By Luigi Ambrosio

This booklet is dedicated to a thought of gradient flows in areas which aren't unavoidably endowed with a common linear or differentiable constitution. It comprises elements, the 1st one pertaining to gradient flows in metric areas and the second dedicated to gradient flows within the area of likelihood measures on a separable Hilbert area, endowed with the Kantorovich-Rubinstein-Wasserstein distance.

The components have a few connections, since the distance of chance measures presents a huge version to which the "metric" idea applies, however the publication is conceived in one of these manner that the 2 elements will be learn independently, the 1st one via the reader extra drawn to non-smooth research and research in metric areas, and the second by way of the reader extra oriented in the direction of the functions in partial differential equations, degree thought and probability.

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This publication is dedicated to a concept of gradient flows in areas which aren't inevitably endowed with a typical linear or differentiable constitution. It includes components, the 1st one relating gradient flows in metric areas and the second dedicated to gradient flows within the area of likelihood measures on a separable Hilbert house, endowed with the Kantorovich-Rubinstein-Wasserstein distance.

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**Extra info for Gradient flows in metric spaces and in the space of probability measures**

**Sample text**

In coordinates, is described by giving r functions of n variables Xl, . . , xn y l , . . , yr x x). ,r or simply y F(x). We will frequently use the more dangerous notation y y(x). Let Yo F(xo); the Jacobian matrix (ay'" jax i )(xo) has the following significance. = = 1, = yr v = x(O) x" W = Y (O) = F. v y(t) = F(x(t)) F - image of jR" under F �_____________ y r - I 4------ x l , . . 3 Xo. x(t) such that x (O) Xo x(t) Xo + tv . V (0) = L � (xo) x i (0) ax i=l 11 = L i= l (� a "' ) (xo)v i ax The assignment v � w is, from this expression, independent of the curve and defines a linear transformation, the differential of at F Xo F ..

We shall soon define a "manifold" to be a space that, like the surface of the Earth, can be covered by a family of local coordinate systems. A manifold will turn out to be the most general space in which one can use differential and integral calculus with roughly the same facility as in euclidean space. It should be recalled, though, that calculus in ]R 3 demands special care when curvilinear coordinates are required. The most familiar manifold is N-dimensional euclidean space ]R N , that is, the space of ordered N tuples (x I .

In fact, it is shown in every topology book that any s u bs et X of �n (with the induced topology) is compact if and only if X 1. 2. X is a closed subset of lRn , is a bounded subset, that is, II x II < some number c, for all x E X. Finally we shall need two properties of continuous maps. First The continuous image of a compact space is itself compact. If f : G ---+ M is continuous and if { V; } is an open cover of f (G ) c M, then { f I (Vi ) } is an open cover of G. Since G is compact we can extract a finite open subcover { f- I (Va ) } of G , and then { Va } is a finite subcover of f(G).