–Kac formula to relate the solution of the growth-fragmentation equation to the semigroup of a Markov process, and characterise the rate of decay or growth in terms of this process. We then identify the Malthus exponent and the asymptotic profile in terms of a related Markov process, and give a spectral interpretation in terms of the growth-fragmentation operator and its dual. 相似文献
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Interactions of Pt‐ttpy with G‐Quadruplexes Originating from Promoter Region of the c‐myc Gene Deciphered by NMR and Gel Electrophoresis Analysis
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G. Panina 《Central European Journal of Mathematics》2003,1(2):157-168
All 3-dimensional convex polytopes are known to be rigid. Still their Minkowski differences (virtual polytopes) can be flexible
with any finite freedom degree. We derive some sufficient rigidity conditions for virtual polytopes and present some examples
of flexible ones. For example, Bricard's first and second flexible octahedra can be supplied by the structure of a virtual
polytope. 相似文献
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Peter Imkeller 《Probability Theory and Related Fields》1996,106(1):105-135
Summary. The analytic treatment of problems related to the asymptotic behaviour of random dynamical systems generated by stochastic
differential equations suffers from the presence of non-adapted random invariant measures. Semimartingale theory becomes accessible
if the underlying Wiener filtration is enlarged by the information carried by the orthogonal projectors on the Oseledets spaces
of the (linearized) system.
We study the corresponding problem of preservation of the semimartingale property and the validity of a priori inequalities
between the norms of stochastic integrals in the enlarged filtration and norms of their quadratic variations in case the random
element F enlarging the filtration is real valued and possesses an absolutely continuous law. Applying the tools of Malliavin’s calculus,
we give smoothness conditions on F under which the semimartingale property is preserved and a priori martingale inequalities are valid.
Received: 12 April 1995 / In revised form: 7 March 1996 相似文献
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