Download this article
Download this article For screen
For printing
Recent Issues
Volume 18
Volume 16
Volume 15
Volume 14
Volume 13
Volume 12
Volume 11
Volume 10
Volume 9
Volume 8
Volume 6+7
Volume 5
Volume 4
Volume 3
Volume 2
Volume 1
The Journal
About the journal
Ethics and policies
Peer-review process
 
Submission guidelines
Submission form
Editorial board
 
Subscriptions
 
ISSN (electronic): 2640-7345
ISSN (print): 2640-7337
Author Index
To Appear
 
Other MSP Journals
This article is available for purchase or by subscription. See below.
Random Möbius–Kantor group cobordisms

Sylvain Barré and Mikaël Pichot

Vol. 19 (2022), No. 4, 137–152
Abstract

We introduce a new model of random groups, in which the random group is CAT (0) (but not hyperbolic). The definition relies on a surgery type construction for Möbius–Kantor complexes; it depends on the existence of a sufficiently large semigroup of group cobordisms, which can be composed in a random way to define a group. By construction, the local geometry in this model is preassigned. We aim to study the asymptotic geometry of the random group, in particular to prove that it is not hyperbolic in a strong sense.

PDF Access Denied

We have not been able to recognize your IP address 18.222.115.179 as that of a subscriber to this journal.
Online access to the content of recent issues is by subscription, or purchase of single articles.

Please contact your institution's librarian suggesting a subscription, for example by using our journal-recom­mendation form. Or, visit our subscription page for instructions on purchasing a subscription.

You may also contact us at contact@msp.org
or by using our contact form.

Or, you may purchase this single article for USD 40.00:

Keywords
nonpositive curvature, discrete groups, random groups
Mathematical Subject Classification
Primary: 20F65
Milestones
Received: 24 July 2021
Revised: 23 April 2022
Accepted: 25 August 2022
Published: 1 December 2022
Authors
Sylvain Barré
UMR 6205, Laboratoire de mathématiques de Bretagne Atlantique (LMBA)
Université Bretagne-Sud
Vannes
France
Mikaël Pichot
Department of Mathematics and Statistics
McGill University
Montreal, QC
Canada