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Among the problems that prevent free-space optical communication systems from becoming a truly mainstream technology is beam wander, which is especially important for structured light beams since beam misalignment introduces additional crosstalk at the receiver. The paper suggests a recurrent neural network-based (RNN) solution to predict beam wander in free space optics (FSO). The approach uses past beam center of mass positions to predict future movement, significantly outperforming various prediction types. The proposed approach is demonstrated using under-sampled experimental data over a 260 m link as a worst-case and over-sampled simulated data as a best-case scenario. In addition to conventional Gaussian beams, Hermite- and Laguerre-Gaussian beam wander is also investigated. With a 20 to 40% improvement in error over naive and linear predictions, while predicting multiple samples ahead in typical situations and overall matching or outperforming considered predictions across all studied scenarios, this method could help mitigate turbulence-induced fading and has potential applications in intelligent re-transmits, quality of service, optimized error correction, maximum likelihood-type algorithms, and predictive adaptive optics.
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This Lab Note introduces the "Stokes Camera," a simple experimental arrangement for real-time measurement of spatial amplitude and polarization and thus spatially resolved Stokes parameters. It uses a polarization sensitive camera and a fixed quarter-wave plate, providing a one-shot, digital solution for polarization measurement that is only limited by the frame rate of the camera and the computation speed of the provided code. The note also provides background information on relevant polarization theory and vector vortex beams, which are used as a demonstration of the device.
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We present a fast and efficient simulation method of structured light free space optics (FSO) channel effects from propagation through a turbulent atmosphere. In a system that makes use of multiple higher order modes (structured light), turbulence causes crosstalk between modes. This crosstalk can be described by a channel matrix, which usually requires a complete physical simulation or an experiment. Current simulation techniques based on the phase-screen approximation method are very computationally intensive and are limited by the accuracy of the underlying models. In this work, we propose to circumvent these limitations by using a data-driven approach for the decomposition matrix simulation with a conditional generative adversarial network (CGAN) synthetic simulator.
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Orbital angular momentum (OAM) modes are topical due to their versatility, and they have been used in several applications including free-space optical communication systems. The classification of OAM modes is a common requirement, and there are several methods available for this. One such method makes use of deep learning, specifically convolutional neural networks, which distinguishes between modes using their intensities. However, OAM mode intensities are very similar if they have the same radius or if they have opposite topological charges, and as such, intensity-only approaches cannot be used exclusively for individual modes. Since the phase of each OAM mode is unique, deep learning can be used in conjugation with interferometry to distinguish between different modes. In this paper, we demonstrate a very high classification accuracy of a range of OAM modes in turbulence using a shear interferometer, which crucially removes the requirement of a reference beam. For comparison, we show only marginally higher accuracy with a more conventional Mach-Zehnder interferometer, making the technique a promising candidate towards real-time, low-cost modal decomposition in turbulence.
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Digital micro-mirror devices (DMDs) are a popular alternative to liquid crystal spatial light modulators for laser beam shaping due to their relatively low cost, high speed, and polarization and wavelength independence. Here we describe in detail how to convert a low-cost digital light projector (DLP) evaluation module that uses a Texas Instruments DLP4710 DMD into a spatial light modulator using a 3D printed mount. The resulting device is shown to accurately shape Laguerre-Gauss modes, is able to operate in real-time over HDMI without modification with a 180 Hz hologram refresh rate, and has a resolution of 1920×1080 pixels and diagonal screen size of 0.47 inches (11.9 mm).
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Free-space-optics-based communication links are an attractive potential solution for solving the last mile challenge but suffer from turbulence-induced fading. This fading causes errors in the received signal. While models exist to predict how turbulence affects the signal, these models often do not account for the channel's memory. Typical fading models accurately predict the average effect of the channel on a signal but not the distribution of the errors and the individual lengths of events such as deep fades. To better model the channel, this paper presents an alternative approach: Fritchman Markov modeling. The models produced accurately match the behavior of the channel and can be used to develop robust and efficient error mitigation strategies in the future.
