Professor Joseph M. Landsberg
Joseph M. Landsberg works on questions at the interface of algebraic geometry, differential geometry and representation theory. His current research is focused on geometric problems originating in complexity theory. Landsberg obtained his PhD in 1990 from Duke University under the direction of Robert Bryant. He was Maître de Conférences at Paul Sabatier University from 1996 to 2000, and he is Professor at Texas A&M University since 2004.
He has directed twelve PhD theses. He is the author of over eighty research articles and several textbooks, including "Geometry and complexity theory" (Cambridge 2017) and "Tensors: Geometry and Applications" (AMS 2012).
Colloquium CIMI
13th May 2022 at 02:00 pm, salle du conseil (bâtiment administratif de l'UPS)
Géométrie algébrique et complexité.
Résumé: L'informatique a motivé des nouvelles questions de géométrie algébrique et de théorie des représentations. Dans cet exposé, je discuterai du problème de la complexité de la multiplication des matrices. Les informaticiens ont conjecturé que pour n très grand, il est presque aussi facile de multiplier des matrices nxn que de les ajouter ! Je présenterai l'histoire du problème et ses développements récents.
Lectures on Introduction to classical and quantum information theory
As part of his CIMI Excellence Chair, J.M. Landsberg will give a mini-course entitled "Introduction to classical and quantum information theory". This 18-hour course is intended to be widely accessible. It will be held in the Johnson room (1st floor, building 1R3) on Tuesdays and Thursdays from 15:30 to 17:00. The first session will take place on Tuesday 29 March and will give a general presentation of the course content, which is summarised below.
This course will cover classical information theory, quantum information theory and uses of representation theory in quantum information theory.
No prior knowledge of anything quantum will be assumed. Notes will be distributed.
In more detail, the topics that will be covered are:
Classical information theory:
Data compression: noiseless channels
Entropy, i.e., uncertainty
Shannon’s noiseless channel theorem
Transmission over noisy channels
Quantum information:
Laws of quantum mechanics and first consequences
Distances in the classical and quantum settings
The quantum noiseless channel theorem
Properties of von Neumann entropy
Conditional von Neumann entropy and strong subadditivity
Entanglement and LOCC
Representation theory and Quantum information:
Basics of Representation theory
Schur-Weyl duality and ε-typical subspaces
The quantum marginal problem
Tripartite States
The lectures notes are available here