Sheaves on Graphs and Their Homological Invariants

Mathematics – Combinatorics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

80 pages. This has been withdrawn, since it has been combined with article 1105.0129 to make one article (whose first chapter

Scientific paper

We introduce a notion of a sheaf of vector spaces on a graph, and develop the foundations of homology theories for such sheaves. One sheaf invariant, its "maximum excess," has a number of remarkable properties. It has a simple definition, with no reference to homology theory, that resembles graph expansion. Yet it is a "limit" of Betti numbers, and hence has a short/long exact sequence theory and resembles the $L^2$ Betti numbers of Atiyah. Also, the maximum excess is defined via a supermodular function, which gives the maximum excess much stronger properties than one has of a typical Betti number. The maximum excess gives a simple interpretation of an important graph invariant, which will be used to study the Hanna Neumann Conjecture in a future paper. Our sheaf theory can be viewed as a vast generalization of algebraic graph theory: each sheaf has invariants associated to it---such as Betti numbers and Laplacian matrices---that generalize those in classical graph theory.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Sheaves on Graphs and Their Homological Invariants does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Sheaves on Graphs and Their Homological Invariants, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Sheaves on Graphs and Their Homological Invariants will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-165227

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.