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A quantitative analysis of optical fields is essential, particularly when the light is structured in some desired manner, or when there is perhaps an undesired structure that must be corrected for. A ubiquitous procedure in the optical community is that of optical mode projections-a modal analysis of light-for the unveiling of amplitude and phase information of a light field. When correctly performed, all the salient features of the field can be deduced with high fidelity, including its orbital angular momentum, vectorial properties, wavefront, and Poynting vector. Here, we present a practical tutorial on how to perform an efficient and effective optical modal decomposition, with emphasis on holographic approaches using spatial light modulators, highlighting the care required at each step of the process.
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Free-space optical communication with spatial modes of light has become topical due to the possibility of dramatically increasing communication bandwidth via Mode Division Multiplexing (MDM). While both scalar and vector vortex modes have been used as transmission bases, it has been suggested that the latter is more robust in turbulence. Using orbital angular momentum as an example, we demonstrate theoretically and experimentally that the crosstalk due to turbulence is the same in the scalar and vector basis sets of such modes. This work brings new insights about the behaviour of vector and scalar modes in turbulence, but more importantly it demonstrates that when considering optimal modes for MDM, the choice should not necessarily be based on their vectorial nature.
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Information exchange between two distant parties, where information is shared without physically transporting it, is a crucial resource in future quantum networks. Doing so with high-dimensional states offers the promise of higher information capacity and improved resilience to noise, but progress to date has been limited. Here we demonstrate how a nonlinear parametric process allows for arbitrary high-dimensional state projections in the spatial degree of freedom, where a strong coherent field enhances the probability of the process. This allows us to experimentally realise quantum transport of high-dimensional spatial information facilitated by a quantum channel with a single entangled pair and a nonlinear spatial mode detector. Using sum frequency generation we upconvert one of the photons from an entangled pair resulting in high-dimensional spatial information transported to the other. We realise a d = 15 quantum channel for arbitrary photonic spatial modes which we demonstrate by faithfully transferring information encoded into orbital angular momentum, Hermite-Gaussian and arbitrary spatial mode superpositions, without requiring knowledge of the state to be sent. Our demonstration merges the nascent fields of nonlinear control of structured light with quantum processes, offering a new approach to harnessing high-dimensional quantum states, and may be extended to other degrees of freedom too.
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Waves can carry both linear and angular momentum. When the wave is transverse (e.g. light), the angular momentum can be characterised by the "spin" angular momentum associated with circular polarisation, and the "orbital" angular momentum (OAM) arising from the phase cross-section of the beam. When the wave is longitudinal (e.g. sound) there is no polarization and hence no spin angular momentum. However, a suitably phase-structured sound beam can still carry OAM. Observing the transfer of OAM from sound to a macroscopic object provides an excellent opportunity to study the exchange of energy between waves and matter. In this paper we show how to build a compact free-space acoustic spanner based on a 3D-printed sound-guiding structure and common electronic components. We first characterise the sound fields by measuring both phase and amplitude maps, and then show a video of our free-space acoustic spanner in action, in which macroscopic objects spin in a circular motion and change direction of rotation according to the handedness of the OAM acoustic field.
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Free-Space Optical (FSO) systems offer the ability to distribute high speed digital links into remote and rural communities where terrain, installation cost or infrastructure security pose critical hurdles to deployment. A challenge in any point-to-point FSO system is initiating and maintaining optical alignment from the sender to the receiver. In this paper we propose and demonstrate a low-complexity self-aligning FSO prototype that can completely self-align with no requirement for initial manual positioning and could therefore form the opto-mechanical basis for a mesh network of optical transceivers. The prototype utilises off-the-shelf consumer electrical components and a bespoke alignment algorithm. We demonstrate an eight fibre spatially multiplexed link with a loss of 15 dB over 210 m.