In the eigenbasis, let a candidate eigenvector be . The eigenvalue equation is and , so a nonzero vector requires . Choosing normalized phases givesThe two spin eigenstates are orthogonal, as required for distinct eigenvalues of a self-adjoint operator.
Vector normalization Created 2026-10-14 Updated 2026-10-18
Vector normalization converts a nonzero vector in a normed vector space into a unit vector. Absolute homogeneity of a norm givesThe direction is unchanged by multiplying by a positive real scalar. For , and ; for a negative real scalar, . Thus and normalize to the same unit vector, while normalizes to its negative. This decomposition is useful for specifying a direction independently of a force, velocity or displacement magnitude.
In a complex normed vector space, a nonzero complex scalar instead gives . The remaining complex argument is not removed by normalization. For a pure quantum state, vectors differing only by this overall global phase represent the same physical state; vector normalization alone does not identify them.
The zero vector cannot be normalized this way. The construction also applies in a function space: an eigenfunction of a Sturm-Liouville problem can be scaled to unit weighted norm byThe positive weight specifies the weighted inner product. Multiplication by this nonzero constant preserves the eigenvalue equation and its homogeneous boundary conditions.