Generation of multi-channel chaotic signals with time delay signature concealment and ultrafast photonic decision making based on a globally-coupled semiconductor laser network

Han, Yanan; Xiang, Shuiying; Wang, Yang; Ma, Yuanting; Wang, Bo; Wen, Aijun

doi:10.1364/prj.403319

Cited by 27 publications

(9 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and utilized for reconstruction of chaotic systems, which seriously threaten the security of communication. Many methods have been reported to complicate and suppress the TDS . In order to improve the security of multiplexed fluorescence lifetime encryption, herein, we propose a scheme for the generation of lifetime division multiplexing (LTDM) and verify its effectiveness and adaptability.…”

Section: Resultsmentioning

confidence: 99%

Lifetime Division Multiplexing by Multilevel Encryption Algorithm

Luo

Zhou

2021

ACS Nano

View full text Add to dashboard Cite

Asymmetric, multilevel, switchable, and reversible encryption is realized by algorithm encryption, which plays an important role in encryption technology. Fluorescence lifetime encryption is currently not executed by an algorithm. It is well-known that the short fluorescence lifetime (τ1), long fluorescence lifetime (τ2), amplitude-weighted average fluorescence lifetime (τm), and intensity-weighted average fluorescence lifetime (τi) can be obtained using a double exponential fitting, and then these four lifetime parameters can be considered as four lifetime algorithms. Therefore, we propose that the acquisition of these four fluorescence lifetimes can be regarded as further dividing the lifetime by different algorithms and optimizing lifetime multiplexing. Moreover, the four lifetime algorithms of τ1, τm, τ2, and τi can be switched between each other and can be used to perform asymmetric, multilevel, and reversible lifetime encryption to effectively increase the difficulties of anticounterfeiting.

show abstract

Section: Resultsmentioning

confidence: 99%

Lifetime Division Multiplexing by Multilevel Encryption Algorithm

Luo

Zhou

2021

ACS Nano

View full text Add to dashboard Cite

show abstract

“…The photonic reinforcement learning based on laser chaos with time-delay signature concealment was demonstrated by introducing a phase-modulated Sagnac loop in mutually delay-coupled semiconductor lasers (PMSL-MC) [73] , as shown in Fig. 22.…”

Section: Photonic Reinforcement Learningmentioning

confidence: 99%

“…(f) The CC as a function of coupling strength for dual-channels and one-channel in the PMSL-MC system. Reprinted with permission from Ref [73]…”

mentioning

confidence: 99%

A review: Photonics devices, architectures, and algorithms for optical neural computing

et al. 2021

Self Cite

View full text Add to dashboard Cite

The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era. Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed, wide bandwidth, and massive parallelism. Here, we offer a review on the optical neural computing in our research groups at the device and system levels. The photonics neuron and photonics synapse plasticity are presented. In addition, we introduce several optical neural computing architectures and algorithms including photonic spiking neural network, photonic convolutional neural network, photonic matrix computation, photonic reservoir computing, and photonic reinforcement learning. Finally, we summarize the major challenges faced by photonic neuromorphic computing, and propose promising solutions and perspectives.

show abstract

“…Furthermore, mode competition dynamics in a ring–cavity semiconductor laser on a chip has been utilized to solve two-armed bandit problems (i.e., problems with two slot machines) 13 . The lag synchronization of chaos in mutually coupled semiconductor lasers has been used for decision making 14 , and this approach has been extended to laser networks with a large number of slot machines 15 , 16 . Furthermore, single 17 , 18 and entangled 19 – 21 photons have been utilized for photonic decision making.…”

Section: Introductionmentioning

confidence: 99%

Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers

Morijiri

Mihana

Kanno

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Decision making using photonic technologies has been intensively researched for solving the multi-armed bandit problem, which is fundamental to reinforcement learning. However, these technologies are yet to be extended to large-scale multi-armed bandit problems. In this study, we conduct a numerical investigation of decision making to solve large-scale multi-armed bandit problems by controlling the biases of chaotic temporal waveforms generated in semiconductor lasers with optical feedback. We generate chaotic temporal waveforms using the semiconductor lasers, and each waveform is assigned to a slot machine (or choice) in the multi-armed bandit problem. The biases in the amplitudes of the chaotic waveforms are adjusted based on rewards using the tug-of-war method. Subsequently, the slot machine that yields the maximum-amplitude chaotic temporal waveform with bias is selected. The scaling properties of the correct decision-making process are examined by increasing the number of slot machines to 1024, and the scaling exponent of the power-law distribution is 0.97. We demonstrate that the proposed method outperforms existing software algorithms in terms of the scaling exponent. This result paves the way for photonic decision making in large-scale multi-armed bandit problems using photonic accelerators.

show abstract

Generation of multi-channel chaotic signals with time delay signature concealment and ultrafast photonic decision making based on a globally-coupled semiconductor laser network

Cited by 27 publications

References 44 publications

Lifetime Division Multiplexing by Multilevel Encryption Algorithm

Lifetime Division Multiplexing by Multilevel Encryption Algorithm

A review: Photonics devices, architectures, and algorithms for optical neural computing

Decision making for large-scale multi-armed bandit problems using bias control of chaotic temporal waveforms in semiconductor lasers

Contact Info

Product

Resources

About