Neural network classification of beams carrying orbital angular momentum after propagating through controlled experimentally generated optical turbulence.

We generate an alphabet of spatially multiplexed Laguerre-Gaussian beams carrying orbital angular momentum, which are demultiplexed at reception by a convolutional neural network (CNN). In this investigation, a methodology for optimizing alphabet design for best classification rates is proposed, and three 256-symbol alphabets are designed for performance evaluation in optical turbulence. The beams were propagated in three environments: through underwater optical turbulence generated by Rayleigh-Bénard (RB) convection (C n2≅10-11 m -2/3), through a simulated propagation path derived from the Nikishov spectrum (C n2≅10-13 m -2/3), and through optical turbulence from a thermal point source located in a water tank (C n2≅10-10 m -2/3). We report a classification accuracy of 93.1% for the RB environment, 99.99% in simulation, and 48.5% in the point source environment. The project demonstrates that the CNN can classify the complex alphabet symbols in a practical turbulent flow that exhibits strong optical turbulence, provided sufficient training data is available and testing data is representative of the specific environment. We find the most important factor in a high classification accuracy is a diversification in the intensity profiles of the alphabet symbols.

Randomness of optical turbulence generated by Rayleigh-Bénard convection using intensity statistics.

The experimental study of optical turbulence proves difficult due to challenges in generating controllable conditions in a laboratory environment. Confined water tanks that produce Rayleigh-Bénard (RB) convection are one method to generate optical turbulence using a controllable temperature gradient. It is of utmost concern to quantify the properties of the optical turbulence generated for characterization of other optical applications such as imaging, sensing, or communications. In this experimental study a Gaussian beam is propagated through a RB water tank where two intensity measurements are made at the receiver's pupil and focal plane. The pupil and focal plane results include quantification of the intensity fluctuation distribution, scintillation distribution, and refractive index structure constant at various values of the temperature gradient. The angle of arrival fluctuations is also calculated at the focal plane to obtain a second estimate of C n2. The pupil plane estimate for C n2 using scintillation index and focal plane angle of arrival fluctuations is compared to preliminary predictions of C n2 as a function of RB temperature gradient showing C n2âˆ¼Δ T 4/3. The outcomes of the study confirm that the RB process produces intensity fluctuations that follow gamma-gamma and log-normal probability density functions. Estimates of the refractive index structure constant C n2 produce the same trends with different magnitudes when measured from the pupil and focal plane.

Propagation through and characterization of atmospheric and oceanic phenomena: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

This joint feature issue in Applied Optics and JOSA A collects articles focused on the topic of propagation through and characterization of atmospheric oceanic phenomena. The papers cover a broad range of topics, many of which were addressed at the 2023 Propagation Through and Characterization of Atmospheric Oceanic Phenomena (pcAOP) Topical Meeting at the Optica Imaging Congress in Boston, Massachusetts, 14-17 August 2023. These papers are supplemented by numerous examples of the current state of research in the field. This is the first pcAOP feature issue, with the intention to produce an issue on this topic every two years.

Propagation through and characterization of atmospheric and oceanic phenomena: introduction to the joint feature issue in Applied Optics and Journal of the Optical Society of America A.

This joint feature issue in Applied Optics and JOSA A collects articles focused on the topic of propagation through and characterization of atmospheric oceanic phenomena. The papers cover a broad range of topics, many of which were addressed at the 2023 Propagation Through and Characterization of Atmospheric Oceanic Phenomena (pcAOP) Topical Meeting at the Optica Imaging Congress in Boston, Massachusetts, 14-17 August 2023. These papers are supplemented by numerous examples of the current state of research in the field. This is the first pcAOP feature issue, with the intention to produce an issue on this topic every two years.

2022 JOSA A Emerging Researcher Best Paper Prize: editorial.

JOSA A Editor-in-Chief Olga Korotkova, Deputy Editor Markus Testorf, and the members of the 2022 Emerging Researcher Best Paper Prize Committee announce the recipient of the 2022 prize for the best paper published by an emerging researcher in the Journal.

Synchronous optical intensity and phase measurements to characterize Rayleigh-Bénard convection.

