Photonic Neuromorphic Pattern Recognition with a Spiking DFB‐SA Laser Subject to Incoherent Optical Injection

Photonic neuromorphic computing is a competitive paradigm to overcome the bottleneck of von Neumann architectures. Incoherent and coherent synaptic networks are two popular schemes realizing photonic weighting functions. Previous works have proved the distributed feedback (DFB) laser with an intraca...

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Published inLaser & photonics reviews Vol. 19; no. 1
Main Authors Zhang, Yuna, Xiang, Shuiying, Yu, Chengyang, Gao, Shuang, Han, Yanan, Guo, Xingxing, Zhang, Yahui, Shi, Yuechun, Hao, Yue
Format Journal Article
LanguageEnglish
Published Weinheim Wiley Subscription Services, Inc 01.01.2025
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ISSN1863-8880
1863-8899
DOI10.1002/lpor.202400482

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Abstract Photonic neuromorphic computing is a competitive paradigm to overcome the bottleneck of von Neumann architectures. Incoherent and coherent synaptic networks are two popular schemes realizing photonic weighting functions. Previous works have proved the distributed feedback (DFB) laser with an intracavity saturable absorber (DFB‐SA) can behavior like a spiking neuron. However, the compatibility with the incoherent synaptic architecture has not yet been demonstrated. Here the neuron‐like dynamics of a DFB‐SA laser subject to single‐wavelength and multiple‐wavelengths incoherent optical injections are experimentally demonstrated. The results show that, for the DFB‐SA laser subject to single‐wavelength incoherent injection, the neuron‐like dynamics including threshold, temporal integration, and refractory period are achieved. Besides, the range of injection wavelength that leads to a successful neuron‐like response is identified. For the DFB‐SA laser with four‐wavelength incoherent optical injection, the neuron‐like dynamics can also be achieved. In addition, the effect of wavelength interval is also considered. The logic XOR operation and Iris recognition tasks are successfully implemented. Furthermore, the feasibility of a cascaded system for the DFB‐SA lasers with four‐wavelengths incoherent optical injection is demonstrated. This work provides a feasible scheme for the system integration of photonic spiking neurons and incoherent synaptic networks. Neuron‐like dynamics in a DFB‐SA laser with single‐wavelength and multiple‐wavelengths incoherent optical injections, and successfully implemented logic XOR operations and Iris recognition are experimentally demonstrated. Additionally, The feasibility of a cascaded DFB‐SA laser system with four‐wavelengths incoherent optical injection is demonstrated. This work offers a viable scheme for integrating photonic spiking neurons and incoherent synaptic networks.
AbstractList Photonic neuromorphic computing is a competitive paradigm to overcome the bottleneck of von Neumann architectures. Incoherent and coherent synaptic networks are two popular schemes realizing photonic weighting functions. Previous works have proved the distributed feedback (DFB) laser with an intracavity saturable absorber (DFB‐SA) can behavior like a spiking neuron. However, the compatibility with the incoherent synaptic architecture has not yet been demonstrated. Here the neuron‐like dynamics of a DFB‐SA laser subject to single‐wavelength and multiple‐wavelengths incoherent optical injections are experimentally demonstrated. The results show that, for the DFB‐SA laser subject to single‐wavelength incoherent injection, the neuron‐like dynamics including threshold, temporal integration, and refractory period are achieved. Besides, the range of injection wavelength that leads to a successful neuron‐like response is identified. For the DFB‐SA laser with four‐wavelength incoherent optical injection, the neuron‐like dynamics can also be achieved. In addition, the effect of wavelength interval is also considered. The logic XOR operation and Iris recognition tasks are successfully implemented. Furthermore, the feasibility of a cascaded system for the DFB‐SA lasers with four‐wavelengths incoherent optical injection is demonstrated. This work provides a feasible scheme for the system integration of photonic spiking neurons and incoherent synaptic networks.
