Atmospheric Turbulence Research Articles

Practical Performance Analysis of MDI-QKD with Orbital Angular Momentum on UAV Relay Platform.

The integration of terrestrial- and satellite-based quantum key distribution (QKD) experiments has markedly advanced global-scale quantum networks, showcasing the growing maturity of quantum technologies. Notably, the use of unmanned aerial vehicles (UAVs) as relay nodes has emerged as a promising method to overcome the inherent limitations of fiber-based and low-Earth orbit (LEO) satellite connections. This paper introduces a protocol for measurement-device-independent QKD (MDI-QKD) using photon orbital angular momentum (OAM) encoding, with UAVs as relay platforms. Leveraging UAV mobility, the protocol establishes a secure and efficient link, mitigating threats from untrusted UAVs. Photon OAM encoding addresses reference frame alignment issues exacerbated by UAV jitter. A comprehensive analysis of atmospheric turbulence, state-dependent diffraction (SDD), weather visibility, and pointing errors on free-space OAM-state transmission systems was conducted. This analysis elucidates the relationship between the key generation rate and propagation distance for the proposed protocol. Results indicate that considering SDD significantly decreases the key rate, halving previous data results. Furthermore, the study identifies a maximum channel loss capacity of 26 dB for the UAV relay platform. This result is pivotal in setting realistic parameters for the deployment of UAV-based quantum communications and lays the foundation for practical implementation strategies in the field.

Hollow Gaussian Beam Based Experimental Investigation on Echo Measurements Under Atmospheric Turbulence and Central Obstruction

Hollow Gaussian Beam Based Experimental Investigation on Echo Measurements Under Atmospheric Turbulence and Central Obstruction

Continuous-wave degenerate cavity laser for optical imaging in scattering media.

Lasers play a significant role in optical communication, medical, and scientific research, owing to their high brightness and high coherence. However, the high spatial coherence will lead to specific challenges, such as speckle noise in imaging and wavefront distortion during propagation through scattering media. Here, a continuous-wave (cw) degenerate cavity laser (DCL) with low spatial coherence is demonstrated with efficient suppression of the thermal lensing effect from the gain crystal. Experimentally, a cw degenerate laser output with about 2000 transverse modes corresponding to a speckle contrast of about 0.0224 is achieved. This laser can be used for speckle reduction and is robust against atmospheric turbulence, which may find applications in the field of laser imaging technology and illumination.

Perfect correlation vortices.

We introduce perfect correlation vortices and show that the degree of coherence of any such vortex at the source is nearly statistically homogeneous and independent of the topological charge of the vortex. We demonstrate that while slowly diffracting in free space, perfect correlation vortices maintain their "perfect" vortex structure; they are capable of preserving said structure even in strong atmospheric turbulence. Structural resilience to diffraction and turbulence sets the discovered perfect vortices apart from their coherent cousins and makes them suitable for free-space optical communications.

Differential image motion in astrometric observations with very large seeing-limited telescopes

We investigate how to quantitatively model the observed differential image motion (DIM) in relative astrometric observations. As a test bed we used differential astrometric observations from the FORS2 camera of the Very Large Telescope (VLT) obtained during 2010--2019 under several programs of observations of southern brown dwarfs . The measured image motion was compared to models that decompose atmospheric turbulence in frequency space and translate the vertical turbulence profile into DIM amplitude. This approach accounts for the spatial filtering by the telescope's entrance pupil and the observation parameters (field size, zenith angle, reference star brightness and distribution, and exposure time), and it aggregates that information into a newly defined metric integral term. We demonstrate excellent agreement (within 1<!PCT!>) between the model parameters derived from the DIM variance and determined by the observations. For a 30 s exposure of a typical 1 field close to the Galactic plane, image motion limits astrometric precision to sim 60 mu as when sixth-order transformation polynomial is applicable. We confirm that the measured image motion variance is well described by Kolmogorov-type turbulence with exponent 11/3 dependence on the field size at effective altitudes of 16--18 km, where the best part of the DIM is generated. Extrapolation to observations with extremely large telescopes enables the estimation of the astrometric precision limit for seeing-limited observations of sim 5 mu as, which has a variety of exciting scientific applications.

Performance analysis of the dual-hop mixed RF/UWOC system with fog channel and turbulence based on diversity

ABSTRACT In this paper, the performance of a dual-hop mixed radio frequency (RF)/underwater wireless optical communication (UWOC) system with amplifying and forwarding (AF) relaying is investigated. The diversity combining technology were combined with unifying Fisher-Snedecor ( F ), extended generalized- K (EGK), and α − μ distribution for atmospheric turbulence in foggy conditions to analyze the probability density function (PDF) of RF links. The UWOC link experiences mixed exponential generalized gamma (EGG) fading. By utilizing diversity combination methods and considering the statistical effects of atmospheric turbulence, random fog, and underwater turbulence, we derive the expression for the PDF of the RF/UWOC system. In addition, the tight asymptotic expression for the outage probability and average bit error rate under high signal-to-noise ratio (SNR) is provided. The analytical expressions are verified by Monte Carlo method, and the effects of channel number on RF/UWOC system performance under various atmospheric, underwater and weather conditions are demonstrated.

Free Space Optical Communication and its Implementation Using Diffractive Optical Elements Using Artificial Intelligence (AI)

Background: Free Space Optics (FSO) is a wireless data transmission method for infrastructure that uses laser beam energy to transmit information waves through the atmosphere. Furthermore, due to its high bandwidth potential and simple deployment, FSO has garnered considerable interest. However, atmospheric turbulence and misalignment present obstacles to establishing dependable and effective FSO links. Objective: For systems varying from space invariant to totally space variant, the optimal design of free-space optical connectivity systems using diffractive optics is found from an engineering perspective. Parameters such as the light's wavelength, the system's total number of optical sources and detectors, their sizes, and their spacing are used to determine the system's volume. Another important parameter is the diffractive lens's f-number. Diffraction Optical Elements (DOEs) have emerged as a promising means of addressing these difficulties. Also, the patent related to automated honey beehive box gives the insight of its monitoring system. Methods:: This paper provides an overview of the implementation and advancements of FSO systems utilizing DOEs, including the fundamental principles, design considerations, and performance improvements. The study discusses the basics of diffraction and the role of DOEs in FSO systems. It explores the diffraction grating equation and the Huygens-Fresnel principle to understand wave propagation and interference phenomena. Design considerations for FSO systems equipped with DOEs are discussed, including the selection of appropriate DOEs and evaluation of performance benefits. The study also investigates the application of AI methods, such as machine learning and deep learning, in optimizing FSO systems with DOEs. Results: A thorough overview of Free Space Optics (FSO) systems utilizing Diffraction Optical Elements (DOEs) is given in this review study. It examines diffraction theory and DOE use in FSO, emphasizing their potential for beam forming, beam steering, and adaptive optics. The study examines FSO with DOE design concerns, performance improvements, applications, and future approaches. FSO systems may overcome problems with air turbulence, misalignment, and fading by using the characteristics of DOEs, opening the door for dependable and effective wireless communication. Conclusion: In conclusion, the effect of DOEs on BER efficiency is also modified by the obscuration ratio. Transmission power is increased when more DOEs are used by an amount defined by their obscuration ratios. Additionally, because of the increased power complement in these systems, the effect of DOEs is more pronounced. The integration of AI further enhances FSO capabilities by providing adaptive optimization, fault detection, predictive maintenance, and improved security. Future research directions may include exploring advanced AI techniques and conducting practical implementations of FSO systems with DOEs for various applications, particularly in Internet of Things (IoT) scenarios.

PAM4-modulated 2-micron band for enhanced indoor optical communications: experimental evaluation

This research explores the application of PAM4 modulation to optical signals in the 2-μm wavelength band for indoor optical communication. Experiments conducted in a simulated atmospheric turbulence environment demonstrated a BER of 10−5 for the 2-μm laser carrier with PAM4, surpassing the forward error correction threshold. Power loss comparisons to a back-to-back setup showed minimal degradation under various turbulence levels, with losses of 1.80 dB, 1.91 dB, 2.09 dB, and 2.55 dB for non-turbulent, weak-turbulent, moderate-turbulent, and strong-turbulent conditions, respectively. The system's sensitivity was measured at -7.69 dBm, emphasizing its effectiveness in detecting low-power signals. OptiSystem simulations indicated that PAM4 necessitates a higher optical OSNR than NRZ, suggesting the necessity for sophisticated signal processing techniques for systems operating in the 2-μm band. The study's results contribute to the body of knowledge on high-bandwidth optical communication and suggest future research avenues aimed at enhancing system performance while maintaining cost-effectiveness.

Experimental analysis of reducing outage probability using deep interleaving for long‐distance free space optical systems

AbstractFree space optical communication (FSO) has become a popular research direction due to its high bandwidth, easy deployment, and inherent security. Its channel state is unstable because of atmospheric environment, especially in long‐distance ground transmission system. Interleaving combined with forward error correction coding (FEC) have been utilised to improve the stability of system. However, there is little detailed experimental results of deep interleaving combined with FEC under different atmospheric turbulence intensity over long‐distance FSO system. A deep interleaving with FEC method was designed and implemented on a 7 km long online experiment. The performance of different depth interleaving is analysed under weak and strong atmospheric turbulence state. The experiment results show that deep interleaving performs better under weak turbulence for the larger correlation factor of the channel and the outage probability of the system with deep interleaving can be greatly reduced.

Atmospheric Turbulence Phase Reconstruction via Deep Learning Wavefront Sensing.

The fast and accurate reconstruction of the turbulence phase is crucial for compensating atmospheric disturbances in free-space coherent optical communication. Traditional methods suffer from slow convergence and inadequate phase reconstruction accuracy. This paper introduces a deep learning-based approach for atmospheric turbulence phase reconstruction, utilizing light intensity images affected by turbulence as the basis for feature extraction. The method employs extensive light intensity-phase samples across varying turbulence intensities for training, enabling phase reconstruction from light intensity images. The trained U-Net model reconstructs phases for strong, medium, and weak turbulence with an average processing time of 0.14 s. Simulation outcomes indicate an average loss function value of 0.00027 post-convergence, with a mean squared error of 0.0003 for individual turbulence reconstructions. Experimental validation yields a mean square error of 0.0007 for single turbulence reconstruction. The proposed method demonstrates rapid convergence, robust performance, and strong generalization, offering a novel solution for atmospheric disturbance correction in free-space coherent optical communication.

End-to-end simulations of photonic phase correctors for adaptive optics systems

Optical beams and starlight distorted by atmospheric turbulence can be corrected with adaptive optics systems to enable efficient coupling into single-mode fibers. Deformable mirrors, used to flatten the wavefront in astronomical telescopes, are costly, sensitive, and complex mechanical components that require careful calibration to enable high-quality imaging in astronomy, microscopy, and vision science. They are also impractical to deploy in large numbers for non-imaging applications like free-space optical communication. Here, we propose a photonic integrated circuit capable of spatially sampling the wavefront collected by the telescope and co-phasing the subapertures to maximize the flux delivered to an output single-mode fiber as the integrated photonic implementation of a deformable mirror. We present the results of end-to-end simulations to quantify the performance of the proposed photonic solution under varying atmospheric conditions toward realizing an adaptive optics system without a deformable mirror for free-space optical receivers.

Fisher information of orbital angular momentum quantum states in atmospheric turbulence

Free-space optical communication based on orbital angular momentum (OAM) offers advantages such as high security, large information capacity, and high-speed transmission. However, turbulence can induce random perturbations to the wavefront, thereby affecting communication performance. Hence, accurately measuring turbulence intensity is crucial. We delve into the quantum Fisher information (QFI) of the spatial coherence length, a pivotal parameter in atmospheric turbulence. Within the framework of free-space optical channels, we conduct a comprehensive analysis of the QFI in models encompassing both single and biphoton systems. As photons propagate through free space, the QFI regarding turbulence parameter initially increases and then decreases, due to the coupling and decoherence between the photons and turbulence. Increasing the number of OAM modes can significantly enhance the QFI regarding turbulence parameters. We considered situations closer to practical preparation, our results indicate that the impact of entanglement on estimation precision depends on the purity of the prepared entangled state. Moreover, we discuss and compare the variations in the QFI of various parameters upon considering backward scattering (BS). We believe our work is the first theoretical attempt towards the exploration of estimating the turbulence parameter via QFI.

Comparing thin and volume regimes of analog holograms for wavefront sensing

Two analog holographic wavefront sensors, for measurement of defocus, have been fabricated as both thin and volume phase transmission holograms in a self-developing photopolymer. This represents the first reported direct comparison of hologram regimes when designed for wavefront sensing. An analysis of the effect of crosstalk in the presence of one other aberration mode (astigmatism X (0/90°), coma X (horizontal), and primary spherical aberration) was carried out with each version of the sensor. The performance of thin and volume analog holographic wavefront sensors was characterized under emulated conditions associated with moderate atmospheric turbulence.

Deep-learning-based recognition of composite vortex beams through long-distance and moderate-to-strong atmospheric turbulence

Deep-learning-based recognition of composite vortex beams through long-distance and moderate-to-strong atmospheric turbulence

Outage probability minimization by optimal beamwidth selection for UAV-to-HAP FSO links under pointing inaccuracies

The design of a free-space optical (FSO) link between an unmanned aerial vehicle (UAV) and a high-altitude platform (HAP) in the practical scenario of generalized pointing errors (PE) and beam wandering (BWAN) is addressed. We propose to select appropriately the system parameters such as optical beamwidth at the UAV and its flight altitude so as to minimize the outage probability. First, we characterize the channel statistics by taking into account the joint influence of attenuation loss, weak atmospheric turbulence and generalized PE particularly impaired by BWAN. Second, we formulate the closed-form expressions for outage probability, where we also derive an asymptotic expression at high signal-to-noise ratios (SNR)s. Third, we derive the optimum beamwidth at the UAV leading to the instantaneous minimum outage probability under generalized PE and BWAN. Finally, we address the optimal flight altitude of the UAV to avoid strong turbulence in order to ensure efficient data transmission. Our simulation results validate both the effectiveness and the accuracy of the derived asymptotic outage probability and the adequate choice of beamwidth and flight altitude to minimize the average outage performance. For instance, our results show that at an SNR of 20 dBm, the link availability is increased from 20% (with nominal beamwidth) to more than 70% by adopting the proposed beamwidth optimization.

Analysis of speckle-beacon size impact on wavefront sensing and closed-loop control in deep turbulence conditions

The impact of the laser beacon size on the performance of an ideal phase-conjugation-type adaptive optics (AO) system is analyzed using wave-optics-based numerical simulation. The analysis includes wavefront aberration sensing and closed-loop control for laser beam propagation both in vacuum and in distributed (volume) atmospheric turbulence with the beacon beam scattering off a flat extended target with Lambertian surface roughness. For mitigation of the impact of target-induced speckle effects on the performance of AO systems, speckle-average wavefront sensing and control approaches are introduced and analyzed. The results demonstrate that proposed speckle-average phase conjugation control algorithms enable partial mitigation of turbulence-induced aberrations in presence of strong speckle modulations.

A Partial Near-infrared Guide Star Catalog for Thirty Meter Telescope Operations

At first light, the Thirty Meter Telescope (TMT) near-infrared (NIR) instruments will be fed by a multiconjugate adaptive optics instrument known as the Narrow Field Infrared Adaptive Optics System (NFIRAOS). NFIRAOS will use six laser guide stars to sense atmospheric turbulence in a volume corresponding to a field of view of 2′, but natural guide stars (NGSs) will be required to sense tip/tilt and focus. To achieve high sky coverage (50% at the north Galactic pole), the NFIRAOS client instruments use NIR on-instrument wave front sensors that take advantage of the sharpening of the stars by NFIRAOS. A catalog of guide stars with NIR magnitudes as faint as 22 mag in the J band (Vega system), covering the TMT-observable sky, will be a critical resource for the efficient operation of NFIRAOS, and no such catalog currently exists. Hence, it is essential to develop such a catalog by computing the expected NIR magnitudes of stellar sources identified in deep optical sky surveys using their optical magnitudes. This paper discusses the generation of a partial NIR Guide Star Catalog (IRGSC), similar to the final IRGSC for TMT operations. The partial catalog is generated by applying stellar atmospheric models to the optical data of stellar sources from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) optical data and then computing their expected NIR magnitudes. We validated the computed NIR magnitudes of the sources in some fields by using the available NIR data for those fields. We identified the remaining challenges of this approach. We outlined the path for producing the final IRGSC using the Pan-STARRS data. We have named the Python code to generate the IRGSC as irgsctool, which generates a list of NGS for a field using optical data from the Pan-STARRS 3pi survey and also a list of NGSs having observed NIR data from the UKIRT Infrared Deep Sky Survey if they are available. irgsctool is available in the public domain on this GitHub public repository (https://github.com/sshah1502/irgsc), while the generated and validated IRGSC for the 20 test fields and additional Pan-STARRS Medium Deep Survey fields can be found on Zenodo.