Propagation of a laser beam through the Rayleigh-Bénard (RB) convection is experimentally investigated using synchronous optical wavefront and intensity measurements. Experimental results characterize the turbulence strength and length scales, which are used to inform numerical wave optic simulations employing phase screens. Experimentally found parameters are the refractive index structure constant, mean flow rate, kinetic and thermal dissipation rates, Kolmogorov microscale, outer scale, and shape of the refractive index power spectrum using known models. Synchronization of the wavefront and intensity measurements provide statistics of each metric at the same instance in time, allowing for two methods of comparison with numerical simulations. Numerical simulations prove to be within agreement of experimental and published results. Synchronized measurements provided more insight to develop reliable propagation models. It is determined that the RB test bed is applicable for simulating realistic undersea environments.

Classifying beams carrying orbital angular momentum with machine learning: tutorial.

This tutorial discusses optical communication systems that propagate light carrying orbital angular momentum through random media and use machine learning (aka artificial intelligence) to classify the distorted images of the received alphabet symbols. We assume the reader is familiar with either optics or machine learning but is likely not an expert in both. We review select works on machine learning applications in various optics areas with a focus on beams that carry orbital angular momentum. We then discuss optical experimental design, including generating Laguerre-Gaussian beams, creating and characterizing optical turbulence, and engineering considerations when capturing the images at the receiver. We then provide an accessible primer on convolutional neural networks, a machine learning technique that has proved effective at image classification. We conclude with a set of best practices for the field and provide an example code and a benchmark dataset for researchers looking to try out these techniques.

Machine learning-aided classification of beams carrying orbital angular momentum propagated in highly turbid water: publisher's note.

This publisher's note corrects the name of an author of J. Opt. Soc. Am. A37, 1662 (2020)JOAOD60740-323210.1364/JOSAA.401153.

Machine learning-aided classification of beams carrying orbital angular momentum propagated in highly turbid water.

A set of laser beams carrying orbital angular momentum is designed with the objective of establishing an effective underwater communication link. Messages are constructed using unique Laguerre-Gauss beams, which can be combined to represent four bits of information. We report on the experimental results where the beams are transmitted through highly turbid water, reaching approximately 12 attenuation lengths. We measured the signal-to-noise ratio in each test scenario to provide characterization of the underwater environment. A convolutional neural network was developed to decode the received images with the objective of successfully classifying messages quickly. We demonstrate near-perfect classification in all scenarios, provided the training set includes some images taken under the same underwater conditions.

Designing laser beams carrying OAM for a high-performance underwater communication system.

We present a design methodology for creating a distinct laser beam set suitable for detection by using only the recorded intensity pattern. We consider four coherent Laguerre-Gaussian beams carrying orbital angular momentum (OAM) to form the basis for optical communication. The complex electric fields of the beams are superimposed to create 16 dissimilar intensity patterns. The presented beam set design method considers the beam generation hardware limitations and aims to minimize the correlation among the messages and maximize their intensity differences. After propagating the 16 messages through a water channel, we measured high correlation, intensity similarity, and R-squared values for the identical messages and low values for the different ones. Distinct clustering between the measurements for the matching messages and the rest allows us to set a threshold in the gap among the groupings and successfully classify the received images.

Generating dark and antidark beams using the genuine cross-spectral density function criterion.

In this work, we demonstrate how to generate dark and antidark beams-diffraction-free partially coherent sources-using the genuine cross-spectral density function criterion. These beams have been realized in prior work using the source's coherent-mode representation and by transforming a J0-Bessel correlated partially coherent source using a wavefront-folding interferometer. We generalize the traditional dark and antidark beams to produce higher-order sources, which have not been realized. We simulate the generation of these beams and compare the results to the corresponding theoretical predictions. The simulated results are found to be in excellent agreement with theory, thus validating our analysis. We discuss the pros and cons of our synthesis approach vis-à-vis the prior coherent modes work. Lastly, we conclude this paper with a brief summary, and a discussion of how to physically realize these beams and potential applications.

Capacitive displacement sensor for detecting planar submicrometer motion.

This paper describes the design of a very simple displacement sensor that measures the change in the position of an object by sensing the change in capacitance due to the movement of this object in the sensor fringing electric field. Two sensor geometries with small footprints were considered and several sensor variations were built and tested. At distances of approximately 0.5 µm and 30 µm, test results demonstrated that the sensors' resolution was in the order of tens of nanometers.

