Crossing statistics of laser light scattered through a nanofluid
| Autor: | S. M. S. Movahed, Rouhollah Karimzadeh, M. Arshadi Pirlar, D. Razzaghi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Gaussian
FOS: Physical sciences Probability density function Condensed Matter - Soft Condensed Matter 01 natural sciences Speckle pattern symbols.namesake Optics Consistency (statistics) 0103 physical sciences Statistics 010306 general physics 010303 astronomy & astrophysics Condensed Matter - Statistical Mechanics Mathematics Physical quantity Statistical Mechanics (cond-mat.stat-mech) business.industry Fluid Dynamics (physics.flu-dyn) Probability and statistics Physics - Fluid Dynamics Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials Physics - Data Analysis Statistics and Probability Time derivative symbols Soft Condensed Matter (cond-mat.soft) Computer Vision and Pattern Recognition business Fresnel diffraction Data Analysis Statistics and Probability (physics.data-an) Physics - Optics Optics (physics.optics) |
| DOI: | 10.48550/arxiv.1705.03542 |
| Popis: | In this paper, we investigate the crossing statistics of speckle patterns formed in Fresnel diffraction region by a laser beam scattering through a nanofluid. We extend $zero-crossing$ statistics to assess dynamical properties of nanofluid. According to joint probability density function of laser beam fluctuation and its time derivative, theoretical framework for Gaussian and non-Gaussian regimes are revisited. We count number of crossings not only at {\it zero} level but also for all available thresholds to determine the average speed of moving particles. Using probabilistic framework in determining crossing statistics, {\it a priori} Gaussianity is not essentially considered, therefore even in presence of deviation from Gaussian fluctuation, this modified approach is capable to compute relevant quantities such as mean value of speed more precisely. Generalized total crossing which represents the weighted summation of crossings for all thresholds to quantify small deviation from Gaussian statistics is introduced. This criterion can also manipulate the contribution of noises and trends to infer reliable physical quantities. The characteristic time scale for having successive crossings at a given threshold is defined. In our experimental setup, we find that increasing sample temperature leads to more consistency between Gaussian and perturbative non-Gaussian predictions. The maximum number of crossing does not necessarily occur at mean level indicating that we should take into account other levels in addition to {\it zero} level to achieve more accurate assessments. Comment: 12 pages, 7 figures, 2 tables. Matched to accepted version |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|