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A real matrix product giving pairwise dot products of columns, for $T^{\top }T$, or rows, for $T{T}^{\top }$. It is a positive semidefinite matrix. The kernel of a Gram product is determined by the corresponding factor, which makes these products useful for converting a zero quadratic form into an exact null space condition.

Fix one common eigenvector $v\ne 0$, and write $A{A}^{\top }v=\lambda v$ and $B{B}^{\top }v=\mu v$. By (d),so $\lambda \mu v=0$ and at least one of the two eigenvalues is zero.

To exclude both being zero, use the kernel of a Gram product identity:If both products annihilate $v$, then $A^{\top }v=B^{\top }v=0$. By (b), $v\in \mathrm{im}L$, and by (e), this is $\mathrm{im}B$. On the other hand, $B^{\top }v=0$ makes $v$ orthogonal to every vector in $\mathrm{im}B$. In particular $v$ is orthogonal to itself, so $\Vert v{\Vert }^2=0$ and $v=0$, a contradiction.

Therefore each specified common eigenvector belongs to exactly one of $\ker (A{A}^{\top })$ and $\ker (B{B}^{\top })$. Both eigenvalues are nonnegative by the displayed squared-norm identities, so the other eigenvalue is strictly positive. This is the spectral mechanism behind orthogonal null-space completion of a square matrix.