A finite-dimensional self-adjoint operator has an orthonormal eigenbasis and real eigenvalues. The point is to make the formal expression readable enough to audit line by line.
Definitions first
An inner product \(\langle x,y\rangle\) converts algebraic decompositions into orthogonal ones. Self-adjoint maps satisfy \(T=T^\ast\) and have real spectral data.
The formulas should not be merged too early. The datum \(\mathsf D\), the conclusion \(\mathsf C\), and the bridge \(\Longrightarrow\) have three different logical jobs.
A small case in full
This is the algebraic core of the note. Once this line is correct, the surrounding interpretation has something solid to refer to.
The reusable statement
The aligned summary deliberately puts the datum and conclusion on different rows. Mathematically, this is the distinction between specifying an object and proving a property of it.
A nearby false statement
Orthogonal diagonalization requires self-adjointness over the real or complex inner-product setting. A general diagonalizable matrix need not have orthogonal eigenvectors.
The important habit is to remember what was fixed before the calculation began and what was proved only afterward. The final display preserves that order.