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＜E-Book＞
Stochastic Neutron Transport : And Non-Local Branching Markov Processes / by Emma Horton, Andreas E. Kyprianou
(Probability and Its Applications. ISSN:22970398)

Edition	1st ed. 2023.
Publisher	Cham : Springer International Publishing : Imprint: Birkhäuser
Year	2023
Language	English
Size	XV, 272 p. 10 illus., 4 illus. in color : online resource
Authors	*Horton, Emma author Kyprianou, Andreas E author SpringerLink (Online service)
Subjects	LCSH:Probabilities LCSH:Stochastic processes LCSH:Markov processes FREE:Applied Probability FREE:Probability Theory FREE:Stochastic Processes FREE:Markov Process
Notes	Part I Neutron Transport Theory -- Classical Neutron Transport Theory -- Some background Markov process theory -- Stochastic Representation of the Neutron Transport Equation -- Many-to-one, Perron-Frobenius and criticality -- Pal-Bell equation and moment growth -- Martingales and path decompositions -- Discrete evolution -- Part II General branching Markov processes -- A general family of branching Markov processes -- Moments -- Survival at criticality -- Spines and skeletons -- Martingale convergence and laws of large numbers This monograph highlights the connection between the theory of neutron transport and the theory of non-local branching processes. By detailing this frequently overlooked relationship, the authors provide readers an entry point into several active areas, particularly applications related to general radiation transport. Cutting-edge research published in recent years is collected here for convenient reference. Organized into two parts, the first offers a modern perspective on the relationship between the neutron branching process (NBP) and the neutron transport equation (NTE), as well as some of the core results concerning the growth and spread of mass of the NBP. The second part generalizes some of the theory put forward in the first, offering proofs in a broader context in order to show why NBPs are as malleable as they appear to be. Stochastic Neutron Transport will be a valuable resource for probabilists, and may also be of interest to numerical analysts and engineers in the field of nuclear research HTTP:URL=https://doi.org/10.1007/978-3-031-39546-8

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