101.718 VO (2std Vorlesung, Sommersemester 2018)
Theory of distributions

First meeting

Aim of the lecture

The theory of distributions is a generalization of classical analysis, which makes it possible to systematically deal with difficulties that have been overcome beforehand by ad hoc constructions, or by heuristic arguments. The theory was created by Laurent Schwartz in the 20th century and gives a unified broader framework in which one can reformulate and develop classical problems in engineering, physics, and mathematics. Distributions have many very different properties. They are a generalization of the notion of function, and their purpose is to solve problems of differentiation. Indeed, every distribution is differentiable and even infinitely differentiable, and the derivatives are also distributions. If a continuous function is not differentiable, then, considered as a distribution, it always admits a derivative, but the derivative is a distribution which is not necessarily a function. This is why distributions are widely used in the analysis of partial differential equations. The aim of the course is to make the interested student acquainted with the foundations of the theory of distributions as introduced by Schwartz in the elegant framework of topological vector spaces. Applications in partial differential equations and harmonic analysis will be emphasized whenever possible. Last but not least, the theory of distributions is a beautiful piece of mathematics, and the course is surely a good opportunity for all those persons who are interested in broadening their foundational mathematical baggage.

Contents of the lecture

Topological vector spaces. Locally convex Spaces. Fréchet spaces. Fundamental function spaces. Space of distributions. Tensor product of distributions. Convolutions of distributions.


Schwartz, Laurent. Théorie des distributions. Paris: Hermann, 1997.

Treves, François. Topological vector spaces, distributions and kernels. Elsevier, 2016.

Horváth, John. Topological vector spaces and distributions. Addison-Wesley, 2012.

Previous knowledge

The lecture will build on the prerequisites of Analysis 3 (Lebesgue integration theory). Some knowledge of basic functional analysis and Sobolev spaces is of advantage.

Examination modalities

Oral examination. If you wish to do the examination, please email us to arrange an appointment.


116.03.2018Motivations from physics and PDEs. Diract delta is a singular Radon measure. Properties of balanced sets, convex sets, absorbing sets.Giovanni Di Fratta
Easter holidays (Osterferien)
213.04.2018Special sets in Vector Spaces. Properties of Seminorms and gauges. Generalized sequences (Nets) and Filters in TopologyGiovanni Di Fratta
320.04.2018Topological Vector Spaces IGiovanni Di Fratta
427.04.2018Topological Vector Spaces IIGiovanni Di Fratta
504.05.2018Locally Convex Spaces, Frechet SpacesGiovanni Di Fratta
11.05.2018Rectors Day/dies academicus (no classes)
618.05.2018Locally Convex Spaces, Frechet SpacesGiovanni Di Fratta
725.05.2018Inductive topologies. LF spaces.Giovanni Di Fratta
801.06.2018Dieudonné-Schwartz theorem. Fundamental function spacesGiovanni Di Fratta
908.06.2018Duality. Fundamental function spacesGiovanni Di Fratta
1015.06.2018Duality. Spaces of DistributionsGiovanni Di Fratta
1122.06.2018Operations on DistributionsGiovanni Di Fratta


The lecture notes will be assembled on-the-fly and will be published here.

01.03.2018Course announcement[pdf]
16.03.2018Lecture 1[pdf]
13.04.2018Lecture 2[pdf]
20.04.2018Lecture 3[pdf]
27.04.2018Lecture 4[pdf]
04.05.2018Lecture 5[pdf]
18.05.2018Lecture 6[pdf]
25.05.2018Lecture 7[pdf]
01.06.2018Lecture 8[pdf]
08.06.2018Lecture 9[pdf]
15.06.2018Lecture 10[pdf]
22.06.2018Lecture 11[pdf]