ProofComplete

Bounded Linear Operators - Key Proof

We present a detailed proof of the spectral theorem for compact self-adjoint operators, one of the cornerstones of spectral theory.

TheoremSpectral Theorem for Compact Self-Adjoint Operators

Let HH be an infinite-dimensional separable Hilbert space and T:HHT : H \to H a compact self-adjoint operator. Then there exists an orthonormal basis {en}\{e_n\} of HH consisting of eigenvectors of TT, with corresponding eigenvalues {λn}\{\lambda_n\} such that λn0\lambda_n \to 0.

Moreover, for any xHx \in H, T(x)=n=1λnx,enenT(x) = \sum_{n=1}^\infty \lambda_n \langle x, e_n \rangle e_n

Proof

Step 1: Existence of Eigenvalues

Define λ1=supx=1Tx,x\lambda_1 = \sup_{\|x\|=1} |\langle Tx, x \rangle|. Since TT is self-adjoint, Tx,xR\langle Tx, x \rangle \in \mathbb{R} for all xx.

Choose a sequence (xn)(x_n) with xn=1\|x_n\| = 1 and Txn,xnλ1|\langle Tx_n, x_n \rangle| \to \lambda_1. The sequence (Txn)(Tx_n) is bounded, so by compactness of TT, there exists a subsequence (still denoted xnx_n) such that TxnyTx_n \to y for some yHy \in H.

By the parallelogram law and properties of the supremum, we can show that (xn)(x_n) is Cauchy, hence converges to some e1e_1 with e1=1\|e_1\| = 1. By continuity, Te1=yTe_1 = y.

From Txn,xn±λ1\langle Tx_n, x_n \rangle \to \pm \lambda_1 and TxnTe1Tx_n \to Te_1, we get Te1,e1=±λ1\langle Te_1, e_1 \rangle = \pm \lambda_1. Setting λ1\lambda_1 to be this value (with sign), we have Te1=λ1e1Te_1 = \lambda_1 e_1.

Step 2: Orthogonal Decomposition

Let H1=span{e1}H_1 = \text{span}\{e_1\}^\perp be the orthogonal complement. For any xH1x \in H_1, we have Tx,e1=x,Te1=λ1x,e1=0\langle Tx, e_1 \rangle = \langle x, Te_1 \rangle = \lambda_1 \langle x, e_1 \rangle = 0

Thus TT maps H1H_1 to itself. The restriction TH1T|_{H_1} is also compact and self-adjoint.

Step 3: Iteration

Repeat Step 1 on H1H_1 to find λ2\lambda_2 and e2e_2, then on H2=span{e1,e2}H_2 = \text{span}\{e_1, e_2\}^\perp, and so on. This produces an orthonormal sequence {en}\{e_n\} of eigenvectors with eigenvalues {λn}\{\lambda_n\} satisfying λ1λ2|\lambda_1| \geq |\lambda_2| \geq \cdots.

Step 4: Convergence of Eigenvalues

If λn↛0\lambda_n \not\to 0, then for some ε>0\varepsilon > 0, infinitely many λnε|\lambda_n| \geq \varepsilon. The sequence (en)(e_n) satisfies en=1\|e_n\| = 1 but Ten=λnε\|Te_n\| = |\lambda_n| \geq \varepsilon. Since eneme_n \perp e_m for nmn \neq m, we have TenTem2=Ten2+Tem22ε2\|Te_n - Te_m\|^2 = \|Te_n\|^2 + \|Te_m\|^2 \geq 2\varepsilon^2. Thus (Ten)(Te_n) has no convergent subsequence, contradicting compactness.

Step 5: Completeness

Let M=span{e1,e2,}M = \overline{\text{span}\{e_1, e_2, \ldots\}}. For xMx \in M^\perp, we have x,en=0\langle x, e_n \rangle = 0 for all nn, so Tx,en=λnx,en=0\langle Tx, e_n \rangle = \lambda_n \langle x, e_n \rangle = 0. Thus TxMTx \in M^\perp.

If MHM \neq H, then TMT|_{M^\perp} is a nonzero compact self-adjoint operator, which must have a nonzero eigenvalue λ\lambda with eigenvalue ee. But this contradicts the construction. Therefore M=HM = H.

Remark

This theorem extends the diagonalization of symmetric matrices to infinite dimensions. The key difference is that eigenvalues accumulate at zero rather than being finite in number.

This spectral theorem is fundamental to solving integral equations, studying Sturm-Liouville problems, and quantum mechanics.