Photonic neuromorphic computing is a competitive paradigm to overcome the bottleneck of von Neumann architectures. Incoherent and coherent synaptic networks are two popular schemes realizing photonic weighting functions. Previous works have proved the distributed feedback (DFB) laser with an intracavity saturable absorber (DFB‐SA) can behavior like a spiking neuron. However, the compatibility with the incoherent synaptic architecture has not yet been demonstrated. Here the neuron‐like dynamics of a DFB‐SA laser subject to single‐wavelength and multiple‐wavelengths incoherent optical injections are experimentally demonstrated. The results show that, for the DFB‐SA laser subject to single‐wavelength incoherent injection, the neuron‐like dynamics including threshold, temporal integration, and refractory period are achieved. Besides, the range of injection wavelength that leads to a successful neuron‐like response is identified. For the DFB‐SA laser with four‐wavelength incoherent optical injection, the neuron‐like dynamics can also be achieved. In addition, the effect of wavelength interval is also considered. The logic XOR operation and Iris recognition tasks are successfully implemented. Furthermore, the feasibility of a cascaded system for the DFB‐SA lasers with four‐wavelengths incoherent optical injection is demonstrated. This work provides a feasible scheme for the system integration of photonic spiking neurons and incoherent synaptic networks. Neuron‐like dynamics in a DFB‐SA laser with single‐wavelength and multiple‐wavelengths incoherent optical injections, and successfully implemented logic XOR operations and Iris recognition are experimentally demonstrated. Additionally, The feasibility of a cascaded DFB‐SA laser system with four‐wavelengths incoherent optical injection is demonstrated. This work offers a viable scheme for integrating photonic spiking neurons and incoherent synaptic networks.
Author Han, Yanan
Guo, Xingxing
Yu, Chengyang
Zhang, Yahui
Shi, Yuechun
Gao, Shuang
Hao, Yue
Zhang, Yuna
Xiang, Shuiying
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Cites_doi 10.1364/PRJ.413742
10.29026/oea.2023.230140
10.1109/JPHOT.2016.2614104
10.1038/srep19126
10.1016/j.optcom.2023.129870
10.1038/srep07377
10.1109/JSTQE.2017.2685140
10.1364/OPTICA.468347
10.24251/HICSS.2019.770
10.1364/OE.21.026182
10.1063/1.4937730
10.1109/JLT.2023.3331252
10.1126/science.1254642
10.1080/02626669609491511
10.1364/OE.21.020931
10.1364/OL.36.004476
10.1007/s11432-023-3810-9
10.1002/lpor.202300424
10.1364/OL.34.000440
10.1136/svn-2017-000101
10.1038/s41551-018-0305-z
10.1109/TKDE.2006.183
10.1109/JSTQE.2017.2678170
10.1364/OL.42.001560
10.1103/PhysRevLett.88.063901
10.1364/PRJ.485941
10.1109/JSTQE.2013.2257700
10.1109/JLT.2023.3322628
10.1103/PhysRevE.84.036209
10.1103/PhysRevA.82.023807
10.1103/PhysRevLett.98.153903
10.1364/OL.39.001254
10.1063/1.3692726
10.1109/TNN.2009.2023653
10.1109/JPROC.2014.2304638
10.1038/ncomms6915
10.1109/ISLC.2014.215
