Implementations and the independent set polynomial below the Shearer threshold

TL;DR

This paper proves that for values below the Shearer threshold, it is possible to densely implement real numbers using the independent set polynomial, which has implications for the computational hardness of approximation.

Contribution

It demonstrates that below the Shearer threshold, implementations can densely approximate any real value, establishing tight bounds for intractability results.

Findings

Implementation sets are dense over the reals for λ < -λ*

Implementation sets are not dense for λ > λ*

Used to prove #P-hardness of approximation below the threshold

Abstract

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).