A graph polynomial for independent sets of bipartite graphs

Computer Science – Discrete Mathematics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We introduce a new graph polynomial that encodes interesting properties of graphs, for example, the number of matchings and the number of perfect matchings. Most importantly, for bipartite graphs the polynomial encodes the number of independent sets (#BIS). We analyze the complexity of exact evaluation of the polynomial at rational points and show that for most points exact evaluation is #P-hard (assuming the generalized Riemann hypothesis) and for the rest of the points exact evaluation is trivial. We conjecture that a natural Markov chain can be used to approximately evaluate the polynomial for a range of parameters. The conjecture, if true, would imply an approximate counting algorithm for #BIS, a problem shown, by [Dyer et al. 2004], to be complete (with respect to, so called, AP-reductions) for a rich logically defined sub-class of #P. We give a mild support for our conjecture by proving that the Markov chain is rapidly mixing on trees. As a by-product we show that the "single bond flip" Markov chain for the random cluster model is rapidly mixing on constant tree-width graphs.

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

A graph polynomial for independent sets of bipartite graphs 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 A graph polynomial for independent sets of bipartite graphs, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A graph polynomial for independent sets of bipartite graphs will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-622572

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