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
