Download PDF by Dominique Bakry, Ivan Gentil, Michel Ledoux (auth.): Analysis and Geometry of Markov Diffusion Operators

By Dominique Bakry, Ivan Gentil, Michel Ledoux (auth.)

ISBN-10: 3319002260

ISBN-13: 9783319002262

ISBN-10: 3319002279

ISBN-13: 9783319002279

The current quantity is an in depth monograph at the analytic and geometric points of Markov diffusion operators. It makes a speciality of the geometric curvature houses of the underlying constitution that allows you to research convergence to equilibrium, spectral bounds, sensible inequalities corresponding to Poincaré, Sobolev or logarithmic Sobolev inequalities, and numerous bounds on options of evolution equations. whilst, it covers a wide classification of evolution and partial differential equations.

The booklet is meant to function an creation to the topic and to be available for starting and complex scientists and non-specialists. concurrently, it covers quite a lot of effects and methods from the early advancements within the mid-eighties to the most recent achievements. As such, scholars and researchers drawn to the trendy elements of Markov diffusion operators and semigroups and their connections to analytic sensible inequalities, probabilistic convergence to equilibrium and geometric curvature will locate it in particular important. chosen chapters is also used for complex classes at the topic.

Show description

Read Online or Download Analysis and Geometry of Markov Diffusion Operators PDF

Best differential geometry books

Download PDF by Stephen Bruce Sontz: Principal Bundles: The Quantum Case (Universitext)

This introductory textual content is the 1st booklet approximately quantum crucial bundles and their quantum connections that are common generalizations to non-commutative geometry of important bundles and their connections in differential geometry. To make for a extra self-contained publication there's additionally a lot historical past fabric on Hopf algebras, (covariant) differential calculi, braid teams and appropriate conjugation operations.

Extra resources for Analysis and Geometry of Markov Diffusion Operators

Example text

We therefore exclude the possibility that L(x, x) = 0 for any x (such a point would be a trap point, meaning that when the process arrives at this point, it stays there forever). Look first at the discrete time Markov chain (Xk )k∈N with matrix K as Markov kernel, that is the sequence of random variables with X0 = x such that, for all k ∈ N and (x, y) ∈ E × E, P Xk+1 = y | Xk = x = K(x, y). This process is known as the underlying Markov chain of the process X. Then the associated Markov process X may described in the following terms.

In this setting, the Hille-Yosida theory (cf. Sect. 1, p. 473) indicates that there is a dense linear subspace of B, called the domain D of the semigroup (Pt )t≥0 , on which the derivative at t = 0 of Pt exists in B. The operator that maps f ∈ D to this derivative Lf ∈ B of Pt f at t = 0 is a linear (usually unbounded) operator, called the infinitesimal generator of the semigroup (Pt )t≥0 , denoted L. The domain D is also called the domain of L, denoted D(L), and depends on the underlying Banach space B.

2. In particular, they act on function spaces, satisfy the fundamental stability property of preserving the unit function, and admit an invariant measure. These properties may be translated (equivalently) on the generator L of the semigroup P. If the constant 1 function is in L2 (μ), then it is in the domain D(L) and L(1) = 0. This is the case when μ is finite. When the measure μ is infinite, 1 cannot be in the domain, and it is not enough in general to know that L(1) = 0 in order to conclude that conversely Pt (1) = 1 for every t ≥ 0.

Download PDF sample

Analysis and Geometry of Markov Diffusion Operators by Dominique Bakry, Ivan Gentil, Michel Ledoux (auth.)

by Richard

Rated 4.25 of 5 – based on 43 votes