Definition. Massive graph Green functions [fdip-000A]
AGENTDRAFTED
Let \(V\) be a finite vertex set, with positive edge weights,
and let \(L\) be its weighted graph Laplacian.
For \(m>0\), define the massive precision and its
Green operator by
\[Q_m=L+m^2I,\qquad G_m=Q_m^{-1}.\]
The inverse exists even when the graph is disconnected. Indeed, the
energy identity gives, for \(f\ne 0\),
\[\begin {aligned}
\langle f,Q_mf\rangle _V
&=\sum _e w(e)(Df)(e)^2\\
&\quad +m^2\sum _v f(v)^2>0.
\end {aligned}\]
Thus \(Q_mf=0\) implies \(f=0\). Finite dimension and rank-nullity
make this injective endomorphism surjective, so it is an isomorphism.
The inverse-response lemma now gives a self-adjoint
inverse and the unique solution \(f=G_mj\) to \(Q_mf=j\).
The endomorphism \(Q_m\) is a
positive precision parameter; its
counting array realizes it as a positive symmetric matrix. For \(j\ne 0\),
write \(x=G_mj\ne 0\); then
\(\langle j,G_mj\rangle _V=\langle Q_mx,x\rangle _V>0\).
On an empty vertex set the same map argument gives the unique
isomorphism of zero modules; there are no point-source columns.
By the real spectral theorem, choose an orthonormal
eigenbasis \(u_a\) of the self-adjoint operator \(L\), with eigenvalues \(\lambda _a\ge 0\).
The energy identity proves this last inequality by evaluation on each
unit eigenvector. Put \(q_a=\lambda _a+m^2>0\). Then
\[\begin {aligned}
Q_m&=\sum _a q_a u_au_a^T,\\
G_m&=\sum _a q_a^{-1}u_au_a^T.
\end {aligned}\]
Since \(u_a^Tu_b=\delta _{ab}\) and \(\sum _a u_au_a^T=I\), multiplication
gives \(Q_mG_m=G_mQ_m=I\). Also \(G_m^T=G_m\), and
\(f^TG_mf=\sum _a q_a^{-1}(u_a^Tf)^2>0\) for nonzero \(f\).
The Green kernel is defined from the inverse map by
\(G_m(v,w)=(G_m\delta _w)(v)\). These are its matrix entries in the
counting coordinate basis. Its column at \(w\)
is the unique field solving
\[Q_mG_m(\cdot ,w)=\delta _w,\]
where \(\delta _w(v)\) is one at \(v=w\) and zero elsewhere.
For a source field \(j\), the unique solution of \(Q_mf=j\) is
\(f(v)=\sum _wG_m(v,w)j(w)\). No vertex-volume factor occurs because
the vertex pairing and basis are counting.
This convention has to be matched when comparing lattice Green
functions. Wingate's lattice action uses a positive operator built from
minus the backward-forward difference and a mass term
[wingate2025lattice, Section 4, Equations (4.2)-(4.5), p. 3].
For unit spacing, that difference term has the sign of our \(L\).
In [friedli2017statistical, Theorem 8.26, p. 399], the massive
lattice precision is
\[Q=-\frac {1}{2d}\Delta +m^2I.\]
Here \(\Delta f(x)=\sum _{y\sim x}(f(y)-f(x))\). The factor \(1/(2d)\)
and the lattice boundary conditions belong to that normalization.
Identifying their covariance with an inverse requires that precision,
not an unscaled adjacency Laplacian.
Mathlib's Matrix.PosDef.isUnit proves invertibility of a
positive definite matrix, and Matrix.PosDef.inv proves
positivity of its inverse. These apply to the matrix step after the
graph-energy calculation supplies positivity. The kernel convention and
its graph interpretation are specified here.