Eigenvalues/eignevectors of Jones matrix

In summary, the conversation discusses finding the optical component of a Jones matrix using eigenvalues and eigenvectors. It is concluded that the Jones matrix represents a quarter-wave plate oriented at 45 degrees from the incident plane. The orientation of the optical component is determined by the eigenvectors, while the phase shift is determined by the eigenvalues. The assumption that the eigenvectors determine the geometry and the eigenvalues determine the phase shift is supported by empirical testing with linearly polarised light. The speaker expresses a desire to better understand the mathematical reasoning behind this conclusion.
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I did an exercice for an optic course and the question was to find which optical component, using eigenvalues and eigenvectors, the following Jones matrix was (the common phase is not considered) :

1 i
i 1

I found that this is a quarter-wave plate oriented at 45 degree from the incident plan. To get this result, I assumed that the eigenvectors (without the normalisation):

1
1

and

1
-1 are giving the orientation (±45 degree) of the optical component, and the eigenvalues :

1+i = √(2)ei*π/4
and
1-i = √(2)e-i*π/4

are giving the phase shift.

My question is, how can I justify that this assumption about the eigenvectors giving the 'geometry' and eigenvalues giving the phase shift is correct (I know that this is a quarter-wave plate by testing empiricaly with a linearly polarised incident light).
 
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I am not familiar with the math behind the Jones calculus and I would like to understand this point better.Thank you
 

What is the definition of eigenvalues and eigenvectors of a Jones matrix?

The eigenvalues and eigenvectors of a Jones matrix refer to the special set of values and corresponding vectors that satisfy the equation Ax = λx, where A is the Jones matrix, x is the eigenvector, and λ is the eigenvalue. In other words, the eigenvectors are the vectors that do not change direction when multiplied by the Jones matrix, and the eigenvalues are the scaling factors for these eigenvectors.

Why are eigenvalues and eigenvectors important in the study of Jones matrices?

Eigenvalues and eigenvectors are important because they provide insight into the properties of a Jones matrix. For example, the eigenvalues of a Jones matrix can tell us about the polarization state of light passing through a particular optical system. Additionally, eigenvectors can be used to simplify calculations involving Jones matrices, making them an essential tool in analyzing complex optical systems.

How can you determine the eigenvalues and eigenvectors of a Jones matrix?

The process of finding the eigenvalues and eigenvectors of a Jones matrix involves solving the characteristic equation det(A - λI) = 0, where A is the Jones matrix and I is the identity matrix. This equation will result in a set of eigenvalues, which can then be used to solve for the corresponding eigenvectors.

Can Jones matrices have complex eigenvalues and eigenvectors?

Yes, Jones matrices can have complex eigenvalues and eigenvectors. This is because the eigenvalues and eigenvectors of a Jones matrix are determined by the properties of the light passing through the optical system, which can have both real and imaginary components. In fact, complex eigenvalues and eigenvectors are often necessary to fully describe the polarization state of light.

How are eigenvalues and eigenvectors used in practical applications of Jones matrices?

Eigenvalues and eigenvectors of Jones matrices are commonly used in practical applications such as optical system design and analysis, polarization measurements, and quantum information processing. They can also be used to optimize the performance of optical systems by identifying and manipulating the eigenvalues and eigenvectors that correspond to desired polarization states.

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