🎉 从330转为WashU帮助手册啦!

Math429
模块
Math429 L37

Lecture 37

Chapter VIII Operators on complex vector spaces

Generalized Eigenspace Decomposition 8B


Review

Definition 8.19

The generalized eigenspace of TT for λF\lambda \in \mathbb{F} is G(λ,T)={vV(TλI)kv=0 for some k>0}G(\lambda,T)=\{v\in V\vert (T-\lambda I)^k v=0\textup{ for some k>0}\}

Theorem 8.20

G(λ,T)=null((TλI)dim V)G(\lambda, T)=null((T-\lambda I)^{dim\ V})


New materials

Theorem 8.31

Suppose v1,...,vnv_1,...,v_n is a basis where M(T,(v1,...,vk))M(T,(v_1,...,v_k)) is upper triangular. Then the number of times λ\lambda appears on the diagonal is the multiplicity of λ\lambda as an eigenvalue of TT.

Proof:

Let λ1,...,λn\lambda_1,...,\lambda_n be the diagonal entries, SS be such that M(S,(v1,...,vn))M(S,(v_1,...,v_n)) is upper triangular. Note that if μ1,...,μn\mu_1,...,\mu_n are the diagonal entires of M(S)M(S), then the diagonal entires of M(Sn)M(S^n) are μ1n,...,μnn\mu_1^n,...,\mu_n^n

dim(null Sn)=ndim range (Sn)n number of non-zero diagonal entries on Sn= number of zero diagonal entries of Sn\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=TλIS=T-\lambda I, then

dimG(λ,T)=dim(null (TλI)n)number times where λ appears on the diagonal of M(T)\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(λ1,T)G(λk,T)V=G(\lambda_1, T)\oplus \dots \oplus G(\lambda_k, T)

for distinct λ1,...,λk\lambda_1,...,\lambda_k thus n=dim G(λ1,T)++dim (λk,T)n=dim\ G(\lambda_1,T)+\dots +dim\ (\lambda_k, T)

on the other hand n= number of times λ1 appears as a diagonal entry++ number of times λk appears as a diagonal entry+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(λi,T)=dim\ G(\lambda_i, T)= number of times where λi\lambda_i appears oas a diagonal entry.

Definition 8.35

A block diagonal matrix is a matrix of the form (A100Am)\begin{pmatrix} A_1& & 0\\ & \ddots &\\ 0& & A_m \end{pmatrix} where AkA_k is a square matrix.

Example:

(1000002100002000004100004) \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 VV be a complex vector space and let λ1,...,λm\lambda_1,...,\lambda_m be the distinct eigenvalue of TT with multiplicity d1,...,dmd_1,...,d_m, then there exists a basis where (A100Am)\begin{pmatrix} A_1& & 0\\ & \ddots &\\ 0& & A_m \end{pmatrix} where AkA_k is a dk×dkd_k\times d_k matrix upper triangular with only λk\lambda_k on the diagonal.

Proof:

Note that (TλkI)G(λk,T)(T-\lambda_k I)\vert_{G(\lambda_k,T)} is nilpotent. So there is a basis of G(λk,T)G(\lambda_k,T) where (TλkI)G(λk,T)(T-\lambda_k I)\vert_{G(\lambda_k,T)} is upper triangular with zeros on the diagonal. Then (TλkI)G(λk,T)(T-\lambda_k I)\vert_{G(\lambda_k,T)} is upper triangular with λk\lambda_k on the diagonal.

Jordan Normal Form 8C

Nilpotent operators

Example: T(x,y,z)=(0,x,y),M(T)=(010001000)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 TL(V)T\in \mathscr{L}(V) a basis of VV is a Jordan basis of TT if in that basis (A100Ap)\begin{pmatrix} A_1& & 0\\ & \ddots &\\ 0& & A_p \end{pmatrix} where each Ak=(λ11010λk)A_k=\begin{pmatrix} \lambda_1& 1& & 0\\ & \ddots& \ddots &\\ &&\ddots& 1\\ 0&&&\lambda_k\\ \end{pmatrix}

Theorem 8.45

Suppose TL(V)T\in \mathscr{L}(V) is nilpotent, then there exists a basis of VV that is a Jordan basis of TT.

Sketch of Proof:

Induct on dim Vdim\ V, if dim V=1dim\ V=1, clear.

if dim V>1dim\ V>1, then let mm be such that Tm=0T^m=0 and Tm10T^{m-1}\neq 0. Then uV\exists u\in V such that Tm1u0T^{m-1}u\neq 0, then Span(u,Tu,...,Tm1u)Span (u,Tu, ...,T^{m-1}u) is mm dimensional.

Theorem 8.46

Suppose VV is a complex vector space TL(V)T\in \mathscr{L}(V) then TT has a Jordan basis.

Proof:

take V=G(λ1,T)G(λm,T)V=G(\lambda_1, T)\oplus \dots \oplus G(\lambda_m, T), then look at (TλkI)G(λk,T)(T-\lambda_k I)\vert_{G(\lambda_k,T)}