Inner Product Spaces & Adjoints

adjoint identities

The adjoint is not just a definition; it obeys a tidy algebra worth memorizing. It is conjugate-linear in scalars, (c T)^* = conj(c) T^*; additive, (S + T)^* = S^* + T^*; order-reversing on products, (S T)^* = T^* S^*; involutive, (T^*)^* = T; and it sends identity to identity. These mirror the transpose rules with conjugates sprinkled in.

The order reversal (S T)^* = T^* S^* is the one people slip on. It is the same flip as for the inverse or transpose: apply S then T, and the adjoint unwinds them in reverse. A quick check using <S T u, v> = <u, (ST)^* v> confirms the swap.

The deepest identities are the four fundamental subspace relations: ker T^* = (im T)-perp and im T^* = (ker T)-perp, with the two companions ker T = (im T^*)-perp and im T = (ker T^*)-perp. They say the adjoint exactly trades kernels for image-complements.

These relations are the orthogonal upgrade of Vol I's four fundamental subspaces. They make the rank-nullity bookkeeping geometric: the domain splits as ker T (+) im T^*, the codomain as im T (+) ker T^*, and T is a clean isomorphism between the two non-kernel pieces. Least squares, the SVD, and the pseudoinverse all rest on exactly this.

(S T)^* = T^* S^*, (T^*)^* = T, ker T^* = (im T)-perp, im T^* = (ker T)-perp

The algebra of adjoints plus the fundamental-subspace duality; together they make rank-nullity into an orthogonal decomposition.

Memory hook: ker T^* = (im T)-perp says the adjoint's null directions are exactly those the original operator never reaches. This single relation is why least squares lands the residual orthogonal to the column space.

Also called
properties of the adjointfundamental subspace relations