Information transmission through parallel multi-task-based recognition of high-resolution multiplexed orbital angular momentum

doi:10.1007/s11467-024-1402-y

2024, Vol. 19

Issue (5) : 52202 https://doi.org/10.1007/s11467-024-1402-y

Information transmission through parallel multi-task-based recognition of high-resolution multiplexed orbital angular momentum

Jingwen Zhou¹, Yaling Yin¹(

), Jihong Tang¹, Yong Xia^1,^2,³(

), Jianping Yin¹

¹. State key laboratory of precision spectroscopy, School of Physics and Electronic Science, East China Normal University, Shanghai 200241, China
². Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China
³. NYU-ECNU Institute of Physics at NYU Shanghai, Shanghai 200062, China

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Abstract

Orbital angular momentums (OAMs) greatly enhance the channel capacity in free-space optical communication. However, demodulation of superposed OAM to recognize them separately is always difficult, especially upon multiplexing more OAMs. In this work, we report a directly recognition of multiplexed fractional OAM modes, without separating them, at a resolution of 0.1 with high accuracy, using a multi-task deep learning (MTDL) model, which has not been reported before. Namely, two-mode, four-mode, and eight-mode superposed OAM beams, experimentally generated with a hologram carrying both phase and amplitude information, are well recognized by the suitable MTDL model. Two applications in information transmission are presented: the first is for 256-ary OAM shift keying via multiplexed fractional OAMs; the second is for OAM division multiplexed information transmission in an eightfold speed. The encouraging results will expand the capacity in future free-space optical communication.

Keywords information transmission orbital angular momentum multi-task deep learning holographic multiplexing structured light

Corresponding Author(s): Yaling Yin,Yong Xia

About author:

Li Liu and Yanqing Liu contributed equally to this work.

Issue Date: 22 April 2024

Cite this article:

Jingwen Zhou,Yaling Yin,Jihong Tang, et al. Information transmission through parallel multi-task-based recognition of high-resolution multiplexed orbital angular momentum[J]. Front. Phys. , 2024, 19(5): 52202.

URL:

https://academic.hep.com.cn/fop/EN/10.1007/s11467-024-1402-y
https://academic.hep.com.cn/fop/EN/Y2024/V19/I5/52202

Fig.1 The first row: experimental setup for multiplexed fractional OAM modes. ISO: optical isolator; OL: objective lens; L: lens; M: mirror; HWP: half wave plate; BS: beam splitter; SLM: spatial light modulator; CCD: charge-coupled device; z: the distance between SLM and CCD. The second row: MTDL to transmit “The Self-Portrait of Van Gogh”: encoding and decoding.

Fig.2 Optical intensity distributions of two-mode OAM superposition at different combinations of

l 1

and

l 2

. Horizontal images are at different

l 1

. Vertical images are at different

l 2

. EXP: experimental data; THE: theoretical data.

Fig.3 Image recognition of fractional multiplexed OAMs by the MTDL. (a) Building blocks in Layers II of ResNeXt 50; (b) building blocks in Layers III of ResNeXt 50; (c) building blocks in Layers IV of ResNeXt 50; (d) building blocks in Layers V of ResNeXt 50. A layer is denoted as a filter size and output channels.

Fig.4 Training and validation of the MTDL model on four-mode multiplexing OAM beams. (a) Accuracy curves; (b) loss function curves. Solid lines are from the training set and dotted lines are from the validation set.

Fig.5 Confusion matrixes for two-mode fractional OAM multiplexing. (a) l₁ and (b) l₂. The horizontal axis represents the experimental/known OAM modes, and the vertical axis presents the to-be-predicted OAM modes.

Fig.6 Confusion matrix for four-mode fractional OAM multiplexing. (a) l₁, (b) l₂, (c) l₃ and (d) l₄. The horizontal axis represents the experimental/known OAM modes, and the vertical axis presents the to-be-predicted OAM modes.

Fig.7 Confusion matrix for eight-mode fractional OAM multiplexing. (a) l₁, (b) l₂, (c) l₃, (d) l₄, (e) l₅, (f) l₆, (g) l₇ and (h) l₈. The horizontal axis represents the experimental/known OAM modes, and the vertical axis presents the to-be- predicted OAM modes.

Fig.8 Coding mechanism of superposed OAM states. GS: grayscale. (a) For two-mode multiplexing. (b) For four-mode multiplexing. (c) For eight-mode multiplexing.

Fig.9 Received image with a size of 160 pixel × 160 pixel by (a) two-mode multiplexing, (b) four-mode multiplexing, and (c) eight-mode multiplexing. (d) PER (%) dependence on the sizes of image and the numbers of multiplexed OAMs.

Fig.10 Illustration of MTDL-based OAM-DM optical information transmission for (a) the general single task way and (b) our eightfold transmission. There are eight-pixel points in the red rectangular box and one pixel point in each red square box. Using a single task model, to transmits the unit of eight-pixel points following the general way [for (a)], each pixel needs to be coded into a light intensity image. For a 160 pixel × 160 pixel image, a total of 25 600 images are required. As for the eightfold transmission way [for (b)], the unit of eight-pixel points is coded into a light intensity image, so only requires 3200 images for the MTDL model.

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