A set of nonzero vectors $\{p_0,p_1,\ldots,p_{n-1}\}$ is said to be conjugate with respect to a symmetric positive definite matrix $A$ if $$ p_i^{\mathrm T}Ap_j=0 $$ for all $i\ne j$. Such vectors are used in the conjugate gradient method. It follows that conjugate vectors are also linearly independent. An example of conjugate vectors are the eigenvectors of the matrix $A$.
Are the conjugate vectors unique up to a scalar multiple? In other words, if there are two sets of conjugate vectors with respect to the same symmetric positive definite matrix $A$, are the vectors going to be the same up to a scalar multiple?
I would guess that that they are unique up to a scalar multiple, but I am not sure.
Any help is much appreciated!
Take $A=I_n$. Then any orthogonal basis is a set of conjugate vectors.