Optical Turbulence Research Articles

First field measurements of optical turbulence near the ground with a newly developed fine-wire thermometer

First results of optical turbulence field measurements collected with a newly developed fine-wire temperature sensing system are presented and discussed. The centerpiece of the sensing system is an array of fine-wire platinum resistance thermometers. The active fine wire in each sensor element has a diameter of 0.64 μm and a length between 0.5 and 1 mm. The sampling rate is 44.1 kHz, and the noise level is 1 mK for a bandwidth of 10 kHz. Data were recorded while the car onto which the sensors were mounted was traveling at a speed of about 40 mph, or 18 m s . Estimates of the temperature structure function are compared against the classical Obukhov-Corrsin theory, which predicts power-law asymptotes with in the viscous-diffusive range and in the inertial-convective range. For the pair of separations cm and cm, we observed . The frequency spectrum follows the theoretically predicted power law in the inertial-convective subrange. The ‘Hill bump’ in the transition regime between the inertial-convective and viscous-diffusive subranges is visible.

Symmetry transformations of the vortex field statistics in optical turbulence

Symmetry transformations of the vortex field statistics in optical turbulence

A GAUGE-INVARIANT LAGRANGIAN DETERMINED BY THE <i>n</i>-POINT PROBABILITY DENSITY FUNCTION OF VORTICITY FIELD OF THE WAVE OPTICAL TURBULENCE

The geometry methods for Yang–Mills fields of the gauge transformations are applied to finding an invariant Lagrangian in fiber bundle of the configuration \(2d\) space \(X\) of the turbulent flow defined by the \(n\)-point probability density function \({{f}_{n}}\) (PDF). The two-dimensional wave optical turbulence is considered in the case of the inverse cascade of energy. The n-point PDF of the vorticity field satisfies the \({{f}_{n}}\)-equation from the Landgren–Monin–Novikov (LMN) hierarchy. The basic result reads: we construct the Lagrangian which is invariant under a subgroup \(H \subset G\) – the group of the gauge transformations in fiber bundles of the space X and the conserved currents.

A Real-Time Measurement System for Atmospheric Turbulence Intensity and Distribution Based on the GLAO System

Measuring the intensity and distribution of atmospheric optical turbulence at large-aperture astronomical telescope sites is crucial to optimizing turbulence correction for different layers. A real-time measurement of turbulence distribution in large-aperture telescopes would be valuable for the parameter optimization of adaptive optics (AO) systems, especially for large field-of-view AO systems such as multi-conjugate adaptive optics (MCAO) and ground-layer adaptive optics (GLAO). Based on the GLAO system of NVST at FSO, a real-time measurement system was deployed to assess the site’s atmospheric turbulence intensity and distribution. This system is, to our knowledge, the first real-time turbulence parameter measurement system in the world with an AO system. We adopt pseudo-open loop methods to restore the turbulence information from the close-loop data of GLAO and measure the turbulence strength and distribution. Multiple subaperture pairs are used instead of a pair of subapertures for fitting calculation to increase the measurement accuracy. Two conventional measurement algorithms, SLODAR and S-DIMM+, are compared with the data from the open-source simulator SOAPY, to cross-verify the correctness of our calculation based on the data process of pseudo-open loop data and multiple subaperture pairs. The simulation results show that for two layers’ turbulence input, approximately 93% of the turbulence is correctly detected with the SLODAR method and the given parameters of wavefront sensors and correctors, while the S-DIMM+ is 87%. Real-time measurements of atmospheric turbulence at the NVST site were carried out on 28 May 2023. The observation results indicated that approximately 80% of the turbulence was located below an altitude of 2000 m; only a few appear in the upper height.

Continuous daytime and nighttime forecast of atmospheric optical turbulence from numerical weather prediction models.

Future satellite-to-ground optical communication systems will benefit from accurate forecasts of atmospheric optical turbulence; namely for site selection, for the routing and the operation of optical links, and for the design of optical communication terminals. This work presents a numerical approach based on the Weather Research and Forecasting software that enables continuous forecast of the refractive index structure parameter, C n2, vertical profiles. Two different C n2 models are presented and compared. One is based on monitoring the turbulent kinetic energy, while the other is a hybrid model using the Tatarskii equation to depict the free atmosphere region, and the Monin-Obukhov similarity theory for describing the boundary layer. The validity of both models is assessed by using thermosonde measurements from the Terrain-induced Rotor Experiment campaign, and from day and night measurements of the coherence length collected during a six-day campaign at Paranal observatory by a Shack-Hartmann Image Motion Monitor. The novelty of this work is the ability of the presented approach to continuously predict optical turbulence both during daytime and nighttime, and its validation with measurements in day and night conditions.

