In this paper, a novel chaotic secure communication system based on vertical-cavity surface-emitting lasers (VCSEL) with a common phase-modulated electro-optic (CPMEO) feedback is proposed. The security of the CPMEO system is guaranteed by suppressing the time-delay signature (TDS) with a low-gain electro-optic (EO) feedback loop. Furthermore, the key space is enhanced through a unique secondary encryption method. The first-level encrypted keys are the TDS in the EO feedback loop, and the second-level keys are the physical parameters of the VCSEL under variable-polarization optical feedback. Numerical results show that, compared to the dual-optical feedback system, the TDS of the CPMEO system is suppressed 8 times to less than 0.05 such that they can be completely concealed when the EO gain is 3, and the bandwidth is doubled to over 22 GHz. The error-free 10 Gb/s secure optical transmission can be realized when the time-delay mismatch is controlled within 3 ps. It is shown that the proposed scheme can significantly improve the system performance in TDS concealment, as well as bandwidth and key space enhancement, which has great potential applications in secure dual-channel chaos communication.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1364/OE.398125 | DOI Listing |
Accurate forecasting of contagious illnesses has become increasingly important to public health policymaking, and better prediction could prevent the loss of millions of lives. To better prepare for future pandemics, it is essential to improve forecasting methods and capabilities. In this work, we propose a new infectious disease forecasting model based on physics-informed neural networks (PINNs), an emerging area of scientific machine learning.
View Article and Find Full Text PDFHyperspectral images (HSI) have been extensively applied in a multitude of domains, due to their combined spatial and spectral characteristics along with a wealth of spectral bands. The ingenious combination of spatial and spectral information in HSI classification has remained a central research area for an extended period. In the classification process, it is essential to choose an expanded neighborhood window for learning.
View Article and Find Full Text PDFThe space-time wave packet (STWP) is a type of pulsed optical field, exhibiting distinctive characteristics, including the capacity to propagate without diffraction or dispersion and to have arbitrary group velocities. However, the intensity of the STWP is constrained by the low damage threshold of some indispensable optical elements like the spatial light modulator (SLM). While optical parametric amplification (OPA) has been proposed for amplifying STWPs, spatio-temporal (ST) characteristics of amplified STWPs remain significantly unexplored.
View Article and Find Full Text PDFType-II superlattice (T2SL) detectors are emerging as key technologies for next-generation long-wavelength infrared (LWIR) applications, particularly in the 8-14 µm range, offering advantages in space exploration, medical imaging, and defense. A major challenge in improving quantum efficiency (QE) lies in achieving sufficient light absorption without increasing the active layer (AL) thickness, which can elevate dark current and complicate manufacturing. Traditional methods, such as thickening the absorber, are limited by the short carrier lifetime in T2SLs, necessitating alternative solutions.
View Article and Find Full Text PDFSpatial differentiation is the key element for edge detection and holds unquestionable significance in the current information era. All-optical computation based on metasurfaces has emerged as a powerful platform for spatial differentiation due to its advantage of high integration and parallel processing. However, while most current works focus on one- or two-dimensional (2D) spatial differentiation, three-dimensional (3D) all-optical computation for compact spatial differentiator remains elusive.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!