This paper presents a comprehensive investigation of a concurrent electro-optical up- and down-conversion architecture based on a semiconductor optical amplifier Mach–Zehnder interferometer (SOA-MZI) operating under a differential modulation configuration. The proposed system employs a high-repetition-rate optical pulse clock (OPC) to generate the sampling control signal required for concurrent frequency conversion. A 4096-QAM data signal modulated at 100 GHz is simultaneously up- and down-converted at the SOA-MZI output through the interaction between the optical sampling signal and the electrically driven SOA branches. The influence of the OPC repetition rate and pulse width on the conversion performance is experimentally analyzed. By increasing the sampling repetition rate to 150 GHz with a pulse width of 0.5 ps, concurrent frequency conversion is achieved over a wide frequency range extending up to 1.6 THz. The performance of the converted signals is evaluated using error vector magnitude (EVM) measurements and temporal characterization. For the up-converted replicas, an EVM of 5.5% is obtained at 1.6 THz for a 1 Tbit/s 4096-QAM transmission. For the down-converted replica at 50 GHz, the EVM reaches 4% at a data rate of 10 Tbit/s. In addition, pulse compression based on a parallel grating pair connected by a 3 km optical fiber is investigated for temporal characterization of the concurrent signal. A compressed pulse width of 45 fs is achieved at full width at half maximum (FWHM). Experimental results demonstrate that the proposed electro-optical SOA-MZI differential modulation architecture provides improved conversion efficiency, reduced noise floor, ultra-wide frequency operation, and high-capacity data transmission capability, making it suitable for terahertz communications, microwave photonics, and ultra-high-speed optical transmission systems.
In this paper, a hybrid radiofrequency/free space optics (RF/FSO) system is considered. The Nakagami-m distribution model was used to describe the RF section in the hybrid system, while the FSO section was described by the Gamma–Chi-square model. The Gamma–Chi-square model is based on the existing FSO channel models of Gamma distribution and Rician distribution. An expression for the outage probability is analytically derived for the considered hybrid RF/FSO system. Numerical results are presented graphically for various system parameters: Nakagami fading parameter m, outage threshold, average signal-to-noise ratio (SNR), Rician factor K, FSO link distance and different atmospheric turbulence levels. Based on the obtained results, it is possible to design hybrid RF/FSO systems with optimal parameters for obtaining the best possible signal transmission performance.
Binocular vision is widely used in structured-light three-dimensional measurement and industrial inspection. However, reliable stereo correspondence for repeated dot-matrix patterns remains challenging because neighboring dots are visually similar. To address this problem, this study proposes a topology-constrained binocular correspondence method integrating ordered grid localization with calibration-disparity-guided local search. An ordered lattice is constructed in the right view to provide refined dot locations and consistent spatial indices. A fixed disparity derived from stereo calibration is then used to restrict correspondence search to local regions in the rectified left view, reducing ambiguity among neighboring dots. Experiments on 20 stereo image pairs acquired from two stationary planar surfaces showed that the proposed method recovered all 121 lattice points in every acquisition, achieving 100% precision, recall, and F1 under a topology-derived reference-label protocol. Compared with a calibration-disparity global baseline using the same fixed disparity prior, the proposed method reduced the mean least-squares-plane residual standard deviation by 95.1% and 95.7% on the gray metal surface and white board, respectively, while reducing the mean residual peak-to-valley value by 94.5% on both surfaces. A controlled component study confirmed the complementary contributions of grid constraints and local association. Additional evaluations showed closer agreement with a screened coordinate measuring machine reference and complete lattice correspondence recovery at 50% linear image resolution. These results demonstrate that integrating ordered topology with calibration-guided local search improves stereo correspondence reliability and planar reconstruction consistency for repeated dot-matrix structured-light patterns.
Photonic platforms are strong candidates for scalable quantum information processing because the photonic circuit itself operates at room temperature, its qubits are largely immune to thermal decoherence, and the platform is compatible with existing fiber and CMOS infrastructure. The dominant error channel in these platforms is not decoherence but optical loss, which makes the quality of the guiding material the limiting factor when quantum optics experiments are translated from free-space benches to integrated circuits. A free-space heralded single-photon quantum eraser at 810 nm restores a fringe visibility of 0.900 ± 0.012 from 0.060 ± 0.002 and sets the specification for the thin film. This work reports a plasma-enhanced atomic layer deposition (PEALD) process for silicon nitride (SixNy) from bis(diethylamino)silane (BDEAS) and N2-plasma, developed to supply the core of such waveguides. At 810 nm, the thin film reaches a refractive index of 1.824, and the Urbach term of the ellipsometric fit gives an extinction coefficient of 7.9 × 10−10. Also, hard X-ray photoelectron spectroscopy shows an N:Si ratio of 1.16 with 12.7% carbon. Furthermore, the SixNy waveguide core can be clad with a lower refractive index thin film of SiO2 by the same process.
To address the low contrast of X-ray weakly absorbing materials, phase retrieval (PR) is employed for contrast enhancement and material identification but inevitably leads to structural blurring and boundary smoothing due to its equivalent low-pass filtering. A space–frequency physics-guided neural network (SF-PGNet) is proposed to improve the reconstruction quality of phase-sensitive hard X-ray tomography without additional hardware assistance for weakly absorbing materials. It consists of three sub-networks: (i) the spatial-domain network (SD-Net) predicts a projection-conditioned effective deconvolution kernel (PSF_N) from the measured projection, using the experimentally calibrated effective kernel PSFtot as physical supervision, and applies PSF_N to obtain a sharpness-enhanced sub-image; (ii) the frequency-domain network (FD-Net) predicts the inverse transfer function HN−1 from the measured projection, using analytical H−1(γ) functions generated from physically selected phase-retrieval parameters as supervision, and generates a phase-contrast-enhanced sub-image; and (iii) the dual-domain fusion network integrates the complementary sub-images to produce the final reconstruction. Validation on a polymer phantom and testing on a biological specimen demonstrate that SF-PGNet enhances material contrast and boundary representation, while the learned spatial- and frequency-domain branches remain highly consistent with their corresponding physics-based correction references.
