Suppose we have a symmetric PD or PSD matrix M which induces an inner product $\langle \cdot, \cdot \rangle\_M$. If we have that $\langle x, y \rangle > 0$ for two unit vectors $x$, $y$, are there any sufficient conditions on $x, y$, and/or $M$ that ensure that $\langle{x}, {y}\rangle\_M > 0$ (other than the obvious $x=y$ or $M = I$)?.



Which inner products preserve positive correlation?
Since $M$ is PSD, it can be decomposed as $M=A^T A$, where $A$ is another matrix; see
<https://math.stackexchange.com/questions/1801403/decomposition-of-a-positive-semidefinite-matrix>


Now $\langle x,y\rangle=x^T M y=x^T A^T Ay=\langle Ax,Ay\rangle$ and so your question is equivalent to: Which matrices $A$ preserve positive correlations between vectors? It is known that the matrices that preserve orthogonality are precisely those that are scalar multiples of orthogonal transformations:
<https://math.stackexchange.com/questions/2355551/linear-transformations-that-preserve-orthogonality>


Certainly if a matrix does not preserve orthogonality, it does not preserve positive correlations (it can fix $x$ and map $y$ to a vector orthogonal to $x$). Conversely, scalar multiples of orthogonal matrices *do* preserve positive correlations -- more generally, they preserve dot products:
<https://math.stackexchange.com/questions/2161729/how-orthogonal-matrices-preserve-dot-product-and-volume-proof>


We conclude that $A$ must be a scalar multiple of an orthogonal matrix, and hence $M$ must be a positive multiple of the identity $I$.


