Created by M. Oki Orlandofrom the Noun Project

Diagonal

Definition (Diagonal)

A matrix A=[ai,j]Fn×nA=[a_{i,j}]\in\mathbb{F}^{n\times n} is called diagonal is ai,j=0a_{i,j}=0 whenever iji\not=j i.e.: A:=[a1,10000a2,20000a3,30000an,n] A:= \begin{bmatrix} a_{1,1} & 0 & 0 &\cdots & 0 \\ 0 & a_{2,2} & 0 & \cdots & 0 \\ 0 & 0 & a_{3,3} & \cdots & 0 \\\vdots & \vdots & \vdots & \ddots & \vdots \\ 0 & 0 & 0 & \cdots & a_{n,n}\\ \end{bmatrix}We say the elements ai,ia_{i,i} are “on the diagonal” of AA.

Definition (Diagonalizable)

Let VV be a Finite Dimensional Vector Space and we define some Linear Map TL(V)T\in\mathscr{L}(V). If there is a Finite Basis of VV such that M(T)\mathcal{M}(T) is Diagonal, then we say TT is a diagonalizable.

Remark

Using this theorem we can say that if M(T)\mathcal{M}(T) then M(T)=PDP1=[v1TvnT][λ10000λn][v1TvnT]1\begin{align*} \mathcal{M}(T)&=PDP^{-1}\\ &=\begin{bmatrix}v_{1}^T & \cdots & v_n^T \\ \end{bmatrix}\begin{bmatrix}\lambda_{1} & \cdots & 0 \\ 0 & \ddots & 0 \\ 0 & \cdots & \lambda_{n}\end{bmatrix} \begin{bmatrix}v_{1}^T & \cdots & v_n^T \\ \end{bmatrix}^{-1} \end{align*}where λ1,,λn\lambda_1,\cdots,\lambda_{n} are eigenvalues of TT and v1,,vnv_1,\cdots,v_n are the corresponding eigenvectors.

Proposition (Enough Diagonal Elements Imply Diagonalizability)

Let VV be a finite dimensional vector space with dim(V)=ndim(V)=n, and TL(V)T\in\mathscr{L}(V). If TT has nn distinct eigenvalues, then there is a basis such that M(T)\mathcal{M}(T) is Diagonal.

[!prp] Equivalent conditions for diagonalizability Let VV be a Finite Dimensional Vector Space, where dim(V)=ndim(V)=n, and TL(V)T\in\mathscr{L}(V). If λ1,,λm\lambda_1,\cdots,\lambda_m are all distinct eigenvalues of TT, then the following statements are equivalent.

  1. TT is
  2. There is a basis for VV consisting of eigenvectors of TT
  3. There exists 1-dimensional subspaces W1,,WnW_1,\cdots,W_n of VV, each of which are invariant under TT, such that V=W1WnV=W_1\oplus\cdots\oplus W_n.
  4. VV is a direct sum of eigenspaces. That is, V=\mboxKer(Tλ1IV)\mboxKer(TλmIV)V=\mbox{Ker}(T-\lambda_{1}I_{V})\oplus\cdots\oplus\mbox{Ker}(T-\lambda_{m}I_{V})
  5. \mboxdim(V)=\mboxdim(\mboxKer(Tλ1IV))\mboxdim(\mboxKer(TλmIV))\mbox{dim}(V)=\mbox{dim}(\mbox{Ker}(T-\lambda_{1}I_{V}))\oplus\cdots\oplus\mbox{dim}(\mbox{Ker}(T-\lambda_{m}I_{V}))

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