3.6 KiB
Lecture 37
Chapter VIII Operators on complex vector spaces
Generalized Eigenspace Decomposition 8B
Review
Definition 8.19
The generalized eigenspace of T for \lambda \in \mathbb{F} is G(\lambda,T)=\{v\in V\vert (T-\lambda I)^k v=0\textup{ for some k>0}\}
Theorem 8.20
G(\lambda, T)=null((T-\lambda I)^{dim\ V})
New materials
Theorem 8.31
Suppose v_1,...,v_n is a basis where M(T,(v_1,...,v_k)) is upper triangular. Then the number of times \lambda appears on the diagonal is the multiplicity of \lambda as an eigenvalue of T.
Proof:
Let \lambda_1,...,\lambda_n be the diagonal entries, S be such that M(S,(v_1,...,v_n)) is upper triangular. Note that if \mu_1,...,\mu_n are the diagonal entires of M(S), then the diagonal entires of M(S^n) are \mu_1^n,...,\mu_n^n
\begin{aligned}
dim(null\ S^n)&=n-dim\ range\ (S^n)\leq n-\textup{ number of non-zero diagonal entries on } S^n\\
&=\textup{ number of zero diagonal entries of }S^n
\end{aligned}
plus in S=T-\lambda I, then
\begin{aligned}
dim G(\lambda, T)&=dim(null\ (T-\lambda I)^n)\\
&\leq \textup{number times where }\lambda \textup{ appears on the diagonal of }M(T)\\
\end{aligned}
Note:
V=G(\lambda_1, T)\oplus \dots \oplus G(\lambda_k, T)
for distinct \lambda_1,...,\lambda_k thus n=dim\ G(\lambda_1,T)+\dots +dim\ (\lambda_k, T)
on the other hand n=\textup{ number of times }\lambda_1 \textup{ appears as a diagonal entry}+\dots +\textup{ number of times }\lambda_k \textup{ appears as a diagonal entry}+\dots
So dim\ G(\lambda_i, T)= number of times where \lambda_i appears oas a diagonal entry.
Definition 8.35
A block diagonal matrix is a matrix of the form $\begin{pmatrix}
A_1& & 0\
& \ddots &\
0& & A_m
\end{pmatrix}$ where A_k is a square matrix.
Example:
$ \begin{pmatrix} 1&0&0 & 0&0\ 0 & 2 &1&0&0\ 0 & 0 &2&0&0\ 0& 0&0& 4&1\ 0& 0&0& 0&4\ \end{pmatrix}$
Theorem
Let V be a complex vector space and let \lambda_1,...,\lambda_m be the distinct eigenvalue of T with multiplicity d_1,...,d_m, then there exists a basis where $\begin{pmatrix}
A_1& & 0\
& \ddots &\
0& & A_m
\end{pmatrix}$ where A_k is a d_k\times d_k matrix upper triangular with only \lambda_k on the diagonal.
Proof:
Note that (T-\lambda_k I)\vert_{G(\lambda_k,T)} is nilpotent. So there is a basis of G(\lambda_k,T) where (T-\lambda_k I)\vert_{G(\lambda_k,T)} is upper triangular with zeros on the diagonal. Then (T-\lambda_k I)\vert_{G(\lambda_k,T)} is upper triangular with \lambda_k on the diagonal.
Jordan Normal Form 8C
Nilpotent operators
Example: $T(x,y,z)=(0,x,y), M(T)=\begin{pmatrix} 0&1&0\ 0&0&1\ 0&0&0 \end{pmatrix}$
Definition 8.44
Let T\in \mathscr{L}(V) a basis of V is a Jordan basis of T if in that basis $\begin{pmatrix}
A_1& & 0\
& \ddots &\
0& & A_p
\end{pmatrix}$ where each $A_k=\begin{pmatrix}
\lambda_1& 1& & 0\
& \ddots& \ddots &\
&&\ddots& 1\
0&&&\lambda_k\
\end{pmatrix}$
Theorem 8.45
Suppose T\in \mathscr{L}(V) is nilpotent, then there exists a basis of V that is a Jordan basis of T.
Sketch of Proof:
Induct on dim\ V, if dim\ V=1, clear.
if dim\ V>1, then let m be such that T^m=0 and T^{m-1}\neq 0. Then \exists u\in V such that T^{m-1}u\neq 0, then Span (u,Tu, ...,T^{m-1}u) is m dimensional.
Theorem 8.46
Suppose V is a complex vector space T\in \mathscr{L}(V) then T has a Jordan basis.
Proof:
take V=G(\lambda_1, T)\oplus \dots \oplus G(\lambda_m, T), then look at (T-\lambda_k I)\vert_{G(\lambda_k,T)}