Eigenvalues and eigenvectors, pauli matrices

In summary, the matrix A has two eigenvalues of +-1 and two eigenvectors that are linear combinations of these values.
  • #1
ma18
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1

Homework Statement



Look at the matrix:

A = sin t sin p s_x + sin t sin p s_y +cos t s_z

where s_i are the pauli matrices

a) Find the eigenvalues and normalized eigenvectors (are they orthogonal)?

b) Write the eigenvector of s_x with positive eigenvalue as a linear combination of the eigenvalues of A

Homework Equations

The Attempt at a Solution



I got an answer but I am not confident as to it's veracity.

The matrix A is :

(cos t , sin t cos p - i sin t sin p
sin t cos p + i sin t sin p, - cos t)

or

(cos t, sin t (e^-i p)
sin t (e^ip), - cos t)

Finding the eigenvalues

(cos t - lambda, sin t (e^i p)
sin t (e^i p), - cos t - lambda)

You get

lambda^2 - 1 = 0

So the eigenvalues are +-1

The problem is finding the eigenvectors;

For +1

(cos t - 1, sin t e^(-i p )
sin t e^i p, - cos t - 1)

Using the cofactor method you get the equations

(cos t - 1) x +(sin e^i p) y = 0

(sin t e^i p) x + (-cos t - 1) y = 0

I get

v1 = C_1 (-e^-i p tan (t/2), 1)
v2 = C_2 (-e^i p tan (t/2), 1)

Then normalizing

C_1 = 1/sqrt(e^-2 i p tan (t/2)^2 + 1)

C_2 = 1/sqrt(e^-2 i p cot (t/2)^2 + 1)

I don't know how to do b

Any help/checking would be helpful
 
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  • #2
ma18 said:
The problem is finding the eigenvectors;

For +1

(cos t - 1, sin t e^(-i p )
sin t e^i p, - cos t - 1)

Using the cofactor method you get the equations

(cos t - 1) x +(sin e^i p) y = 0

(sin t e^i p) x + (-cos t - 1) y = 0
Looks good so far. Try using the trig identities ##\sin^2 \frac \theta 2 = \frac{1 - \cos \theta}{2}## and ##\sin \theta = 2 \sin\frac \theta 2 \cos \frac \theta 2##. That'll make the algebra a bit easier to deal with.
 
  • #3
Thanks for all your help guys!
 

FAQ: Eigenvalues and eigenvectors, pauli matrices

What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are mathematical concepts used in linear algebra. Eigenvalues represent the scale factor by which an eigenvector is scaled when it is multiplied by a linear transformation matrix. Eigenvectors are non-zero vectors that are only scaled by a scalar factor when multiplied by a linear transformation matrix.

How are eigenvalues and eigenvectors used in science?

Eigenvalues and eigenvectors have many applications in science, including in quantum mechanics and physics, where they are used to describe the behavior of physical systems. They are also used in image processing, data compression, and computer graphics.

What are the Pauli matrices?

The Pauli matrices are a set of three 2x2 matrices named after physicist Wolfgang Pauli. They are used to represent spin in quantum mechanics and are important in describing the behavior of particles with spin, such as electrons and protons.

How are the Pauli matrices related to eigenvalues and eigenvectors?

The Pauli matrices have two eigenvectors each, which correspond to the two possible spin states of a particle. The eigenvalues of the Pauli matrices represent the possible spin values that a particle can have. The relationship between the Pauli matrices and eigenvalues and eigenvectors is important in the study of quantum mechanics.

Can you give an example of how eigenvalues and eigenvectors are used in real-world applications?

One example of how eigenvalues and eigenvectors are used in real-world applications is in principal component analysis (PCA). PCA is a statistical method used to reduce the dimensionality of a data set while retaining as much information as possible. It relies on finding the eigenvalues and eigenvectors of a covariance matrix, which helps to identify the most important features of the data set.

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