  The independent set polynomial is important in many areas. For every integer
$\Delta\geq 2$, the Shearer threshold is the value
$\lambda^*(\Delta)=(\Delta-1)^{\Delta-1}/\Delta^{\Delta}$ . It is known that
for $\lambda < - \lambda^*(\Delta)$, there are graphs~$G$ with maximum
degree~$\Delta$ whose independent set polynomial, evaluated at~$\lambda$, is at
most~$0$. Also, there are no such graphs for any $\lambda >
-\lambda^*(\Delta)$. This paper is motivated by the computational problem of
approximating the independent set polynomial when $\lambda < -
\lambda^*(\Delta)$. The key issue in complexity bounds for this problem is
"implementation". Informally, an implementation of a real number $\lambda'$ is
a graph whose hard-core partition function, evaluated at~$\lambda$, simulates a
vertex-weight of~$\lambda'$ in the sense that $\lambda'$ is the ratio between
the contribution to the partition function from independent sets containing a
certain vertex and the contribution from independent sets that do not contain
that vertex. Implementations are the cornerstone of intractability results for
the problem of approximately evaluating the independent set polynomial. Our
main result is that, for any $\lambda < - \lambda^*(\Delta)$, it is possible to
implement a set of values that is dense over the reals. The result is tight in
the sense that it is not possible to implement a set of values that is dense
over the reals for any $\lambda> \lambda^*(\Delta)$. Our result has already
been used in a paper with \bezakova{} (STOC 2018) to show that it is \#P-hard
to approximate the evaluation of the independent set polynomial on graphs of
degree at most~$\Delta$ at any value $\lambda<-\lambda^*(\Delta)$. In the
appendix, we give an additional incomparable inapproximability result
(strengthening the inapproximability bound to an exponential factor, but
weakening the hardness to NP-hardness).

Computational Complexity;Discrete Mathematics