If is an matrix, the product is defined in ordinary matrix multiplication only when . Hence the defining equation of an idempotent matrix already requires equal row and column counts:Equivalently, an idempotent linear map is an endomorphism, so the same vector space is both its domain and codomain.
If the idempotent matrix is invertible, multiply on the left by its matrix inverse:Thus a nonidentity idempotent matrix must be singular; the identity itself is both invertible and idempotent.
Using ,Thus is another idempotent matrix. In fact : as linear projections, they select the complementary summands in the decomposition .
Take determinants of the idempotence equation and use multiplicativity of the determinant:Thus satisfies , provingIf the determinant is one, is invertible and solution gives . Every other idempotent matrix has zero determinant.
For real orthonormal column vectors, and . Expand using associativity of matrix multiplication:HenceMore precisely, it is the orthogonal projection onto the span of : it fixes both vectors and annihilates every vector orthogonal to both.
The transpose convention presumes real vectors, or the explicitly stated bilinear identities above. For complex vectors orthonormal in the Hermitian inner product, the correct orthogonal projection is . The printed transpose formula need not work in that setting: and are Hermitian-orthonormal, but has square , which is different from itself.
Induction from gives for every integer . Separate the zeroth term of the matrix exponential series:Therefore the exponential of an idempotent linear map isThe last form shows its action directly: it multiplies the image of a linear map of by and fixes its kernel of a linear map. No Hermiticity assumption on the idempotent matrix is needed.
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