Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. EPFL thesis
  4. Representing groups against all odds
 
doctoral thesis

Representing groups against all odds

Gheysens, Maxime  
2017

We investigate how probability tools can be useful to study representations of non-amenable groups. A suitable notion of "probabilistic subgroup" is proposed for locally compact groups, and is valuable to induction of representations. Nonamenable groups admit nonabelian free subgroups in that measure-theoretical sense. Consequences for affine actions and for unitarizability are then drawn. In particular, we obtain a new characterization of amenability via some affine actions on Hilbert spaces. Along the way, various fixed-point properties for groups are studied. We also give a survey of several useful facts about group representations on Banach spaces, continuity of group actions, compactness of convex hulls in locally convex spaces, and measurability pathologies in Banach spaces.

  • Files
  • Details
  • Metrics
Type
doctoral thesis
DOI
10.5075/epfl-thesis-7823
Author(s)
Gheysens, Maxime  
Advisors
Monod, Nicolas  orcid-logo
Jury

Prof. Kathryn Hess Bellwald (présidente) ; Prof. Nicolas Monod (directeur de thèse) ; Prof. Marc Burger, Prof. Alain Valette, Prof. Mikael de la Salle (rapporteurs)

Date Issued

2017

Publisher

EPFL

Publisher place

Lausanne

Public defense year

2017-08-25

Thesis number

7823

Total of pages

208

Subjects

amenability

•

group representation

•

fixed-point property

•

von Neumann problem

•

Dixmier problem

•

induced representation

•

tychomorphism

•

Krein space.

EPFL units
EGG  
Faculty
SB  
School
MATHGEOM  
Doctoral School
EDMA  
Available on Infoscience
August 21, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/139743
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés