Infrared and Laser Engineering, Volume. 51, Issue 1, 20210857(2022)
Ultra-short pulse fiber amplifier model based on recurrent neural network (Invited)
Figures & Tables(7)
Fig. 1. Schematic of numerical calculationsmodel of fiber amplifiers
Fig. 3. Evolution of pulses calculated using NLSE&RE and RNN respectively. (a) Time domain evolution; (b) Frequency domain evolution; (c) Pulse width (blue line) and spectral width (red line)
Fig. 4. Time domain and frequency of pulses at different transmission distances calculated using NLSE&RE (red dotted line) and RNN (blue solid line) respectively
Fig. 5. Calculation time versus number of grid points and calculation steps by using NLSE&RE and RNN respectively
Fig. 6. Comparison of experimental results with simulation results. (a) Amplifier power; (b) Time domain of output pulses; (c) Spectrum of output pulses, where GNLSE&RE calculated results are red dotted lines, RNN predicted results are blue solid lines and experimental results are black solid lines
Table 1. Parameters used in the simulation
View tableView in ArticleTable 1. Parameters used in the simulation
Parameters Value Source Parameters Value Source ${\lambda _0}/ {{\text{nm}}} $ 1 975 Measured ${\lambda _{\text{p}}}/ {{\text{nm}}} $ 793 Measured ${\sigma _{\text{a} } } \left({ {\lambda _j} } \right)/ { { {\text{m} }^{\text{2} } } }$ Fitted Jackson[16] ${\sigma _{\text{a} } } \left( { {\lambda _{\text{p} } } } \right)/ { { {\text{m} }^{\text{2} } } }$ $6 \times {10^{ - 25}}$ Smith[20] ${\sigma _{\text{e} } } \left({ {\lambda _j} } \right)/ { { {\text{m} }^{\text{2} } } }$ Fitted Jackson[16] ${\sigma _{\text{e} } }\left( { {\lambda _{\text{p} } } } \right)/ { { {\text{m} }^{\text{2} } } }$ $5 \times {10^{ - 26}}$ Smith[20] ${N_{\text{d}}}/ {{{\text{m}}^{-3}}} $ $1.7 \times {10^{26}}$ NUFERN $V$ 3.02 NUFERN ${D_{ {\text{core} } } }/ { {\text{μ} }{\rm{m} } }$ 10 NUFERN ${D_{ {\text{clad} } } }/ { {\text{μ } } }{\rm{m} }$ 130 NUFERN ${A_{\rm{eff} } }/{ {\text{μ } }{ {\rm{m} }^{\text{2} } } }$ 72.7 Calculated[21] ${A_{\text{p} } }/ {\text{μ } } {\text{m} }^{\text{2} }$ $1.40 \times {10^4}$ Calculated[21] $ {\varGamma _{\text{s}}} $ 0.88 Calculated[21] $ {\varGamma _{\text{p}}} $ $5.6 \times {10^{ - 3}}$ Calculated[21] ${A_{30}}/ {{{\text{s}}^{{{ - 1}}}}} $ 0 ${A_{31}}/ {{{\text{s}}^{{{ - 1}}}}} $ $7 \times {10^4}$ Jackson[16] ${A_{32}}/ {{{\text{s}}^{{{ - 1}}}}} $ 0 ${A_{20}}/ {{{\text{s}}^{{{ - 1}}}}} $ 0 ${A_{21}}/ {{{\text{s}}^{{{ - 1}}}}} $ 0 ${A_{10}}/ {{{\text{s}}^{{{ - 1}}}}} $ 3000 Jackson[16] ${k_{3011} }/ { { {\text{m} }^{\text{3} } } \cdot { {\text{s} }^{ { { - 1} } } } }$ $2 \times {10^{ - 22}}$ Smith[20] $ {k_{1130}}/ {{{\text{m}}^{\text{3}}} \cdot {{\text{s}}^{{{ - 1}}}}} $ $2 \times {10^{ - 23}}$ Smith[20] ${k_{2011} }/ { { {\text{m} }^{\text{3} } } \cdot { {\text{s} }^{ { { - 1} } } } } $ 0 $ {k_{1120}}/ {{{\text{m}}^{\text{3}}} \cdot {{\text{s}}^{{{ - 1}}}}} $ 0 ${\alpha _{\text{s} } }/ { { {\text{m} }^{ { { - 1} } } }}$ $2.3 \times {10^{ - 3}}$ Jackson[16] ${\alpha _{_{\text{p} } } } / { { {\text{m} }^{ { { - 1} } } }}$ $1.2 \times {10^{ - 2}}$ Jackson[16] ${\beta _2}/ { {\text{p} }{ {\text{s} }^{\text{2} } }\cdot{\text{k} }{ {\text{m} }^{ { { - 1} } } } }$ −88 NUFERN ${\beta _3}/ { {\text{p} }{ {\text{s} }^{\text{3} } }\cdot{\text{k} }{ {\text{m} }^{ { { - 1} } } }}$ +0.28 NUFERN ${n_2}/ { { {\text{m} }^{\text{2} } }\cdot{ {\text{W} }^{ { { - 1} } } } }$ $2.3 \times {10^{ - 20}}$ Agrawal[18] $\gamma / { { {\text{m} }^{ - 1} }\cdot{ {\text{W} }^{ { { - 1} } } }}$ 0.0010 Calculated[18]
Tools
Get Citation
Copy Citation Text
Yiwen Zhang, Yu Cai, Lixin Yuan, Minglie Hu. Ultra-short pulse fiber amplifier model based on recurrent neural network (Invited)[J]. Infrared and Laser Engineering, 2022, 51(1): 20210857
Paper Information
Category: Lasers & Laser optics
Received: Nov. 25, 2021
Accepted: Dec. 27, 2021
Published Online: Mar. 8, 2022
The Author Email:
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20