  We prove that if $q_1, \ldots, q_m: {\Bbb R}^n \longrightarrow {\Bbb R}$ are
quadratic forms in variables $x_1, \ldots, x_n$ such that each $q_k$ depends on
at most $r$ variables and each $q_k$ has common variables with at most $r$
other forms, then the average value of the product $\left(1+ q_1\right) \cdots
\left(1+q_m\right)$ with respect to the standard Gaussian measure in ${\Bbb
R}^n$ can be approximated within relative error $\epsilon >0$ in
quasi-polynomial $n^{O(1)} m^{O(\ln m -\ln \epsilon)}$ time, provided $|q_k(x)|
\leq \gamma \|x\|^2 /r$ for some absolute constant $\gamma > 0$ and $k=1,
\ldots, m$. When $q_k$ are interpreted as pairwise squared distances for
configurations of points in Euclidean space, the average can be interpreted as
the partition function of systems of particles with mollified logarithmic
potentials. We sketch a possible application to testing the feasibility of
systems of real quadratic equations.
