Orbital angular momentum (OAM)-carrying beams have received extensive attention due to their high-dimensional characteristics in the context of free-space optical communication. However, accurate OAM mode recognition still suffers from reference misalignment of lateral displacement, beam waist size, and initial phase. Here we propose a deep-learning method to exquisitely recognize OAM modes under misalignment by using an alignment-free fractal multipoint interferometer. Our experiments achieve 98.35% recognizing accuracy when strong misalignment is added to hyperfine OAM modes whose Bures distance is 0.01. The maximum lateral displacement we added with respect to the perfectly on-axis beam is about ± 0.5 beam waist size. This work offers a superstable proposal for OAM mode recognition in the application of free-space optical communication and allows an increase of the communication capacity.
Orbital angular momentum (OAM)-carrying beams have received extensive attention due to their high-dimensional characteristics in the context of free-space optical communication. However, accurate OAM mode recognition still suffers from reference misalignment of lateral displacement, beam waist size, and initial phase. Here we propose a deep-learning method to exquisitely recognize OAM modes under misalignment by using an alignment-free fractal multipoint interferometer. Our experiments achieve 98.35% recognizing accuracy when strong misalignment is added to hyperfine OAM modes whose Bures distance is 0.01. The maximum lateral displacement we added with respect to the perfectly on-axis beam is about ± 0.5 beam waist size. This work offers a superstable proposal for OAM mode recognition in the application of free-space optical communication and allows an increase of the communication capacity.
Abstract The rich structure of transverse spatial modes of structured light has facilitated their extensive applications in quantum information and optical communication. The Laguerre–Gaussian (LG) modes, which carry a well-defined orbital angular momentum (OAM), consist of a complete orthogonal basis describing the transverse spatial modes of light. The application of OAM in free-space optical communication is restricted due to the experimentally limited OAM numbers and the complex OAM recognition methods. Here, we present a novel method that uses the advanced deep learning technique for LG modes recognition. By discretizing the spatial modes of structured light, we turn the OAM state regression into classification. A proof-of-principle experiment is also performed, showing that our method effectively categorizes OAM states with small training samples and the accuracy exceeds 99% from three-dimensional (3D) to fifteen-dimensional (15D) space. By assigning each category a classical information, we further apply our approach to an image transmission task, achieving a transmission accuracy of 99.58%, which demonstrates the ability to encode large data with low OAM number. This work opens up a new avenue for achieving high-capacity optical communication with low OAM number based on structured light.
Orbital angular momentum (OAM) of light has enabled quantum encoding in higher dimensional Hilbert spaces, opening up new opportunities for high capacity satellite-to-ground quantum communications. In this paper, machine learning based recognition of OAM modes for satellite-to-ground communication is proposed. Most of the machine learning models for OAM mode detection reported in literature directly take intensity and phase images of OAM modes as inputs. A novel attempt is made in the proposed work, wherein Histogram of Gradients (HOG) features are extracted from these images and fed to machine learning models. Two architectures are proposed in this paper for OAM mode detection and their performances are reported. The performances of proposed models are also compared under different atmospheric turbulence conditions, propagation distances and the results are reported. In order to evaluate the efficacy of proposed models, performance results of OAM mode detection using various other methods reported in literature are compared with the results obtained from proposed work. It is observed that the performance of proposed models are almost on par with the models reported in literature. Maximum recognition accuracy of 100% with a prediction time ranging between 83 - 157ms, was achieved using the proposed models. The proposed OAM mode detection models can be used for various other quantum communication applications too, including underwater communication.
The desire to increase the amount of information that can be encoded onto a single photon has driven research into many areas of optics. One such area is optical orbital angular momentum (OAM) [1]. These beams have helical phasefronts and carry an orbital angular momentum of mbar per photon, where the integer m is unbounded, giving a large state space in which to encode information. We recently developed a telescope system comprising two bespoke refractive optical elements to transform OAM states into transverse momentum states [2]. This is achieved by mapping the azimuthal position of the input plane to the lateral position in the output [3]. A mapping of this type transforms a set of concentric rings at the input plane into a set of parallel lines in the output plane. A lens can then separate the resulting transverse momentum states into specified lateral positions, allowing for the efficient measurement of multiple OAM states simultaneously. Separating OAM states in this way presents an opportunity for this larger alphabet to improve the data capacity of a free space link and has potential application in both the classical and quantum regimes. We will present our latest design, increasing the bandwidth of measurable states to over 50 OAM modes. In such a system we study the crosstalk introduced by a thin phase turbulence, showing that turbulence similarly degrades the purity of all the modes within this range.
Encoding/decoding off-axis points with discrete orbital angular momentum (OAM) modes is investigated. On-axis Laguerre-Gaussian (LG) beams are expanded into off-axis OAM spectra, with which off-axis points are encoded. The influence of the mode and the displacement of the LG beam on the spread of the OAM spectrum is analysed. The results show that not only the conventional on-axis point, but also off-axis points, can be encoded and decoded with OAM of light. This is confirmed experimentally. The analytical result here provides a solid foundation to use OAM modes to encode two-dimensional high density information for multiplexing and to analyse the effect of mis-alignment in practical OAM applications.
The generation of light containing large degrees of orbital angular momentum (OAM) has recently been demon- strated in both the classical and quantum regimes. Since there is no fundamental limit to how many quanta of OAM a single photon can carry, optical states with an arbitrarily high difference in this quantum number may, in principle, be entangled. This opens the door to investigations into high-dimensional entanglement shared between states in superpositions of nonzero OAM. Additionally, making use of non-zero OAM states can allow for a dramatic increase in the amount of information carried by a single photon, thus increasing the information capacity of a communication channel. In practice, however, it is difficult to differentiate between states with high OAM numbers with high precision. Here we investigate the ability of deep neural networks to differentiate between states that contain large values of OAM. We show that such networks may be used to differentiate be- tween nearby OAM states that contain realistic amounts of noise, with OAM values of up to 100. Additionally, we examine how the classification accuracy scales with the signal-to-noise ratio of images that are used to train the network, as well as those being tested. Finally, we demonstrate the simultaneous classification of < 100 OAM states with greater than 70 % accuracy. We intend to verify our system with experimentally-produced classi- cal OAM states, as well as investigate possibilities that would allow this technique to work in the few-photon quantum regime.
Abstract With the recent exponential developments of high-speed optical communications, traditional optical communications systems are showing their limitations. Over the past decade, the orbital angular momentum (OAM) is attracting more and more research attention, due to its orthogonality between two OAM states, which supplies new degrees of freedom and can be used in fiber or free-space optical communication systems for increasing the communication capacity. Here, we propose a novel OAM de/multiplexing method based on the combination of the March–Zehnder interferometer (MZI) implanted pair of dove prisms (DP) (MZI-DP) and a complex phase gratings (CPG), which can be used to sort and detect multiple OAM modes simultaneously. The fundamental Gaussian beam illuminates the spatial light modulator (SLM) to produce the multiplexed Laguerre–Gaussian modes with different topological charges. The MZI-DP system can sort different OAM modes into odd and even values of topological charges. And then, the designed CPGs perform the concrete measurements of different sorted OAM modes. The propagating directions of different modes are arbitrarily steered by two CPGs in two MZI-DP outputting planes. With this designed system, we can simultaneously sort the OAM modes into odd and even values of topological charges, as well as performing the measurement of a large number of OAM modes without any overlapping between adjacent modes. Furthermore, we have simultaneously demultiplexed 50 different OAM modes and controlled their propagation directions successfully, which shows high-recognition rates and superior performances.