Problem of the Week #85 - January 13th, 2014

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Any self-adjoint operator on a real vector space can be diagonalized, as established in the discussion. The proof involves demonstrating that such an operator has at least one eigenvalue, which is derived from the properties of inner products and the definition of self-adjointness. The Real Spectral Theorem further asserts that a self-adjoint operator has an orthonormal basis composed entirely of its eigenvectors. The discussion includes detailed proofs and theorems supporting these conclusions, emphasizing the relationship between self-adjoint operators and their eigenvalues. This foundational understanding is crucial for advanced studies in linear algebra and functional analysis.
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Here's this week's problem!

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Problem: Let $E$ be a real vector space with an inner product $\langle\cdot,\cdot\rangle$. Show that any self-adjoint operator on $E$ can be diagonalized.

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This week's problem was correctly answered by caffeinemachine. You can find his very detailed solution below.

[sp]Notation
Given an operator $T\in\mathcal L(V)$, where $V$ is a finite dimensional inner product space, we write $T^*$ to denote the adjoint of $T$.
We use $U^\perp$ to denote the orthogonal complement of a subspace $U$ of an inner product space $V$.Theorem
Let $V$ be a finite dimensional real vector space. Define set $U=V\times V$; addition on $U$ occurs component-wise.
For any member $a+ib$ of $\mathbb C$ and any member $(v,w)\in U$, define $(a+ib)(v,w)=(av-bw,aw+bv)$.
Then $U$ is a finite dimensional vector space over the complex number field.
Proof.
The fact that $U$ is a vector space over the field of complex numbers is routinely proved.
We show that $U$ is finite dimensional.
Let $\{x_1,\ldots,x_n\}$ be any basis of $V$.
Let $(u,v)$ be any vector in $U$.
Write $\displaystyle\frac{u+v}{2}=\sum_{j=1}^{n}a_jx_j$ and $\displaystyle\frac{v-u}{2}=\sum_{j=1}^{n}b_jx_j$.
Thus $\displaystyle u=\sum_{j=1}^{n}a_jx_j-\sum_{j=1}^{n}b_jx_j$ and $\displaystyle v=\sum_{j=1}^{n}a_jx_j+\sum_{j=1}^{n}b_jx_j$.
This shows that $\displaystyle (u,v)=\sum_{j=1}^{n}(a_j+ib_j)(x_j,x_j)$.
So we see that $\displaystyle \{(x_j,x_j)\}_{j=1}^n$ spans $U$.
Therefore $U$ is a finite dimensional vector space over $\mathbb C$.Theorem.
Let $V$ be a finite dimensional real vector space and $T$ be any operator on $V$.
Then there exists $\lambda,\mu\in\mathbb R$ such that $Tu=\lambda u-\mu v$ and $Tv=\lambda v + \mu u$ for some $u,v\in V$, at least one of which is a non-zero vector.
Proof.
Define a vector space $U=V\times V$ as done in the theorem above.
Now define $S:U\to U$ as $S(v,w)=(Tv,Tw)$.
It's easy to see that $S$ is a linear transformation.
Since $U$ is a finite dimensional complex vector space, $S$ has an eigenvalue.
Say $\lambda+\mu i$ is an eigenvalue of $S$.
Then there exists $(u,v)\neq(0,0)$ such that $S(u,v)=(\lambda+\mu i)(u,v)$.
This gives the desired result and we are done.

Definition .
An operator $T$ on $V$ is said to be self-adjoint if $T=T^*$.Theorem.
Every self-adjoint operator has an eigenvalue.
Proof.
Let $T$ be a self-adjoint operator on a vector space $V$.
If $V$ is a complex vector space then the theorem is true even without the hypothesis that $T$ is self-adjoint.
So we may assume that $V$ is a real vector space.
From the above theorem, we know that there exist vectors $u,v\in V$, not both zero, such that $Tu=\lambda u+\mu v$ and $Tv=-\mu u+\lambda v$, for some $\lambda,\mu\in \mathbb R$.
Now, by using the fact that $T$ is self-adjoint, we can write $\langle{Tu,v}\rangle=\langle{u,Tv}\rangle$.
This gives $\langle{\lambda u+\mu v,v}\rangle=\langle{u,-\mu u+\lambda v}\rangle$.
Thus $\lambda\langle{u,v}\rangle+\mu|v|^2=-\mu|u|^2+\lambda\langle{u,v}\rangle$, from where we get $\mu(|u|^2+|v|^2)=0$.
This forces $\mu=0$ and hence $Tu=\lambda u$ and $Tv=\lambda v$. Since at least one of $u$ and $v$ is not zero, we conclude that $T$ has an eigenvalue.
Theorem.
Real Spectral Theorem. Let $T$ be a linear operator on a finite dimensional real inner-product space $V$.
Then $V$ has an orthonormal basis consisting only of eigenvectors if and only if $T$ is self-adjoint.
Proof.
One direction of the proof is trivial.
We do the proof in the other direction.
Suppose $T$ is self-adjoint over a finite dimensional real inner product space $V$.
We prove the theorem by induction on the dimension of $V$.
The base case, $\dim V=1$, is trivial.
Assume that $\dim V>1$ and that the theorem holds for all vector spaces of strictly smaller dimension.
We know that $T$ has an eigenvalue, say $\lambda$, and let $u$ be the corresponding eigenvector of norm $1$.
Let $U=\{au:a\in\mathbb R\}$ and write $S=T|_{U^\perp}$.
We now show that $U^\perp$ is invariant under $S$.
Let $v\in S$.
Now $\langle{u,Sv}\rangle=\langle{u,Tv}\rangle=\langle{Tu,v}\rangle=\lambda\langle{u,v}\rangle=0$ for all $u\in U$.
Thus $Sv\in U^\perp$.
Now we show that $S$ is self adjoint.
Let $v,w\in U^\perp$.
Now, $\langle{Sv,w}\rangle=\langle{Tv,w}\rangle=\langle{v,Tw}\rangle=\langle{v,Sw}\rangle$.
Thus $S$ is self-adjoint.
This provides us with the necessary tools to apply the induction hypothesis on $U^\perp$ as the dimension of $U^\perp$ is one less than the dimension of $V$.
Using induction, there is an orthonormal basis of $U^\perp$ consisting only of eigenvectors of $S$.
Since every eigenvector of $S$ is an eigenvector of $T$, adjoining $u$ to this orthonormal basis of $U^\perp$ given us an orthonormal basis of $V$ consisting only of eigenvectors and we are done.[/sp]
 

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