Issue |
EPL
Volume 137, Number 1, January 2022
|
|
---|---|---|
Article Number | 11001 | |
Number of page(s) | 6 | |
Section | Statistical physics and networks | |
DOI | https://doi.org/10.1209/0295-5075/ac3e36 | |
Published online | 05 April 2022 |
Identification and generation of different statistical distributions of light using Gamma modeling
1 Electronic Materials Research Laboratory, Key Laboratory of the Ministry of Education & International Center for Dielectric Research, School of Electronic Science and Engineering, Xi'an Jiaotong University Xi'an, Shaanxi 710049, China
2 School of Physics & Astronomy, University of Glasgow - Glasgow G12 8QQ, UK
3 MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter, Department of Applied Physics, Xi'an Jiaotong University - Xi'an 710049, China
(a) huaibinzheng@xjtu.edu.cn (corresponding author)
Received: 28 April 2021
Accepted: 29 November 2021
Correlation measurement or calculation is typically used to classify the antibunched, bunched, or superbunched light with the degree of second-order coherence. However, it cannot characterize and identify the statistical distribution type of light. Since the statistical distributions of many classical light sources can be characterized by the generalized Gamma distribution, here we propose a new method to directly identify and generate classical light with different correlation properties by Gamma modeling from statistics rather than correlation. Experimental verification of beams from a four-wave mixing process agrees with this method, and the influences of temperature and laser detuning on the measured results are investigated. The proposal demonstrates an efficient approach to classifying and identifying classical light sources using Gamma modeling. More importantly, it can flexibly design and generate the required correlated lights meeting various optical applications according to the presented rules.
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