Bessel Processes, Schramm–Loewner Evolution, and the Dyson ModelThe purpose of this book is to introduce two recent topics in mathematical physics and probability theory: the Schramm–Loewner evolution (SLE) and interacting particle systems related to random matrix theory. A typical example of the latter systems is Dyson's Brownian motion (BM) model. The SLE and Dyson's BM model may be considered as "children" of the Bessel process with parameter D, BES(D), and the SLE and Dyson's BM model as "grandchildren" of BM. In Chap. 1 the parenthood of BM in diffusion processes is clarified and BES(D) is defined for any D ≥ 1. Dependence of the BES(D) path on its initial value is represented by the Bessel flow. In Chap. 2 SLE is introduced as a complexification of BES(D). Rich mathematics and physics involved in SLE are due to the nontrivial dependence of the Bessel flow on D. From a result for the Bessel flow, Cardy's formula in Carleson's form is derived for SLE. In Chap. 3 Dyson's BM model with parameter β is introduced as a multivariate extension of BES(D) with the relation D = β + 1. The book concentrates on the case where β = 2 and calls this case simply the Dyson model.The Dyson model inherits the two aspects of BES(3); hence it has very strong solvability. That is, the process is proved to be determinantal in the sense that all spatio-temporal correlation functions are given by determinants, and all of them are controlled by a single function called the correlation kernel. From the determinantal structure of the Dyson model, the Tracy–Widom distribution is derived. |
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Bessel Processes, Schramm–Loewner Evolution, and the Dyson Model Makoto Katori No preview available - 2016 |
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absorbing Airy Aspect Assume Bessel process bounded Brownian motion called Chap complex condition configuration consider constant continuous correlation functions correlation kernel curve defined definition denoted Derive determinant determinantal process differential equation diffusion process dimension distribution drift Dyson model equality event Exercise expectation expression extension flow formula function given gives Hermite implies independent infinite initial integral introduced Katori Lemma martingale Math Mathematical matrix mean measurable noncolliding Note obtained one-dimensional origin particles path Phase Phys polynomials positive Proof Proposition prove random Relat respect satisfies scaling limit Sect Show ſº solution space starting stochastic Stochastic Differential Equations term Theorem theory transformation transition probability density write written zeros