10.1103/PhysRevA.94.033839
10.1109/TNNLS.2015.2404938
10.1109/TCSI.2020.3010723
10.1109/TNNLS.2020.3006263
10.1038/nature14539
10.1007/s11082-014-9884-4
10.1038/srep19510
10.1103/PhysRevE.88.022923
10.1109/ACCESS.2020.2988510
10.1364/OE.21.028922
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References 2021; 9
2023; 10
2017; 42
2015; 6
2017; 2
2012; 100
2023; 11
2009; 20
2023; 17
2013; 88
2013; 21
2015; 521
2023; 6
2011; 84
2017; 23
2006; 18
2014; 46
2016; 94
2023; 549
2015; 107
2011; 36
2020; 32
2007; 98
2022; 29
2010; 82
2020; 8
2009; 34
2023; 42
2013; 19
2016; 6
2015; 26
2018; 2
2014; 4
2019; 40
2002; 88
2019
1996; 41
2020; 67
2014
2024; 67
2014; 39
2010; 4
2014; 345
2016; 8
2020; 29
2014; 102
e_1_2_9_31_1
e_1_2_9_52_1
e_1_2_9_50_1
e_1_2_9_10_1
e_1_2_9_35_1
e_1_2_9_12_1
e_1_2_9_33_1
Mogaji E. (e_1_2_9_4_1) 2020; 29
e_1_2_9_14_1
e_1_2_9_39_1
e_1_2_9_16_1
e_1_2_9_37_1
e_1_2_9_18_1
e_1_2_9_41_1
e_1_2_9_20_1
e_1_2_9_22_1
e_1_2_9_45_1
e_1_2_9_24_1
e_1_2_9_43_1
e_1_2_9_8_1
e_1_2_9_6_1
e_1_2_9_2_1
Basu J. K. (e_1_2_9_13_1) 2010; 4
e_1_2_9_26_1
e_1_2_9_49_1
Song Z. (e_1_2_9_47_1) 2022; 29
e_1_2_9_28_1
e_1_2_9_30_1
e_1_2_9_51_1
e_1_2_9_11_1
e_1_2_9_34_1
e_1_2_9_32_1
e_1_2_9_15_1
e_1_2_9_38_1
e_1_2_9_17_1
e_1_2_9_36_1
e_1_2_9_19_1
e_1_2_9_42_1
e_1_2_9_40_1
e_1_2_9_21_1
e_1_2_9_46_1
e_1_2_9_23_1
e_1_2_9_44_1
e_1_2_9_7_1
e_1_2_9_5_1
e_1_2_9_3_1
e_1_2_9_1_1
e_1_2_9_9_1
e_1_2_9_25_1
e_1_2_9_27_1
e_1_2_9_48_1
e_1_2_9_29_1
References_xml – volume: 39
  start-page: 1254
  year: 2014
  publication-title: Opt. Lett.
– volume: 8
  start-page: 1
  year: 2016
  publication-title: IEEE Phot. J.
– volume: 345
  start-page: 668
  year: 2014
  publication-title: Science
– volume: 2
  start-page: 719
  year: 2018
  publication-title: Nat. Biomed. Eng.
– volume: 32
  start-page: 2494
  year: 2020
  publication-title: IEEE Trans. on Neur. Netw. Learn. Syst.
– volume: 98
  year: 2007
  publication-title: Phys. Rev. Lett.
– volume: 42
  start-page: 1497
  year: 2023
  publication-title: J. Lightwave Technol.
– volume: 40
  start-page: 81
  year: 2019
– volume: 84
  year: 2011
  publication-title: Phys. Rev. E
– volume: 20
  start-page: 1417
  year: 2009
  publication-title: IEEE Trans. Neural. Netw.
– volume: 10
  start-page: 162
  year: 2023
– volume: 19
  start-page: 1
  year: 2013
  publication-title: IEEE J. Sel. Top. Quantum Electron.
– volume: 23
  start-page: 1
  year: 2017
  publication-title: IEEE J. Sel. Top. Quantum Electron.
– volume: 18
  start-page: 1696
  year: 2006
  publication-title: IEEE Trans. Knowl. Data. Eng.
– volume: 8
  year: 2020
  publication-title: Ieee Access
– volume: 4
  start-page: 7377
  year: 2014
  publication-title: Sci. Rep.
– volume: 88
  year: 2013
  publication-title: Phys. Rev. E
– volume: 102
  start-page: 652
  year: 2014
  publication-title: Proc. IEEE
– volume: 46
  start-page: 1353
  year: 2014
  publication-title: Opt. Quant. Electron.
– volume: 100
  year: 2012
  publication-title: Appl. Phys. Lett.
