• Photonics Research
  • Vol. 9, Issue 10, 2116 (2021)
Peipei Wang1, Wenjie Xiong1, Zebin Huang1, Yanliang He1, Zhiqiang Xie1, Junmin Liu2, Huapeng Ye3, Ying Li1, Dianyuan Fan1, and Shuqing Chen1、*
Author Affiliations
  • 1International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology, Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, China
  • 2College of New Materials and New Energies, Shenzhen Technology University, Shenzhen 518118, China
  • 3Guangdong Provincial Key Laboratory of Optical Information Materials and Technology and Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China
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    DOI: 10.1364/PRJ.432919 Cite this Article Set citation alerts
    Peipei Wang, Wenjie Xiong, Zebin Huang, Yanliang He, Zhiqiang Xie, Junmin Liu, Huapeng Ye, Ying Li, Dianyuan Fan, Shuqing Chen. Orbital angular momentum mode logical operation using optical diffractive neural network[J]. Photonics Research, 2021, 9(10): 2116 Copy Citation Text show less
    Schematic of OAM mode logical operation based on ODNN.
    Fig. 1. Schematic of OAM mode logical operation based on ODNN.
    Training data set of OAM logic AND gate.
    Fig. 2. Training data set of OAM logic AND gate.
    Training results of ODNN with logic AND operation. (a) Curve of the loss function with the iteration number. (b) Phase and amplitude distributions of diffractive layers.
    Fig. 3. Training results of ODNN with logic AND operation. (a) Curve of the loss function with the iteration number. (b) Phase and amplitude distributions of diffractive layers.
    Modulation results of ODNN with different logical operations. (a) Logic AND gate. (b) Logic OR gate.
    Fig. 4. Modulation results of ODNN with different logical operations. (a) Logic AND gate. (b) Logic OR gate.
    OAM logic NOT gate based on ODNN. (a) Schematic of the light field modulation by ODNN. (b) Predicted results of ODNNs with different layers.
    Fig. 5. OAM logic NOT gate based on ODNN. (a) Schematic of the light field modulation by ODNN. (b) Predicted results of ODNNs with different layers.
    (a) Operation truth table and (b) prediction outputs by ODNNs for OAM logic NAND and NOR gates.
    Fig. 6. (a) Operation truth table and (b) prediction outputs by ODNNs for OAM logic NAND and NOR gates.
    Logic XNOR gate cascaded by the basic logic AND, OR, and NOT units. (a) System diagram of XNOR operation based on cascaded logical gates. (b) Truth table. (c) Predicted results of logic XNOR operation with four input states of “00,” “01,” “10,” and “11.”
    Fig. 7. Logic XNOR gate cascaded by the basic logic AND, OR, and NOT units. (a) System diagram of XNOR operation based on cascaded logical gates. (b) Truth table. (c) Predicted results of logic XNOR operation with four input states of “00,” “01,” “10,” and “11.”
    Schematic illustration of logic XOR operation. (a) System diagram of XOR gate cascaded by logic AND, OR, and NOT gates. (b) Truth table. (c) Phase and intensity distribution of results predicted by the logic XOR gate.
    Fig. 8. Schematic illustration of logic XOR operation. (a) System diagram of XOR gate cascaded by logic AND, OR, and NOT gates. (b) Truth table. (c) Phase and intensity distribution of results predicted by the logic XOR gate.
    Schematic illustration of the half-adder based on the OAM mode. C: Carry. S: sum. (a) System diagram of the half-adder cascaded by the XOR and AND gates. (b) Truth table. (c) Results of the addition operation performed by the half-adder.
    Fig. 9. Schematic illustration of the half-adder based on the OAM mode. C: Carry. S: sum. (a) System diagram of the half-adder cascaded by the XOR and AND gates. (b) Truth table. (c) Results of the addition operation performed by the half-adder.
    Test results of four input states with different phase rotation angles.
    Fig. 10. Test results of four input states with different phase rotation angles.
    Balanced ternary logic AND operation with OAM modes. (a) Truth table. (b) Results predicted by the 5-layer ODNN.
    Fig. 11. Balanced ternary logic AND operation with OAM modes. (a) Truth table. (b) Results predicted by the 5-layer ODNN.
     Original ModelModel Trained with Different Waists
    w00001101100011011
    1.575.27%47.81%61.45%40.52%94.42%93.26%92.74%92.46%
    1.681.73%55.72%69.02%47.82%95.84%95.13%94.74%95.03%
    1.787.62%65.51%76.70%57.13%96.75%96.17%95.89%96.33%
    1.892.75%77.90%84.82%70.47%97.37%96.82%96.62%97.06%
    1.996.63%91.28%93.04%88.34%97.80%97.26%97.13%97.58%
    2.098.40%97.95%97.87%98.93%98.10%97.60%97.52%98.03%
    2.196.98%92.23%90.20%89.41%98.30%97.86%97.80%98.40%
    2.291.86%81.08%68.89%74.59%98.41%98.01%97.96%98.57%
    2.383.81%71.62%50.74%64.45%98.45%97.99%97.91%98.41%
    2.474.73%65.13%41.93%58.42%98.40%97.72%97.53%97.79%
    2.566.41%60.87%38.44%54.77%98.27%97.11%96.67%96.62%
    Table 1. Test Results of Four Input States with Different Waist Radii
    Cn2 (1016m2/3)00011011
    198.18%96.75%96.24%97.23%
    597.58%86.11%92.53%90.57%
    1096.46%90.26%83.04%81.59%
    5078.72%75.37%71.88%74.37%
    10077.74%66.98%64.21%68.04%
    15059.07%69.55%49.48%45.30%
    Table 2. Test Results of Four Input States under the Influence of Different Turbulences
    Peipei Wang, Wenjie Xiong, Zebin Huang, Yanliang He, Zhiqiang Xie, Junmin Liu, Huapeng Ye, Ying Li, Dianyuan Fan, Shuqing Chen. Orbital angular momentum mode logical operation using optical diffractive neural network[J]. Photonics Research, 2021, 9(10): 2116
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