Theorem. Concavity and covariance of squared edge differences [fdip-005T]

On the open set \(\mathcal U_m\) of Definition [fdip-005R], \[\frac {\partial ^2\mathcal W}{\partial w_e\partial w_f} =-\frac 12(d_e^TGd_f)^2.\] The induced action is concave, including on the nonnegative weight orthant. For the corresponding centered Gaussian field, \[\operatorname {Cov}((d_e^T\phi )^2,(d_f^T\phi )^2) =2(d_e^TGd_f)^2,\] so the Hessian is minus one quarter of this covariance matrix.

[friedli2017statistical, Exercise 8.3, p. 385] states Wick's formula. The last calculation is its four-factor case and agrees with the Gaussian contraction rule. Concavity need not be strict in the weights: loops or dependent matrices \(d_ed_e^T\) can give zero second derivatives in nonzero directions.