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A. HEMED1,* , R. ABBAS2, M. FDHALA3
In this experimental study, several control parameters that affect laser network synchronization are investigated, namely, laser bias currents, coupling strength, optical injection (OI) strength, optoelectronic feedback (OEFB) ratio, and optical feedback (OFB) ratio. Higher nonlinearities were observed when operating lasers far away from their thresholds. The system is operated by twin laser sources in both transmitting and receiving units. Novelty is regarded by making each one of these two lasers subject to OFB and also OEFB in addition to unidirectional OI. The effect of feedback and the unidirectional OI technique is to avoid information leakage from the slave laser (SL). This is also supported by the change in time delay associated with each OFB and OEFB laser. Such a technique is called hybrid feedback and injection (HFBI). Even though a more complicated system is proposed, identical chaotic synchronization is optimized by reducing mismatching and controlling coupling strength sufficiently. Identical chaotic synchronization is achieved with different calculated cross-correlation values, which are increased from 24% to 78%. The maximum value for hidden information within chaotic modulation that was achieved and archived experimentally is 500 MHz. Synchronization diagrams provide evidence for zero-leg synchronization with no anticipated shift for resulted dynamics. Such a result occurred with the arrangement of the receiver signal time delay to compensate for the delay that comes from the signal sent from the transmitter until it reaches the receiver.
Chaotic Synchronization, Laser Network, Cross Correlation.
A. HEMED, R. ABBAS, M. FDHALA, Optimization for chaotic synchronization in a laser diode network by hybrid feedback and unidirectional injection, Optoelectronics and Advanced Materials - Rapid Communications, 18, 3-4, March-April 2024, pp.120-133 (2024).
Submitted at: Sept. 23, 2023
Accepted at: April 8, 2024
Optoelectronics and Advanced Materials - Rapid Communications
(2023): 0.5 - 2023 Journal Citation Reports (Clarivate Analytics, 2024)
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