Orthogonal Diagonalization

 

Selected Homework 10 Answers,  Exercise 1.

`Exercise 1.  Eigenvalue, eigenvector analysis of `*A*`:`

A = matrix([[-2, 0, -36], [0, -3, 0], [-36, 0, -23]]), `  `*(A-I*lambda) = matrix([[-2-lambda, 0, -36], [0, -3-lambda, 0], [-36, 0, -23-lambda]])

det(A-I*lambda)*` = `*(lambda-25)*(lambda+50)*(lambda+3) = 0

evecsAval1 = 25

evecsAmul1 = 1

evecsAvec1 = vector([-4/3, 0, 1])

lambda = 25

A-I*lambda = matrix([[-27, 0, -36], [0, -28, 0], [-36, 0, -48]])

matrix([[-27, 0, -36], [0, -28, 0], [-36, 0, -48]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[1, 0, 4/3], [0, 1, 0], [0, 0, 0]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[a+4/3*c], [b], [0]]) = matrix([[0], [0], [0]])

v[1] = matrix([[-4/3], [0], [1]])

evecsAval2 = -3

evecsAmul2 = 1

evecsAvec2 = vector([0, 1, 0])

lambda = -3

A-I*lambda = matrix([[1, 0, -36], [0, 0, 0], [-36, 0, -20]])

matrix([[1, 0, -36], [0, 0, 0], [-36, 0, -20]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[1, 0, 0], [0, 0, 1], [0, 0, 0]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[a], [c], [0]]) = matrix([[0], [0], [0]])

v[2] = matrix([[0], [1], [0]])

evecsAval3 = -50

evecsAmul3 = 1

evecsAvec3 = vector([1, 0, 4/3])

lambda = -50

A-I*lambda = matrix([[48, 0, -36], [0, 47, 0], [-36, 0, 27]])

matrix([[48, 0, -36], [0, 47, 0], [-36, 0, 27]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[1, 0, -3/4], [0, 1, 0], [0, 0, 0]])*matrix([[a], [b], [c]]) = matrix([[0], [0], [0]])

matrix([[a-3/4*c], [b], [0]]) = matrix([[0], [0], [0]])

v[3] = matrix([[1], [0], [4/3]])

`A is diagonalizable using the eigenvectors of `*A*` to construct P:`

v[1] = matrix([[-4/3], [0], [1]]), v[2] = matrix([[0], [1], [0]]), v[3] = matrix([[1], [0], [4/3]])

P = matrix([[-4/3, 0, 1], [0, 1, 0], [1, 0, 4/3]]), P^`-1` = matrix([[-12/25, 0, 9/25], [0, 1, 0], [9/25, 0, 12/25]])

P^`-1`*P*` = `*matrix([[-12/25, 0, 9/25], [0, 1, 0], [9/25, 0, 12/25]])*matrix([[-4/3, 0, 1], [0, 1, 0], [1, 0, 4/3]]) = matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1]])

P^`-1`*A*P*` = `*matrix([[-12/25, 0, 9/25], [0, 1, 0], [9/25, 0, 12/25]])*matrix([[-2, 0, -36], [0, -3, 0], [-36, 0, -23]])*matrix([[-4/3, 0, 1], [0, 1, 0], [1, 0, 4/3]]) = matrix([[25, 0, 0], [0, -3, ...

`Now find an orthogonal matrix Q that orthogonally diagonalizes A.`

`Begin with the three eigenvectors of A and convert to an orthonormal set: `

v[1] = vector([-4/3, 0, 1])

v[2] = vector([0, 1, 0])

v[3] = vector([1, 0, 4/3])

`Apply Gram-Schmidt Process to these three vectors: `

w[1] = v[1]

w[2] = v[2]-`(`*v[2]*` dot`*` w`[1]*`)`/` ||`/w[1]/`||`^2*`w `[1]

w[3] = v[3]-`(`*v[3]*` dot`*` w`[1]*`)`/` ||`/w[1]/`||`^2*`w `[1]-`(`*v[3]*` dot`*` w`[2]*`)`/` ||`/w[2]/`||`^2*`w `[2]

w[1] = vector([-4/3, 0, 1])

w[2] = vector([0, 1, 0])-`(`*vector([0, 1, 0])*` dot`*vector([-4/3, 0, 1])*`)`/` ||`/vector([-4/3, 0, 1])/`||`^2*vector([-4/3, 0, 1])

w[3] = vector([1, 0, 4/3])-`(`*vector([1, 0, 4/3])*` dot`*vector([-4/3, 0, 1])*`)`/` ||`/vector([-4/3, 0, 1])/`||`^2*vector([-4/3, 0, 1])-`(`*vector([1, 0, 4/3])*` dot`*vector([0, 1, 0])*`)`/` ||`/vect...

`Obtain a basis of three orthogonal vectors: `

w[1] = vector([-4/3, 0, 1])

w[2] = vector([0, 1, 0])

w[3] = vector([1, 0, 4/3])

`Obtain an orthonormal basis of three orthogonal unit vectors: `

u[1] = 1/` ||`/w[1]/`||`*` w`[1], `   ||`*w[1]*`||` = 5/3

u[2] = 1/` ||`/w[2]/`||`*` w`[2], `   ||`*w[2]*`||` = 1

u[3] = 1/` ||`/w[3]/`||`*` w`[3], `   ||`*w[3]*`||` = 5/3

u[1] = matrix([[-4/5], [0], [3/5]]), u[2] = matrix([[0], [1], [0]]), u[3] = matrix([[3/5], [0], [4/5]])

`Use these orthonormal column vectors to construct Q:`

Q = matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]]), Q^`-1` = matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]])

Q^`-1`*Q*` = `*matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]])*matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]]) = matrix([[1, 0, 0], [0, 1, 0], [0, 0, 1]])

Q^`-1`*A*Q*` = `*matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]])*matrix([[-2, 0, -36], [0, -3, 0], [-36, 0, -23]])*matrix([[-4/5, 0, 3/5], [0, 1, 0], [3/5, 0, 4/5]]) = matrix([[25, 0, 0], [0, -3, 0]...

`So, the symmetric matrix A is orthogonally diagonalizable using the orthogonal matrix Q.`