On optimal filtering of measured Mueller matrices

Area of Science:

• Optics and Photonics
• Mathematical Physics

Background:

• Light polarization states are often described as mixed states, a combination of pure and random states.
• Mueller matrices are essential for characterizing the polarization properties of optical systems.

Purpose of the Study:

• To develop a characteristic decomposition for Mueller matrices.
• To establish a framework for quantifying polarimetric randomness.
• To provide criteria for noise filtering in polarimetry.

Main Methods:

• Decomposition of Mueller matrices into a convex combination of components.
• Objective scaling of randomness for additional components.

Main Results:

• Any Mueller matrix can be uniquely decomposed into a pure component and three additional components.
• The randomness of these components is scaled objectively.
• This decomposition provides a robust method for characterizing polarimetric randomness.

Conclusions:

• The characteristic decomposition offers a novel framework for Mueller matrix analysis.
• It enables objective assessment of polarimetric system randomness.
• The method facilitates optimal noise reduction in experimental polarimetry.