Classification and Generation of Light Sources Using Gamma Fitting

TL;DR

This paper introduces a novel Gamma fitting method using a single parameter to classify and generate various light sources, including antibunching, bunching, and superbunching, with experimental validation and potential applications.

Contribution

The paper presents a new Gamma fitting approach that simplifies classification and generation of light sources based on a single characteristic parameter, enhancing existing methods.

Findings

Experimental results agree with the Gamma fitting classification.

Temperature and laser detuning influence the classification results.

Bunching and superbunching distinguished in super-Poissonian statistics.

Abstract

In general, the typical approach to discriminate antibunching, bunching or superbunching categories make use of calculating the second-order coherence function ${g^{(2)}}(\tau )$ of light. Although the classical light sources correspond to the specific degree of second-order coherence ${g^{(2)}}(0)$, it does not alone constitute a distinguishable metric to characterize and determine light sources. Here we propose a new mechanism to directly classify and generate antibunching, bunching or superbunching categories of light, as well as the classical light sources such as thermal and coherent light, by Gamma fitting according to only one characteristic parameter $\alpha$ or $\beta$. Experimental verification of beams from four-wave mixing process is in agreement with the presented mechanism, and the in fluence of temperature $T$ and laser detuning $\Delta$ on the measured results are investigated. The proposal demonstrates the potential of classifying and identifying light with different nature, and the most importantly, provides a convenient and simple method to generate light sources meeting various application requirements according to the presented rules. Most notably, the bunching and superbunching are distinguishable in super-Poissonian statistics using our mechanism.