A global turbulence model shows excellent atmospheric optical turbulence conditions over the Ethiopian plateau during non-rainy season

ABSTRACT A worldwide search is currently being conducted to determine the most appropriate sites for the next generation of large optical and infrared telescopes. Here, we report a global map of atmospheric optical turbulence-associated parameter (atmospheric coherence length) based on the fifth generation of European Centre for Medium Range Weather Forecasts re-analysis data set and results for atmospheric coherence lengths at European Southern Observatory and Tibetan Plateau locations (all at mid-latitudes). These confirm the accuracy of the global atmospheric optical turbulence model, but also the simulation result reveals that an excellent atmospheric calm site exist at the Ethiopian Plateau (at a latitude of ∼10°N) outside of the rainy season. The Ethiopian Plateau is the highest plateau in Africa, known as the ‘Roof of Africa’, with an average elevation of over 2500 m, and thus potentially provides good opportunities for astronomy and astrophysics. The median atmospheric coherence length at the Ethiopian Plateau was 17.7 cm and approximately 75 per cent of the time above 15.6 cm for dry conditions, indicating a very calm atmosphere. Although favourable atmospheric turbulence conditions at the Ethiopian Plateau were found from the global turbulence model, due to the complete lack of infrastructure it has never been visited, meaning that additional validation experiments are required.

Modeling and performance analysis of underwater wireless optical absorption, scattering, and turbulence channels employing Monte Carlo-multiple phase screens.

The absorption, scattering, and turbulence effects have a significant impact on the performance of underwater wireless optical communication (UWOC). Therefore, it is crucial to consider seawater's optical parameters comprehensively when designing UWOC systems. So far, most studies on the UWOC channel have separately modeled the absorption and scattering, and turbulence of seawater, and furthermore, the continuous phase perturbations caused by turbulence are neglected to simplify the model when modeling turbulence channels. Hence, this paper simultaneously considers the absorption, scattering, and turbulence effects of seawater and proposes a UWOC channel modeling method that combines Monte Carlo simulation with multiple phase screen approaches. Subsequently, the impacts of different systems and channel conditions on system performance are explored, and simulation results indicate that as the turbidities and turbulence intensities of the seawater increase, the probability density function of received light signal intensity becomes more dispersed. The turbulence introduces an increase in path loss of approximately 5dB compared to its absence. Furthermore, the channel impulse response (CIR) is obtained, where the turbulence effects cause a 50% decrease in the CIR peak and the noticeable temporal spread.

Astronomical seeing and ground-level optical turbulence at Delingha observatory on the northern Tibetan Plateau

ABSTRACT This paper presents a comprehensive site survey of the Delingha site on the northern Tibetan Plateau from 2012 to 2014. In this campaign, we investigated 24 h continuous astronomical seeing, meteorological properties, and $C_{n}^{2}$ in the ground layer (GL). The results show that the median seeing is 3.46 arcsec during the day and 1.80 arcsec during the night. The best nighttime seeing occurs in summer (1.66 arcsec), while the worst occurs in autumn (1.96 arcsec). Seeing exhibits obvious diurnal behaviour, with the worst seeing occurring around mid-day (11:00 to 14:00, Beijing time), and the best seeing just before sunset (18:00 to 20:00, Beijing time). Moreover, the Delingha site has good meteorological properties for astronomical observations during the measurement period, especially the low median wind speed (2.8 m s−1) and great temperature inversion (day: −0.3 K, night: 0.6 K). As for the vertical distribution of $C_{n}^{2}$, the exponential h−0.46 dependence of $C_{n}^{2}$ varying with height in the GL is also obtained, and its power index is significantly related to the seasons. Furthermore, we calculated the contribution of optical turbulence in the GL to the whole atmosphere. Turbulence within the GL contributes significantly in summer, and its contribution can reach more than 35 per cent. Finally, we present the complete dependence analysis of seeing on meteorological parameters at the Delingha site. The results show that the best seeing tends to occur when the temperature inversion is sufficiently large, but the dependence of seeing on wind speed is not significant.

Π-ML: a dimensional analysis-based machine learning parameterization of optical turbulence in the atmospheric surface layer.

Turbulent fluctuations of the atmospheric refraction index, so-called optical turbulence, can significantly distort propagating laser beams. Therefore, modeling the strength of these fluctuations (C n2) is highly relevant for the successful development and deployment of future free-space optical communication links. In this Letter, we propose a physics-informed machine learning (ML) methodology, Π-ML, based on dimensional analysis and gradient boosting to estimate C n2. Through a systematic feature importance analysis, we identify the normalized variance of potential temperature as the dominating feature for predicting C n2. For statistical robustness, we train an ensemble of models which yields high performance on the out-of-sample data of R2 = 0.958 ± 0.001.

Line-of-sight optical Dome Turbulence Monitor

ABSTRACT Optical turbulence in the enclosure of a ground-based telescope can be a major contributor to the total optical turbulence strength and can therefore limit the precision of astronomical observations, in terms of angular resolution, or signal to noise ratio, depending on the instrumentation used. Here we propose a new Dome Turbulence Monitor (DTM) technique. This DTM is based on the well known Scintillation Detection And Ranging (SCIDAR) concept with a few major differences. By designing the instrument specifically for the dome turbulence, we can use a small (<0.2 m telescope), and observe single bright stars (as opposed to the SCIDAR using double stars). This enables a dedicated instrument with enough targets to operate continuously. Operationally, the DTM could be mounted somewhere on the main astronomical telescope and track stars that are visible through the dome aperture. By measuring through the dome aperture we obtain an optical measure of the strength of the turbulence along a similar line of sight as the main telescope itself. We demonstrate the new technique through numerical Monte Carlo modelling and present results from a proof-of-concept demonstration at the European Space Agency Optical Ground Station on Tenerife, Spain.

Performance Estimation of Solar Imagery Using Different Types of Atmospheric Turbulence Models

This paper proposed several approaches for estimating the optical turbulence of the Earth’s atmosphere and their effect on solar images’ resolution using ground-based telescopes based on von Kárman, Kolmogorov, and modified von Kárman PSDs models. The results showed a strong correlation coefficient for the modified von Kármán model of atmospheric representation. As can be seen in the case where solar adaptive optics have been properly designed, they typically decrease aberration considerably and provide greatly improved imagery.

Anisoplanatic optical turbulence simulation for near-continuous Cn2 profiles without wave propagation

Anisoplanatic optical turbulence simulation for near-continuous Cn2 profiles without wave propagation

Effect of data spatial vertical resolution on the estimation of vertical profiles of the refractive index structure constant.

The vertical profile of optical turbulence is a key factor in the performance design of astronomical telescopes and adaptive optics instruments. As site-testing campaigns are extremely expensive, the selection of appropriate spatial resolution data and estimation methods is extremely important. This study investigated the effect of using different methods (Dewan, HMNSP99, Thorpe method) to estimate the refractive index structure constant (C n2) using different resolution data (5 m, 25 m, ERA5 data) in Huaihua, Hunan. Compared with Dewan, HMNSP99 for estimating C n2 using 5 m and 25 m resolution data, the Thorpe method almost always shows the best performance, with RXY above 0.75 and lower RMSE and MRE between estimated and measured C n2. The results of C n2 estimation using HMNSP99 at different resolution data varied widely, indicating that HMNSP99 is more sensitive to the data resolution and the temperature gradient is more sensitive to the resolution. Using ERA5 data, the two methods of estimating C n2 using Dewan and HMNSP99 have close results. It indicates that the wind shear is the main factor when the spatial resolution of the data is reduced to a certain degree, and the contribution of temperature gradient is small in the high altitude turbulence.

