White Paper: Quantitative Linear Algebra

Posted on 8/21/18 in Reports and White Papers

The following white paper was written by the organizers of the IPAM long program on Quantitative Linear Algebra, held in the spring of 2018, with contributions from many of the program’s participants.

The purpose of the program was to bring together topics from a number of important directions, including discrepancy theory, spectral graph theory, random matrices, geometric group theory, ergodic theory, von Neumann algebras, as well as specific research directions such as the Kadison-Singer problem, the Connes embedding conjecture and the Grothendieck inequality.

A very important aspect of the program is its aim to deepen the links between research communities working on some infinite-dimensional analysis problems that occur in geometric group theory, ergodic theory, von Neumann algebras; and some quantitative finite-dimensional ones that occur in spectral graph theory, random matrices, combinatorial optimization, and the Kadison-Singer problem.

Read the attached white paper for a description of the outcomes of the program.