– start-page: 6408
  year: 2019
– volume: 521
  start-page: 436
  year: 2015
  publication-title: Nature
– volume: 42
  start-page: 1560
  year: 2017
  publication-title: Opt. Lett.
– volume: 11
  start-page: 1382
  year: 2023
  publication-title: Phot. Res.
– start-page: 165
  year: 2014
– volume: 21
  year: 2013
  publication-title: Opt. Express
– volume: 88
  year: 2002
  publication-title: Phys. Rev. Lett.
– volume: 67
  year: 2024
  publication-title: Sci.e China Inform. Sci.
– volume: 67
  start-page: 4932
  year: 2020
  publication-title: IEEE Trans. Circ. Syst. I: Regular Papers
– volume: 2
  start-page: 8
  year: 2017
  publication-title: Stroke Vasc. Neurol.
– volume: 29
  start-page: 1
  year: 2022
  publication-title: IEEE J. Sel. Top. Quantum Electron.
– volume: 17
  year: 2023
  publication-title: Laser Photonics Rev.
– volume: 9
  start-page: B119
  year: 2021
  publication-title: Phot. Res.
– volume: 34
  start-page: 440
  year: 2009
  publication-title: Opt. Lett.
– volume: 6
  year: 2016
  publication-title: Sci. Rep.
– volume: 6
  year: 2023
  publication-title: Opto‐Electronic Advances
– volume: 42
  start-page: 2026
  year: 2023
  publication-title: J. Lightwave Technol.
– volume: 6
  start-page: 5915
  year: 2015
  publication-title: Nat. Commun.
– volume: 82
  year: 2010
  publication-title: Phys. Rev. A
– volume: 549
  year: 2023
  publication-title: Opt. Commun.
– volume: 107
  year: 2015
  publication-title: Appl. Phys. Lett.
– volume: 26
  start-page: 3137
  year: 2015
  publication-title: IEEE Trans. on Neur. Netw. Learn. Syst.
– volume: 29
  start-page: 003
  year: 2020
  publication-title: Australasian Marketing J.
– volume: 4
  start-page: 1
  year: 2010
  publication-title: Int. J. Softw. Eng. Appl.
– volume: 41
  start-page: 399
  year: 1996
  publication-title: Hydrol. Sci. J.
– volume: 36
  start-page: 4476
  year: 2011
  publication-title: Opt. Lett.
– volume: 94
  year: 2016
  publication-title: Phys. Rev. A
– ident: e_1_2_9_50_1
  doi: 10.1364/PRJ.413742
– ident: e_1_2_9_42_1
  doi: 10.29026/oea.2023.230140
– ident: e_1_2_9_29_1
  doi: 10.1109/JPHOT.2016.2614104
– volume: 4
  start-page: 1
  year: 2010
  ident: e_1_2_9_13_1
  publication-title: Int. J. Softw. Eng. Appl.
– ident: e_1_2_9_24_1
  doi: 10.1038/srep19126
– ident: e_1_2_9_11_1
  doi: 10.1016/j.optcom.2023.129870
– ident: e_1_2_9_52_1
  doi: 10.1038/srep07377
– ident: e_1_2_9_30_1
  doi: 10.1109/JSTQE.2017.2685140
– ident: e_1_2_9_41_1
  doi: 10.1364/OPTICA.468347
– ident: e_1_2_9_3_1
  doi: 10.24251/HICSS.2019.770
– ident: e_1_2_9_36_1
  doi: 10.1364/OE.21.026182
– ident: e_1_2_9_28_1
  doi: 10.1063/1.4937730
– ident: e_1_2_9_45_1
  doi: 10.1109/JLT.2023.3331252
– ident: e_1_2_9_9_1
  doi: 10.1126/science.1254642
– volume: 29
  start-page: 003
  year: 2020
  ident: e_1_2_9_4_1
  publication-title: Australasian Marketing J.
