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Markovian optical modes.

G Martínez Niconoff, M A Torres Rodriguez, G Díaz Gonzalez

|March 14, 2015

Summary

This summary is machine-generated.

This study shows how optical modes transition using Markov chains, creating tunable partially coherent modes. The resulting mode

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Area of Science:

Physics
Optics
Quantum Optics

Background:

Partially coherent modes are crucial in optical systems.
Controlling coherence properties is essential for advanced applications.
Markov chains offer a probabilistic framework for dynamic systems.

Purpose of the Study:

To investigate the transition of optical modes using Markov chain processes.
To develop a method for tuning coherence features of optical modes.
To explore the relationship between Markov chain parameters and mode amplitude.

Main Methods:

Modeling optical mode transitions as a Markov chain.
Analyzing the convergence of mean amplitude values.
Utilizing Bessel modes of integer order as a vector space basis.
Employing computer simulations for validation.

Main Results:

Demonstrated convergence to a new type of partially coherent mode.
Showcased that coherence features are tunable via Markov chain parameters.
Established an analogy with gambler's chain ruin for mode behavior.
Mode amplitude is dependent on the chain's probability transitions.

Conclusions:

Markov chain processes provide a novel framework for generating and controlling partially coherent optical modes.
The gambler's ruin analogy offers insights into the underlying dynamics.
Tunable coherence properties open possibilities for advanced optical technologies.