(If we allow loops and multiple edges with the corresponding entry of the
adjacency matrix being the number of such loops or edges, then any
non-negative matrix may be interpreted as an adjacency matrix. Then, the
product $A_{G}A_{H}$ can be interpreted as a graph. However, since the
product of symmetric matrices is usually not symmetric, the product of
adjacency matrices of undirected graphs will need to be interpreted as a
directed graph. Since an undirected graph can be interpreted as a directed
graph with all edges in both directions, directed graphs are assumed here.)
The interpretation of powers of an adjacency matrix in terms of walks can be
generalized to consider the significance of the product $A_{G}A_{H}.$ We
take one step on $G$ and then one step on $H$. Then $K$ has an edge from the
initial vertex in $G$ of this "2-walk" to the final vertex in $H$, i.e., the
directed edges of $K$ are $E(K)=\{ij~|~ik\in E(G)\wedge kj\in E(H)\}$.
In general, this won't be connected since it won't contain a path to/from
the intermediate vertices $k$ unless they also end/begin another 2-walk.
There will be no edges away from the neighborhood of common vertices of $G$
and $H$.
It is possible to have $K$
strongly-connected, e.g., if $G$ and $H$ are complete graphs, but weakly connected
(underlying undirected graph is connected) is more likely and is assumed
here.
It is possible to have $K$ weakly connected even if neither $G$ or$\ H$ are
connected:
The criterion for the graph of an adjacency matrix to be strongly-connected
is (Ref. 1) $(I+A)^{|V|-1}>0$ (all entries positive). The matrix for the
underlying graph is the symmetric version, and so the test for weakly
connected is $(I+A+A^{T})^{|V|-1}>0$. (These tests depend only on the
locations of the zero entries and work for any non-negative matrices.)
1: R.A. Horn, C.R. Johnson, Matrix Analysis, Thm. 6.2.4, p. 362, Cambridge
University Press, 1985.