– ident: e_1_2_9_15_1
  doi: 10.1080/02626669609491511
– ident: e_1_2_9_25_1
  doi: 10.1364/OE.21.020931
– ident: e_1_2_9_38_1
  doi: 10.1364/OL.36.004476
– ident: e_1_2_9_43_1
  doi: 10.1007/s11432-023-3810-9
– ident: e_1_2_9_7_1
  doi: 10.1002/lpor.202300424
– ident: e_1_2_9_33_1
  doi: 10.1364/OL.34.000440
– ident: e_1_2_9_1_1
  doi: 10.1136/svn-2017-000101
– ident: e_1_2_9_2_1
  doi: 10.1038/s41551-018-0305-z
– ident: e_1_2_9_14_1
  doi: 10.1109/TKDE.2006.183
– ident: e_1_2_9_31_1
  doi: 10.1109/JSTQE.2017.2678170
– ident: e_1_2_9_32_1
  doi: 10.1364/OL.42.001560
– ident: e_1_2_9_40_1
  doi: 10.1364/OL.36.004476
– ident: e_1_2_9_19_1
  doi: 10.1103/PhysRevLett.88.063901
– ident: e_1_2_9_6_1
– ident: e_1_2_9_44_1
  doi: 10.1364/PRJ.485941
– ident: e_1_2_9_49_1
  doi: 10.1109/JSTQE.2013.2257700
– ident: e_1_2_9_46_1
  doi: 10.1109/JLT.2023.3322628
– ident: e_1_2_9_37_1
  doi: 10.1103/PhysRevE.84.036209
– ident: e_1_2_9_34_1
  doi: 10.1103/PhysRevA.82.023807
– ident: e_1_2_9_20_1
  doi: 10.1103/PhysRevLett.98.153903
– ident: e_1_2_9_22_1
  doi: 10.1364/OL.39.001254
– ident: e_1_2_9_26_1
  doi: 10.1063/1.3692726
– ident: e_1_2_9_8_1
  doi: 10.1109/TNN.2009.2023653
– volume: 29
  start-page: 1
  year: 2022
  ident: e_1_2_9_47_1
  publication-title: IEEE J. Sel. Top. Quantum Electron.
– ident: e_1_2_9_10_1
  doi: 10.1109/JPROC.2014.2304638
– ident: e_1_2_9_17_1
  doi: 10.1038/ncomms6915
– ident: e_1_2_9_27_1
  doi: 10.1109/ISLC.2014.215
– ident: e_1_2_9_39_1
  doi: 10.1103/PhysRevA.94.033839
– ident: e_1_2_9_51_1
  doi: 10.1109/TNNLS.2015.2404938
– ident: e_1_2_9_16_1
  doi: 10.1109/TCSI.2020.3010723
– ident: e_1_2_9_48_1
  doi: 10.1109/TNNLS.2020.3006263
– ident: e_1_2_9_12_1
  doi: 10.1038/nature14539
– ident: e_1_2_9_23_1
  doi: 10.1007/s11082-014-9884-4
– ident: e_1_2_9_18_1
  doi: 10.1038/srep19510
– ident: e_1_2_9_21_1
  doi: 10.1103/PhysRevE.88.022923
– ident: e_1_2_9_5_1
  doi: 10.1109/ACCESS.2020.2988510
– ident: e_1_2_9_35_1
  doi: 10.1364/OE.21.028922
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Snippet Photonic neuromorphic computing is a competitive paradigm to overcome the bottleneck of von Neumann architectures. Incoherent and coherent synaptic networks...
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SubjectTerms Biometric recognition systems
DFB‐SA laser
Feasibility
incoherent architecture
Lasers
multiple wavelengths optical injection
Neuromorphic computing
Pattern recognition
photonic neuromorphic computing
Photonics
Refractory period
Spiking
spiking neural network
Wavelengths
Weighting functions
Title Photonic Neuromorphic Pattern Recognition with a Spiking DFB‐SA Laser Subject to Incoherent Optical Injection
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Flpor.202400482
https://www.proquest.com/docview/3152498068
Volume 19
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