Diagonalize a matrix (help for exam)

In summary, the conversation is about finding a matrix that diagonalizes a given 2x2 matrix and determining its properties. The conversation includes discussions on computing characteristic equations and eigenvectors. The expert summarizer provides guidance on how to approach the problem and addresses the confusion regarding square roots in row reduction.
  • #1
Gramsci
66
0

Homework Statement



Find a matrix that diagonalizes the following 2x2 matrix:

A= (1/2 , sqrt(3)/2
sqrt(3)/2,-1/2)

What will the diagonalizing matrix D be? What does D mean geometrically? What does A mean geometrically?

Homework Equations


-


The Attempt at a Solution



First I began with computing the characteristic equations determinant:
det A-lambda(call it x)= (1/2-x)(-1/2-x)-(sqrt3/2)(sqrt3/2)=X^2=-1
and since we haven't begun with complex eigenvalues yet:
x(x)=-1
Thus, x1=1 and x2=-1

Then I'm trying to compute the eigenvectors, but I seem to fail after I've added -1 I get:

3/2 , sqrt(3)/2
sqrt(3)/2, 1/2

after row reduction:
3, sqrt(3)
0, 0

Therefore, the eigenvector for -1 have to be (sqrt(3),3)
But according to my solutions manual, it is : 1, - sqrt 3

How do I count for the second one? All these square roots confuse me, any tips on how I handle them in row reduction?

/Gramsci
 
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  • #2
Gramsci said:

Homework Statement



Find a matrix that diagonalizes the following 2x2 matrix:

A= (1/2 , sqrt(3)/2
sqrt(3)/2,-1/2)

What will the diagonalizing matrix D be? What does D mean geometrically? What does A mean geometrically?

Homework Equations


-


The Attempt at a Solution



First I began with computing the characteristic equations determinant:
det A-lambda(call it x)= (1/2-x)(-1/2-x)-(sqrt3/2)(sqrt3/2)=X^2=-1
and since we haven't begun with complex eigenvalues yet:
x(x)=-1
Thus, x1=1 and x2=-1
You can't just declare the eigenvalues to be 1 and -1 because "haven't begun with complex eigenvalues yet"! What that tells you is that you have the wrong equation. (The eigenvalues of a symmetric matrix are always real.) (1/2- x)(-1/2- x)- (sqrt(3)/2)^2= x^2- 1/4- 3/4= x^2- 1= 0 which does have 1 and -1 as roots. Was that sheer luck?

Then I'm trying to compute the eigenvectors, but I seem to fail after I've added -1 I get:

3/2 , sqrt(3)/2
sqrt(3)/2, 1/2

after row reduction:
3, sqrt(3)
0, 0

Therefore, the eigenvector for -1 have to be (sqrt(3),3)
But according to my solutions manual, it is : 1, - sqrt 3
You "added" -1? Since you were subtracting lambda, that means you subtracted 1. What you found is an eigenvector corresponding to 1, not -1. Also, any multiple of an eigenvector is also an eigenvector so there can be many different answer. If, for example, you divide what you got by sqrt(3), you get (1, sqrt(3)) as another eigenvector corresponding to the eigenvalue 1.

How do I count for the second one? All these square roots confuse me, any tips on how I handle them in row reduction?

/Gramsci
Go back to the originally matrix and subtract -1 rather than 1 (add 1 rather than -1). Row reduce that.
 
  • #3
Thanks for the help, now I get it. Thanks.
 

What is diagonalization of a matrix?

Diagonalization is the process of finding a diagonal matrix that is similar to a given square matrix. It involves finding a set of eigenvalues and eigenvectors that can be used to transform the original matrix into a diagonal form.

Why is diagonalization important in linear algebra?

Diagonalization is important because it simplifies the calculation of powers and inverses of matrices, and also makes it easier to solve systems of linear equations. It also provides insight into the properties and behavior of the matrix, such as its trace and determinant.

How do you diagonalize a matrix?

To diagonalize a matrix, you first need to find its eigenvalues and eigenvectors. Then, you can use these eigenvectors to form a matrix P, and the diagonal matrix D is found by multiplying P with the original matrix A and its inverse P^-1, such that A = PDP^-1.

What is the significance of eigenvalues and eigenvectors in diagonalization?

Eigenvalues and eigenvectors play a crucial role in diagonalization as they are used to transform the original matrix into a diagonal form. Eigenvectors also provide information about the direction and magnitude of the transformation, while eigenvalues determine the scale of the transformation.

Can any matrix be diagonalized?

Not all matrices can be diagonalized. A matrix can only be diagonalized if it has a full set of linearly independent eigenvectors. This means that the matrix must have n distinct eigenvalues, where n is the size of the matrix. If the matrix does not have a full set of eigenvectors, it is said to be defective and cannot be diagonalized.

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