An effective semilocal model for wave turbulence in two-dimensional nonlinear optics

The statistical evolution of ensembles of random, weakly interacting waves is governed by wave kinetic equations (WKEs). To simplify the analysis, one frequently works with reduced differential models of the wave kinetics. However, the conditions for deriving such reduced models are seldom justified self-consistently. Here, we derive a reduced model for the wave kinetics of the Schrödinger–Helmholtz equations in two spatial dimensions, which constitute a model for the dynamics of light in a spatially nonlocal, nonlinear optical medium. This model has the property of sharply localizing the frequencies of the interacting waves into two pairs, allowing for a rigorous and self-consistent derivation of what we term the semilocal approximation model (SLAM) of the WKE. Using the SLAM, we study the stationary spectra of Schrödinger–Helmholtz wave turbulence, and characterize the spectra that carry energy downscale, and waveaction upscale, in a forced-dissipated setup. The latter involves a nonlocal transfer of waveaction, in which waves at the forcing scale mediate the interactions of waves at every larger scale. This is in contrast to the energy cascade, which involves local scale-by-scale interactions, familiar from other wave turbulent systems and from classical hydrodynamical turbulence.

Propagating beams carrying orbital angular momentum through simulated optical turbulence generated by Rayleigh–Bénard natural convection

Numerical simulations of Rayleigh–Bénard (RB) convective flow are performed to determine the optical and mechanical turbulence properties and resulting index of refraction field in order to study the propagation characteristics of a laser beam carrying orbital angular momentum. The simulations are carried out in air using a computational fluid dynamics package which solves the Navier-Stokes equations. The computational domain is 0.1 m × 0.5 m × 0.5 m with a temperature difference of 1°K maintained between the top and bottom plate. The simulated temperature field is then converted into refractive index values. To study light propagation through the turbulent volume the split-step screen method is employed with screens at 0.025 m distance from each other along the propagation path which ranges from 0.5 m to 2.5 m. The structure of the phase screens, their spatio-temporal correlation with respect to up/down drafts, and phase changes across regions of interest are discussed. It was observed as the propagation distance increased, the orbital angular momentum carrying Laguerre–Gaussian beams wandered and the beam phase singularity distorted thus impacting the light intensity distribution. In addition, it was found that higher topological charge and order of Laguerre polynomial result in increased distortion of the beam vortex.

Hybrid optical turbulence models using machine-learning and local measurements.

Accurate prediction of atmospheric optical turbulence in localized environments is essential for estimating the performance of free-space optical systems. Macro-meteorological models developed to predict turbulent effects in one environment may fail when applied in new environments. However, existing macro-meteorological models are expected to offer some predictive power. Building a new model from locally measured macro-meteorology and scintillometer readings can require significant time and resources, as well as a large number of observations. These challenges motivate the development of a machine-learning informed hybrid model framework. By combining a baseline macro-meteorological model with local observations, hybrid models were trained to improve upon the predictive power of each baseline model. Comparisons between the performance of the hybrid models, selected baseline macro-meteorological models, and machine-learning models trained only on local observations, highlight potential use cases for the hybrid model framework when local data are expensive to collect. Both the hybrid and data-only models were trained using the gradient boosted decision tree architecture with a variable number of in situ meteorological observations. The hybrid and data-only models were found to outperform three baseline macro-meteorological models, even for low numbers of observations, in some cases as little as one day. For the first baseline macro-meteorological model investigated, the hybrid model achieves an estimated 29% reduction in the mean absolute error using only one day-equivalent of observation, growing to 41% after only two days, and 68% after 180days-equivalent training data. The data-only model generally showed similar, but slightly lower performance, as compared to the hybrid model. Notably, the hybrid model's performance advantage over the data-only model dropped below 2% near the 24 days-equivalent observation mark and trended towards 0% thereafter. The number of days-equivalent training data required by both the hybrid model and the data-only model is potentially indicative of the seasonal variation in the local microclimate and its propagation environment.

Optical turbulence forecasts at short time-scales using an autoregressive method at the Very Large Telescope

ABSTRACT In this study we demonstrate that we can provide forecasts of all the main astroclimatic parameters (seeing, wavefront coherence time, isoplanatic angle, and ground-layer fraction) on time-scales of 1 and 2 h (the most critical ones for the service mode) with a root-mean-square error (RMSE) that is smaller than or, at worst, comparable to the instrumental uncertainty (i.e. the standard deviation between instrument estimates). The seeing RMSE is 0.08 arcsec. Results are achieved thank to the use of the autoregressive method (AR) in our automatic forecast system and the study is applied to the Very Large Telescope (VLT). The AR method is a hybrid method taking into account forecasts of a non-hydrostatical mesoscale model jointly with real-time observations made in situ. We demonstrate that the AR method allows an improvement in forecast performance of roughly a factor of three or more with respect to the standard forecasts at a long time-scale (beginning of the afternoon for the coming night), depending on the parameter and the time-scale (1 and 2 h). The AR method also allows roughly a factor of two gain with respect to prediction by persistence. We also show that the AR method provides significantly better performance than a random-forest machine-learning algorithm. An extended analysis of the AR performance is provided following different strategies. Results achieved in this study are therefore very promising and tell us that we can provide real assistance to the service mode of the VLT instrumentation supported by adaptive optics systems.

