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京都大学 情報学研究科 知能情報学専攻 2020年2月実施 線形代数

Author

思齐塾, 祭音Myyura

Description

Let aa and bb be real numbers. We define a matrix

A=(0aba01b10)A = \begin{pmatrix} 0 & a & b \\ a & 0 & 1 \\ b & 1 & 0 \end{pmatrix}

In all of the questions (1), (2), (3), and (4), assume that an eigenvalue (characteristic value) of AA is 1.

(1) What is the relation between aa and bb ?

(2) When a=0a = 0 , list all eigenvalues of AA .

In questions (3) and (4), let us additionally assume that a>0a > 0 and also that the characteristic polynomial of AA has a double (multiple) root of an integer.

(3) Give the eigenvector vv corresponding to the smallest eigenvalue of AA .

(4) Give a pair of vectors uu and ww satisfying all of the following conditions:

  • both uu and ww are eigenvectors corresponding to the eigenvalue which is the double root of the characteristic polynomial of AA ,
  • uu is orthogonal to both e=(001)e = \begin{pmatrix} 0 \\ 0 \\ 1 \end{pmatrix} and ww , and
  • u=w=1||u|| = ||w|| = 1 .

题目描述

a,ba,b 为实数,并定义

A=(0aba01b10).A= \begin{pmatrix} 0&a&b\\ a&0&1\\ b&1&0 \end{pmatrix}.

在以下第 1–4 问中,始终假设 11AA 的一个特征值。

  1. aabb 之间必须满足的关系。
  2. a=0a=0 时,列出 AA 的全部特征值。

在第 3、4 问中,进一步假设 a>0a>0,并且 AA 的特征多项式有一个整数二重根。

  1. 求与 AA 的最小特征值对应的一个特征向量 v\boldsymbol{v}

  2. 求一对向量 u,w\boldsymbol{u},\boldsymbol{w},使其同时满足:

    • u\boldsymbol{u}w\boldsymbol{w} 都是特征多项式二重根所对应的特征向量;
e=(001),\boldsymbol{e} = \begin{pmatrix} 0\\0\\1 \end{pmatrix},

u\boldsymbol{u} 同时与 e\boldsymbol{e}w\boldsymbol{w} 正交;

  • u=w=1\|\boldsymbol{u}\|=\|\boldsymbol{w}\|=1

Kai

(1) Since 1 is an eigenvalue of A, we have det(AI)=0\det(A - I) = 0 , where II is the identity matrix. Therefore,

det(AI)=det(1aba11b11)=1(11)a(ab)+b(a+b)=a2+ab+ab+b2=a2+2ab+b2=(a+b)2=0\det(A - I) = \det\begin{pmatrix} -1 & a & b \\ a & -1 & 1 \\ b & 1 & -1 \end{pmatrix} = -1(1-1) - a(-a-b) + b(a+b) = a^2 + ab + ab + b^2 = a^2 + 2ab + b^2 = (a+b)^2 = 0

Thus, a+b=0a+b = 0 , so b=ab = -a .

(2) When a=0a=0 , we have b=a=0b = -a = 0 . Then the matrix AA becomes

A=(000001010)A = \begin{pmatrix} 0 & 0 & 0 \\ 0 & 0 & 1 \\ 0 & 1 & 0 \end{pmatrix}

The characteristic polynomial is given by

det(AλI)=det(λ000λ101λ)=λ(λ21)=λ(λ1)(λ+1)=0\det(A - \lambda I) = \det\begin{pmatrix} -\lambda & 0 & 0 \\ 0 & -\lambda & 1 \\ 0 & 1 & -\lambda \end{pmatrix} = -\lambda(\lambda^2 - 1) = -\lambda(\lambda - 1)(\lambda + 1) = 0

The eigenvalues are λ1=0,λ2=1,λ3=1\lambda_1 = 0, \lambda_2 = 1, \lambda_3 = -1 .

(3) We are given a>0a>0 and that the characteristic polynomial has a double root. Also b=ab=-a , so A=(0aaa01a10)A = \begin{pmatrix} 0 & a & -a \\ a & 0 & 1 \\ -a & 1 & 0 \end{pmatrix} . The characteristic polynomial is

det(AλI)=det(λaaaλ1a1λ)=λ(λ21)a(aλ+a)a(aaλ)=λ3+λ+a2λa2a2+a2λ=λ3+(1+2a2)λ2a2=0\det(A - \lambda I) = \det\begin{pmatrix} -\lambda & a & -a \\ a & -\lambda & 1 \\ -a & 1 & -\lambda \end{pmatrix} = -\lambda(\lambda^2 - 1) - a(-a\lambda + a) - a(a - a\lambda) = -\lambda^3 + \lambda + a^2\lambda - a^2 - a^2 + a^2\lambda = -\lambda^3 + (1 + 2a^2)\lambda - 2a^2 = 0

Dividing by λ1\lambda - 1 , we get

(λ1)(λ2+λ2a2)=0-(\lambda - 1)(\lambda^2 + \lambda - 2a^2) = 0

The other roots are λ=1±1+8a22\lambda = \frac{-1 \pm \sqrt{1 + 8a^2}}{2} . The two roots of the quadratic cannot coincide because 1+8a2>01+8a^2>0 . Hence a double root occurs only when one of them is equal to the already known root 1. Thus 1+12a2=01+1-2a^2=0 , and a=1a=1 because a>0a>0 . Therefore the eigenvalues are 1,1,21,1,-2 . For the smallest eigenvalue 2-2 ,

(A+2I)v=0(A+2I)v=0

is satisfied by

v=(111).v=\begin{pmatrix} 1 \\ -1 \\ 1 \end{pmatrix}.

(4) The eigenspace for the double eigenvalue 1 is given by

x+yz=0.-x+y-z=0.

The unit vector in this eigenspace that is orthogonal to ee can be chosen as

u=12(110).u=\frac{1}{\sqrt{2}}\begin{pmatrix} 1 \\ 1 \\ 0 \end{pmatrix}.

Within the same eigenspace, a vector orthogonal to uu is (1,1,2)T(1,-1,-2)^T . Hence we may choose

w=16(112).w=\frac{1}{\sqrt{6}}\begin{pmatrix} 1 \\ -1 \\ -2 \end{pmatrix}.

Then Au=uAu=u , Aw=wAw=w , ue=0u\cdot e=0 , uw=0u\cdot w=0 , and u=w=1||u||=||w||=1 .