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In an orthonormal basis, self-adjoint means conjugate-transpose symmetry and normal means commuting with the conjugate transpose
Statement
Let be a finite-dimensional real or complex inner product space, let be linear, and let be an orthonormal basis of . Write
Then:
- is self-adjoint if and only if .
- is normal if and only if .
Over , is just .
Facts & Assumptions
Given: A finite-dimensional real or complex inner product space , a linear map , an orthonormal basis , and the matrix .
In orthonormal bases, the matrix of the adjoint is the conjugate transpose (In orthonormal bases, the matrix of the adjoint is the conjugate transpose of the matrix).
Proof
By the definition of self-adjointness in Self-adjoint and normal endomorphisms of a finite-dimensional real or complex inner product space, is self-adjoint exactly when . By [L1], this is equivalent to .
By the definition of normality in Self-adjoint and normal endomorphisms of a finite-dimensional real or complex inner product space, is normal exactly when ; using [L2] and then [L1], this is equivalent to , hence to .
Depends on
Used by
- Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis Corollary
- A complex symmetric matrix can be nonzero, square to zero, and fail to be normal Example
- The real quarter-turn is normal and appears as a single 2x2 block in the real normal classification Example
- A normal upper-triangular matrix is diagonal Lemma
- A real normal endomorphism is orthogonally block-diagonalisable with 1x1 real blocks and 2x2 rotation-scaling blocks Theorem
- Complex spectral theorem: a normal endomorphism of a finite-dimensional complex inner product space has an orthonormal eigenbasis, and conversely Theorem
Dependency tree · two levels
13 results within two dependency steps of this one, each drawn at its shortest distance from it. An arrow runs from a result to what uses it, so the chart reads left to right and ends at this result, which carries a heavier outline. Every node is a link to that result. Click elsewhere on the chart to enlarge it.
Sources
- Sheldon Axler, Linear Algebra Done Right, fourth edition (standard reference, not scraped)