Lyapunov stability of suspension bridges in turbulent flow

In the era of sleek, super slender suspension bridges, facing the issue of stability against dynamic wind actions represents an increasingly complex challenge. Despite the significant progress over the last decades, the impact of atmospheric turbulence on bridge stability remains partially not understood, evoking the need for innovative research approaches. This study aims to address a gap in current research by investigating the random flutter stability associated with variations in the angle of attack due to turbulence, which has not formally been addressed yet. The present investigation employs the 2D rational function approximation model to express self-excited forces in a turbulent flow. The application of this type of models to bridge dynamics yields a viscoelastic coupled dynamic system characterized by memory effects and driven by broad-band long-time-scale noise, described here by a linear homogeneous time-variant differential equation, which shows apparent nonlinear features, and which has rarely been matter of research. Utilizing a Monte Carlo methodology, this work innovates in applying the largest Lyapunov exponent (LE) and the moment Lyapunov exponents (MLE) to study bridge random flutter stability. The calculation of LE and MLE under diverse turbulent wind conditions uncovers lower flutter stability than without turbulence effects. In most cases, sample and low-order p-th moment stability thresholds closely align with the bridge dynamic response pattern; therefore, the flutter critical wind speed is unequivocal. However, under certain turbulence scenarios, it is necessary to resort to MLE for a complete description of stability, evoking some additional consideration of which statistical moments should be considered for the engineering assessment of the flutter limit. Finally, this work provides a qualitative insight into the instability mechanisms by approximating the random parametric excitation with a sinusoidal gust and evaluating the time-periodic system stability via Floquet theory.

Analysis of informativeness of features of classification of dangerous weather events based on radar observation results

One of the crucial factors affecting the safety and regularity of state and civil aviation flights is the meteorological situation. The European territory of Russia is most characterized by dangerous meteorological phenomena associated with cumulonimbus clouds: shower, thunderstorms, hail, accompanied by high atmospheric turbulence. Currently, meteorological radar stations are an indispensable source of information about the weather situation for air transport. The criteria for the classification of meteorological phenomena used in modern radar stations are formed for each event separately and are based on knowledge only about the altitude distribution of radar reflectivity and air temperature, despite the fact that radar data assess the wind characteristics of the atmosphere. It is shown that optimization of the classification criteria for the mentioned meteorological phenomena should be realized by generalization of the criteria and their construction in accordance with the theory of statistical hypothesis distinction, as well as by additional use of information on atmospheric turbulence. Based on the analysis of radar signals reflected from the meteorological events of shower, thunderstorm, and hail, probability distributions of reflectivity and specific dissipation rate of turbulent energy were obtained. Statistical analysis of probability distribution densities was carried out for: the maximum value of reflectivity Zmax, its dependence on height H(Zmax), as well as the maximum specific dissipation rate of turbulent energy EDRmax and the value H(EDRmax). The classification criterion based on the maximum probability functional was chosen to determine the structure of classification algorithms and decision rules. At the same time under the acceptable confidence is accepted the value of the probability of correct classification not lower than 0.8. For the accepted criterion the decision thresholds are constructed and the complete matrices of classification probabilities are calculated. The results of calculations showed that the worst informativeness in the classification of dangerous meteorological events of cumulonimbus cloudiness have parameters H(Zmax), H(EDRmax). Parameters Zmax, EDRmax have greater separating ability, but even for them the confidence of classification is unacceptable. In the article to increase the confidence of classification the joint use of features in the form of multivariate probability distribution densities of information parameters was applied. The best results are achieved when three p(Zmax,H(Zmax),EDRmax) and four p(Zmax,H(Zmax),EDRmax,H(EDRmax)) features are used. In the probability matrices for these cases, the maximum and acceptable at 0.8 level of probabilities of correct classification are achieved. Thus, the expansion of the feature space due to atmospheric turbulence is justified in the problem under consideration. These results will be refined with increasing observation time and will vary for different climatic zones. In general, the decision thresholds for classifying dangerous meteorological events of cumulonimbus cloudiness should be adaptive.

Enhanced frame synchronization and carrier recovery in coherent FSO communication: a pseudo-random and cyclic QPSK approach

To alleviate the impact of atmospheric turbulence on receiver carrier recovery in free-space optical communication, this study introduces a novel frame synchronization and carrier recovery method. This method employs a blend of pseudorandom sequences and specific cyclic quadrature phase shift keying (QPSK) training sequences, facilitating frame synchronization and frequency offset (FO) estimation. The research designs a time-series metric curve to counteract the effect of side peaks, enhancing the accuracy of frequency offset estimation via QPSK spectrum features. Furthermore, the method incorporates a two-stage frequency offset estimation process, utilizing the inherent sign characteristics of the x and y polarization states. Applied to the quadrature amplitude modulation system under atmospheric turbulence conditions, the proposed algorithm demonstrates high precision under both strong and weak turbulence conditions. Furthermore, we confirmed the universality of the algorithm across multiple modulation formats.