Design of a 1 DOF MEMS motion stage for a parallel plane geometry rheometer.

Rotational rheometers are used to measure paste properties, but the test would take too long to be useful for quality control (QC) on the job site. In this paper, a new type of rheometer is proposed based on a one degree of freedom (DOF) micro-electro-mechanical systems (MEMS)-based motion stage. Preliminary data will be presented to show the capability of the system to measure the viscoelastic properties of a paste. The parallel plate geometry rheometer consists of two plates, which move relative to each other to apply a strain to the material to be tested. From the stress measured and the strain applied, the rheological characteristics of the material can be calculated. The new device consists of an electrothermal actuator and a motion plate. For the rheological measurements, the device is designed to generate the shear stress up to 60 Pa and maintain its stiffness to less than 44 N/m. With these features, the device uses a square plate of 1.5 mm x 1.5 mm to provide enough area for a few micro-liter level volumes. The motion of the square plate is monitored by a capacitive sensor at the end of the oscillating plate which has a resolution of 1.06 µm. When a reference cementitious paste, Standard Reference Material (SRM)-2492, is placed between the oscillating plate of the presented motion stage and a fixed plate, the reduction in the displacement of the oscillating plate is monitored showing that the presented motion stage is reasonably designed to detect the response of the reference cementitious paste.

Probability density function estimation of laser light scintillation via Bayesian mixtures.

A method for probability density function (PDF) estimation using Bayesian mixtures of weighted gamma distributions, called the Dirichlet process gamma mixture model (DP-GaMM), is presented and applied to the analysis of a laser beam in turbulence. The problem is cast in a Bayesian setting, with the mixture model itself treated as random process. A stick-breaking interpretation of the Dirichlet process is employed as the prior distribution over the random mixture model. The number and underlying parameters of the gamma distribution mixture components as well as the associated mixture weights are learned directly from the data during model inference. A hybrid Metropolis-Hastings and Gibbs sampling parameter inference algorithm is developed and presented in its entirety. Results on several sets of controlled data are shown, and comparisons of PDF estimation fidelity are conducted with favorable results.

Probability density functions of power-in-bucket and power-in-fiber for an infrared laser beam propagating in the maritime environment.

Irradiance fluctuations of an infrared laser beam from a shore-to-ship data link ranging from 5.1 to 17.8 km are compared to lognormal (LN), gamma-gamma (GG) with aperture averaging, and gamma-Laguerre (GL) distributions. From our data analysis, the LN and GG probability density function (PDF) models were generally in good agreement in near-weak to moderate fluctuations. This was also true in moderate to strong fluctuations when the spatial coherence radius was smaller than the detector aperture size, with the exception of the 2.54 cm power-in-bucket (PIB) where the LN PDF model fit best. For moderate to strong fluctuations, the GG PDF model tended to outperform the LN PDF model when the spatial coherence radius was greater than the detector aperture size. Additionally, the GL PDF model had the best or next to best overall fit in all cases with the exception of the 2.54 cm PIB where the scintillation index was highest. The GL PDF model also appears to be robust for off-of-beam center laser beam applications.

Probability density function of the intensity of a laser beam propagating in the maritime environment.

A number of field experiments measuring the fluctuating intensity of a laser beam propagating along horizontal paths in the maritime environment is performed over sub-kilometer distances at the United States Naval Academy. Both above the ground and over the water links are explored. Two different detection schemes, one photographing the beam on a white board, and the other capturing the beam directly using a ccd sensor, gave consistent results. The probability density function (pdf) of the fluctuating intensity is reconstructed with the help of two theoretical models: the Gamma-Gamma and the Gamma-Laguerre, and compared with the intensity's histograms. It is found that the on-ground experimental results are in good agreement with theoretical predictions. The results obtained above the water paths lead to appreciable discrepancies, especially in the case of the Gamma-Gamma model. These discrepancies are attributed to the presence of the various scatterers along the path of the beam, such as water droplets, aerosols and other airborne particles. Our paper's main contribution is providing a methodology for computing the pdf function of the laser beam intensity in the maritime environment using field measurements.