Supervised Machine Learning for Refractive Index Structure Parameter Modeling

The Hellenic Naval Academy (HNA) reports the latest results from a medium-range, near-maritime, free-space laser-communications-testing facility, between the lighthouse of Psitalia Island and the academy’s laboratory building. The FSO link is established within the premises of Piraeus port, with a path length of 2958 m and an average altitude of 35 m, mainly above water. Recently, the facility was upgraded through the addition of a BLS450 scintillometer, which is co-located with the MRV TS5000/155 FSO system and a WS-2000 weather station. This paper presents the preliminary optical turbulence measurements, collected from 24 to 31 of May 2022, alongside the macroscopic meteorological parameters. Four machine-learning algorithms (random forest (RF), gradient boosting regressor (GBR), single layer (ANN), and deep neural network (DNN)) were utilized for refractive-index-structural-parameter regression modeling. Additionally, another DNN was used to classify the strength level of the optical turbulence, as either strong or weak. The results showed very good prediction accuracy for all the models. Specifically, the ANN algorithm resulted in an R-squared of 0.896 and a mean square error (MSE) of 0.0834; the RF algorithm also gave a highly acceptable R-squared of 0.865 and a root mean square error (RMSE) of 0.241. The Gradient Boosting Regressor (GBR) resulted in an R-squared of 0.851 and a RMSE of 0.252 and, finally, the DNN algorithm resulted in an R-squared of 0.79 and a RMSE of 0.088. The DNN-turbulence-strength-classification model exhibited a very acceptable classification performance, given the highly variability of our target value (Cn2), since we observed a predictive accuracy of 87% with the model.

Simulating Atmospheric Characteristics and Daytime Astronomical Seeing Using Weather Research and Forecasting Model

The present study is aimed at the development of a novel empirical base for application to ground-based astronomical telescopes. A Weather Research and Forecasting (WRF) model is used for description of atmospheric flow structure with a high spatial resolution within the Baikal Astrophysical Observatory (BAO) region. Mesoscale vortex structures are found within the atmospheric boundary layer, which affect the quality of astronomical images. The results of simulations show that upward air motions in the lower atmosphere are suppressed both above the cold surface of Lake Baikal and inside mesoscale eddy structures. A model of the outer scale of turbulence for BAO is developed. In this work, we consider the seeing parameter that represents the full width at half-maximum of the point spread function. Optical turbulence profiles are obtained and daytime variations of seeing are estimated. Vertical profiles of optical turbulence are optimized taking into account data from direct optical observations of solar images.

SIMO-Underwater Visible Light Communication (UVLC) system

The advent of visible light communication (VLC) towards 5G and beyond (5GB) networks opened new doors to unveil the mysteries of unguided mediums such as ocean. The varying physicochemical properties of water introduces the underwater optical turbulence (UOT). The UOT of UVLC link is modelled as unified Gamma-Gamma (GG) distribution fading under moderate-to-strong turbulence channel conditions as well as the misalignment of transceivers following exponential fading are included and studied. This study also contains the effect of UOT which is characterized by multiple water layers within the Monte Carlo simulation framework. The end-to-end (E2E) performances of a Single-Input and Multi-Output (SIMO) underwater VLC (UVLC) system is in consideration of Intensity-Modulation/Direct-Detection (IM/DD) technique which is obtained to fulfill the current communication requirements in hostile aqueous channels. More specifically, the probability distribution function (PDF) and cumulative distribution function (CDF) are derived to obtain the E2E performance metrics of the SIMO-UVLC system in terms of Meijer-G function. Consequently, novel closed-form expressions for average bit-error-rate (ABER) and outage probability of the system are formulated. Finally, the numerical and simulation results are obtained based on the experimental data in mixed water layers of the oceanic environments, and analytically verified through the Monte Carlo simulation approach in harsh channel conditions.