We investigate the generation and enhancement of bipartite and tripartite entanglement in an optomechanical ring cavity containing an intracavity optical parametric amplifier (OPA). The system consists of three movable charged mirrors coupled to a single cavity mode through geometry-dependent radiation pressure, while the mechanical resonators are directly coupled through Coulomb interaction. Starting from the total Hamiltonian, we derive the quantum Langevin equations and linearize the dynamics around the steady state. The stationary covariance matrix is then obtained from the Lyapunov equation and used to quantify the quantum correlations through the logarithmic negativity and the minimum residual contangle. Our results show that the cavity–mechanical entanglement is strongly affected by the effective detuning, temperature, OPA gain, pump phase, and Coulomb coupling. The central mechanical resonator exhibits the strongest and most robust entanglement with the cavity field, owing to its larger geometry-dependent radiation-pressure coupling, while the mechanical entanglement is obtained between the two outer mirrors. We also show that the OPA can enhance both bipartite and tripartite correlations when its gain and phase are properly tuned within the stable parameter region. In particular, the hybrid subsystem formed by the central mirror, the third mirror, and the cavity field provides the strongest tripartite entanglement. The limiting cases confirm that the correlation structure arises from the cooperative action of the phase-sensitive OPA and the asymmetric three-link Coulomb configuration. These results highlight the usefulness of combining parametric amplification, Coulomb coupling, and the rhombus geometry as complementary mechanisms for controlling multipartite quantum correlations in optomechanical ring cavities.
This novel research clarifies the effect of incorporating of monometallic Copper nanoparticles CuNPs and Aluminium nanoparticles AlNPs and bimetallic surface CuNPs/ AlNPs on the performance of nano-PSi gas sensor. Crystalline silicon wafers were employed to synthesise the nano-PSi layer via the laser-assisted electrochemical etching (LAEE) methodology, utilising a laser wavelength of 410nm and an intensity of 25mW/cm². AlNPs/nano-PSi, CuNPs/nano-PSi, and CuNPs/AlNPs/nano-PSi were the three different hybrid gas sensor structures that were created by reducing ions from AlCl₃·6H₂O and CuSO₄·5H₂O in a 1:1 solution combination using a simple ion reduction procedure. The characteristics of these hybrid structures were systematically examined employing FE-SEM, FTIR, XRD, and EDS analyses. When compared to both monometallic variants and the as-prepared nano-PSi, the results of the bi-metallic surface of CuNPs/AlNPs/nano-PSi showed a significant decrease in temporal response and a noticeable improvement in sensitivity. There was a 55% reduction in response time and a 58% reduction in recovery time. Sensitivity showed an improvement of over 100% when compared to the nano-PSi sensor as prepared. This enhancement in the performance of the bi-metallic surface of CuNPs/AlNPs can be attributed to the elevated surface area and surface density characteristic of the bimetallic nanoparticles.
We study the fourth-order nonlinear Schrödinger (FONLS) equation that contains higher-order dispersion effects. The equation models ultrashort light pulses in optical fibers. First, we use traveling wave reduction. This turns the partial differential equation into a fourth-order ordinary differential equation. Then we apply the tanh, coth, and sech methods. We find exact solitary wave solutions, including bright and singular solitons, together with their parameter conditions. Next, we work with inhomogeneous media. We develop a new similarity transformation. This transformation connects the constant-coefficient equation to the variable-coefficient equation. It gives nonautonomous solitons. These solitons show how nonlinearity and higher-order dispersion balance each other. This helps in the design of advanced optical systems.
This paper presents a performance analysis of Faster-Than-Nyquist (FTN) signaling in Cooperative Non-Orthogonal Multiple Access (C-NOMA) over Visible Light Communication (VLC) channels. A comparative evaluation is carried out for FTN C-NOMA, Nyquist C-NOMA, FTN-NOMA, and Nyquist-NOMA, considering achievable rate, Bit Error Rate (BER), Outage Probability (OP), Spectral Efficiency (SE), Energy Efficiency (EE), and Signal-to-Interference-plus-Noise Ratio (SINR). The system incorporates transmitter angle diversity, receiver-side Maximum Ratio Combining (MRC), and Successive Interference Cancellation (SIC), with performance compared for cases with and without MRC. The results indicate that FTN C-NOMA enhances SE and EE while maintaining favorable BER and OP performance. The proposed VLC-based FTN C-NOMA design achieves outage probabilities (OPs) in the range of - at an SINR of 15 dB under a deterministic line-of-sight (LOS) Lambertian channel model. These results correspond to idealized VLC operating conditions and should therefore be interpreted as upper-bound system performance.
A transmission-type and polarization-insensitive metalenses are designed in the terahertz band based on the theory of phase propagation and the wavefront of electromagnetic wave is controlled by optimizing the cross-shaped elliptical pillar meta-unit, The metalenses use Silicon as the atom unit material and Polymer as the substrate material. The radius of the metalenses is 11mm, the incident frequency is 0.4THz, the numerical aperture is 0.69, and the efficiency of focus is 51.4%. Furthermore, metalenses exhibit the proportional relation between the focal length and the surrounding refractive index of 1-1.6, and inversely proportional relation between the focal length and the incident band of 0.7~0.8mm, these results validate the designed metalenses have a zoom function.
Two-dimensional (2D) photonic crystals (PhCs)-based photonic sensors have fascinated a lot of concentration in cancer detection throughout the last 20 years. These days, this technique is an essential tool for early cancer detection and monitoring of therapy response since it can identify even the smallest changes in biomarkers molecular interactions and concentrations. This work to detect oral cancer cells in a sample, a novel biosensor based on a 2D PhC was designed and simulated. It is constructed with silicon in air using the FEM. To find out whether the test sample comprised cancerous cells, the transmission spectrum fluctuation was examined. The sensitivity of the sensor, which is essential for the accurate identification of cancer cells, was increased by carefully altering its structural properties. For this structure it had a high sensitivity of 1000 and Q-factor 2283. For further classification probability of the cell with the cancer can be detected using a logistic regression method. Different types of graphs are used for Type A, B, C, D, E cell classification using logistic regression method. Photonic logistic regression model has an accuracy of 100%. In this study usage of photonics and machine learning develops a reliable diagnostic tool for oral cancer detection. Logistic regression-based classification gives the probability of the of disease which enables the risk satisfaction.
