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Time-delay signature concealment of chaos and ultrafast decision making in mutually coupled semiconductor lasers with a phase-modulated Sagnac loop

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Abstract

We propose and experimentally demonstrate the generation of dual-channels chaos with time delay signature (TDS) concealment by introducing a phase-modulated Sagnac loop in mutually coupled semiconductor lasers (MCSL). Furthermore, we demonstrate the utilization of the dual-channels chaos to solve multi-armed bandit (MAB) problem in reinforcement learning. The experimental results agree well with the numerical simulations. For the purpose of comparison, the MCSL with a conventional Sagnac loop is also considered. It is found that the TDS of dual-channels chaotic signals can be better concealed in our proposed system. Besides, the proposed system allows for a better decision making performance in MAB problem. Moreover, compared with the one-channel chaotic system, the proposed dual-channels chaotic system achieves ultrafast decision making in parallel, and thus, is highly valuable for further improving the security of communication systems and the performance of photonic intelligence.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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Figures (13)

Fig. 1.
Fig. 1. Experimental setup of a dual-channels chaotic system with a phase-modulated Sagnac loop. DFB1, DFB2: distributed feedback semiconductor lasers; FC: fiber coupler; VOA: variable optical attenuator; ${t_1},{t_2}$: fiber jumper with different length; PM: electro-optic phase modulator; PRBS generator: pseudo-random binary sequence generator; PC: polarization controller, LDC: laser diode controller, OI: optical isolator, OPM: optical power meter, OSA: optical spectrum analyzer; PD: photodiode; OSC: oscilloscope. Optical spectra are presented in the insets.
Fig. 2.
Fig. 2. The chaotic time series (column a), the corresponding ACFs (column b) and the power spectra (column c) for two lasers. The row 1 and row 2 are the results of DFB1 and DFB2 in the CSL-MC system respectively. The row 3 and row 4 are the results of DFB1 and DFB2 in the PMSL-MC system respectively.
Fig. 3.
Fig. 3. (a) ${\rho _1}$, (b) ${\rho _2}$ in the CSL-MC system (${\rho _{\textrm{CSL - MC1}}}$, ${\rho _{\textrm{CSL - MC2}}}$) and the PMSL-MC system (${\rho _{\textrm{PMSL - MC1}}}$, ${\rho _{\textrm{PMSL - MC2}}}$), as a function of ${k_r}$.
Fig. 4.
Fig. 4. Two dimensional maps of ${\rho _m}$ in the parameter space of ${k_r}$ and $\Delta {f_{ 1 2}}$ for DFB1 (left column) and DFB2 (right column). The row 1 is for the CSL-MC system and the row 2 is for the PMSL-MC system.
Fig. 5.
Fig. 5. Two dimensional maps of ${\rho _m}$ in the parameter space of ${k_r}$ and ${k_{PM}}$ for (a) DFB1 and (b) DFB2.
Fig. 6.
Fig. 6. Two dimensional maps of ${\rho _m}$ in the parameter space of ${\tau _1}$ and ${\tau _2}$ for (a) DFB1 and (b) DFB2.
Fig. 7.
Fig. 7. Architecture for reinforcement learning based on dual-channels laser chaos.
Fig. 8.
Fig. 8. (a) The CDR as a function of cycle for the CSL-MC system and for the PMSL-MC system. (b) The CC as a function of ${k_r}$ for the CSL-MC system and the PMSL-MC system.
Fig. 9.
Fig. 9. Threshold value as a function of cycle for the 1-st, 2500-th, and 5000-th decision making process for (a) $T{V_1}$ (b) $T{V_{2,0}}$ (c) $T{V_{2,1}}$ in the PMSL-MC system.
Fig. 10.
Fig. 10. (a) The CDR as a function of the number of cycles for dual-channels and one-channel in the PMSL-MC system. (b) The CC as a function of ${k_r}$ for dual-channels and one-channel in the PMSL-MC system.
Fig. 11.
Fig. 11. The CDR as a function of the number of cycles for the CSL-MC system and the PMSL-MC system in a changing environment.
Fig. 12.
Fig. 12. Experimental (a) ${\rho _1}$, (b) ${\rho _2}$ in the CSL-MC system (${\rho _{\textrm{CSL - MC1}}}$, ${\rho _{\textrm{CSL - MC2}}}$) and the PMSL-MC system (${\rho _{\textrm{PMSL - MC1}}}$, ${\rho _{\textrm{PMSL - MC2}}}$), as a function of ${P_{inj}}$.
Fig. 13.
Fig. 13. Experimental (a) The CDR as a function of cycle for the CSL-MC system and for the PMSL-MC system with ${P_{inj}} = 98.15\mu \textrm{W}$. Experimental (b) The CC as a function of ${P_{inj}}$ for the CSL-MC system and the PMSL-MC system.

Equations (8)

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dE1(t)dt=1+ia2[g[NtN0]1+ε|E1(t)|21τp]E1(t)+k1[12E1(tτ1)exp(iω1τ1+iϕPM)+12E1(tτ1)exp(iω1τ1)]+k2[12E2(tτ21)exp(iω1τ21+iϕPM)+12E2(tτ21)exp(iω1τ21)]
dE2(t)dt=1+ia2[g[NtN0]1+ε|E2(t)|21τp]E2(t)+k2[12E2(tτ2)exp(iω2τ2+iϕPM)+12E2(tτ2)exp(iω2τ2)]+k1[12E1(tτ12)exp(iω2τ12+iϕPM)+12E1(tτ12)exp(iω2τ12)]
dN1,2(t)dt=I1,2qN1,2(t)τng[NtN0]1+ε|E1,2(t)|2|E1,2(t)|2
Cm(Δt)=<[Im(t+Δt)<Im(t+Δt)>][Im(t)<Im(t)>]><[Im(t+Δt)<Im(t+Δt)>]2><[Im(t)<Im(t)>]2>
T(t)={kL(TV(t)>L)k×TV(t)(|TV(t)|L)kL(TV(t)<L)
TV1 (t + 1)=+Δ1Ω1+aTV1(t) ( if D1=0)TV1 (t + 1)=Δ1+Ω1+aTV1(t) ( if D1=1)TV2,0(t + 1)=+Δ2,0Ω2,0+aTV2,0(t) (if D1=0,D2=0)TV2,0(t + 1)=Δ2,0+Ω2,0+aTV2,0(t) (if D1=0,D2=1)TV2,1(t + 1)=+Δ2,1Ω2,1+aTV2,1(t) (if D1=1,D2=0)TV2,1(t + 1)=Δ2,1+Ω2,1+aTV2,1(t) (if D1=1,D2=1)
Ω1=P^D1=0+P^D1=1Δ1=2(P^D1=0+P^D1=1)Ω2,0=P^D1=0,D2=0+P^D1=0,D2=1Δ2,0=2(P^D1=0,D2=0+P^D1=0,D2=1)Ω2,1=P^D1=1,D2=0+P^D1=1,D2=1Δ2,1=2(P^D1=1,D2=0+P^D1=1,D2=1)
P^D1=k=ND1=k,hitND1=k,totalP^D1=k,D2=k=ND1=k,D2=k,hitND1=k,D2=k,total (k = 0,1)
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