We develop a supervised learning algorithm for photonic spiking neural networks (SNNs) that is founded on the principle of backpropagation. For the supervised learning algorithm, the information is encoded in spike trains of varying intensities, and different spike patterns amongst the output neurons define the SNN training procedure. The classification task within the SNN is numerically and experimentally achieved through the application of a supervised learning algorithm. Photonic spiking neurons, based on vertical-cavity surface-emitting lasers, comprise the structure of the SNN, mirroring the functional characteristics of leaky-integrate-and-fire neurons. The results provide concrete proof of the algorithm's implementation's operation on the hardware. To achieve ultra-low power consumption and ultra-low delay in photonic neural networks, the design and implementation of a hardware-friendly learning algorithm, alongside hardware-algorithm collaborative computing, are of great importance.

The need for a detector that combines a broad operational range with high sensitivity is apparent in the measurement of weak periodic forces. We introduce a force sensor that detects unknown periodic external forces in optomechanical systems. This sensor utilizes a nonlinear dynamical mechanism to lock the amplitude of mechanical oscillations and analyzes the changes in the sidebands of the cavity field. Maintaining the mechanical amplitude locking condition, an unknown external force leads to a linear variation in the locked oscillation amplitude, establishing a direct linear scale between the sensor's sideband response and the force magnitude being measured. In terms of force magnitude measurement, the sensor's linear scaling range aligns precisely with the applied pump drive amplitude, encompassing a wide range. The sensor functions effectively at room temperature thanks to the locked mechanical oscillation's marked resistance to thermal disruptions. Static forces, in addition to weak, cyclical forces, are detectable using the same configuration, although the scope of detection is markedly diminished.

Optical microcavities known as plano-concave optical microresonators (PCMRs) consist of a planar mirror and a concave mirror, separated by a spacer. In the fields of quantum electrodynamics, temperature sensing, and photoacoustic imaging, PCMRs are utilized as sensors and filters, illuminated by Gaussian laser beams. To determine the sensitivity of PCMRs, a model was devised, simulating Gaussian beam propagation through PCMRs, leveraging the ABCD matrix method. Model verification involved comparing interferometer transfer functions (ITFs), calculated for a range of pulse code modulation rates (PCMRs) and beam profiles, with the corresponding experimental data. The model's validity was suggested by the substantial agreement observed. It could thus be a valuable aid in the creation and evaluation of PCMR systems throughout a range of different sectors. The model's underlying computer code has been publicly released online.

Employing scattering theory, we introduce a generalized mathematical model and algorithm for analyzing the multi-cavity self-mixing phenomenon. The pervasive application of scattering theory to traveling waves allows a recursive modeling of self-mixing interference from multiple external cavities, each characterized by individual parameters. The in-depth analysis indicates that the equivalent reflection coefficient for coupled multiple cavities depends on the attenuation coefficient and the phase constant, consequently affecting the propagation constant. A key benefit of recursive modeling is its substantial computational efficiency, particularly when applied to a large quantity of parameters. Ultimately, employing simulation and mathematical modeling, we illustrate how the individual cavity parameters, including cavity length, attenuation coefficient, and refractive index of each cavity, can be adjusted to achieve a self-mixing signal possessing optimal visibility. The proposed model, while primarily intended for biomedical applications involving the probing of multiple diffusive media with varied characteristics, can be adapted for any general setup.

Unpredictable microdroplet movements during LN-based photovoltaic manipulation may contribute to temporary instability and, ultimately, microfluidic process failure. Cryogel bioreactor This paper presents a systematic investigation of the response of water microdroplets to laser illumination on both bare and PTFE-coated LNFe surfaces. The results indicate that the abrupt repulsive behavior is due to an electrostatic transition from dielectrophoresis (DEP) to electrophoresis (EP). Water microdroplet charging, a consequence of Rayleigh jetting from an electrically charged water/oil interface, is proposed as the reason behind the DEP-EP transition. Analyzing the kinetic data of microdroplets against models for their photovoltaic-field motion reveals the charge accumulation on various substrate configurations (1710-11 and 3910-12 Coulombs on bare and PTFE-coated LNFe substrates), demonstrating the prevailing electrophoretic mechanism amidst the presence of both electrophoretic and dielectrophoretic forces. The practical realization of photovoltaic manipulation within LN-based optofluidic chips will depend critically on the outcomes derived from this study.

This paper proposes the preparation of a flexible and transparent three-dimensional (3D) ordered hemispherical array polydimethylsiloxane (PDMS) film for the dual purpose of achieving high sensitivity and uniformity in surface-enhanced Raman scattering (SERS) substrates. Through self-assembly, a single-layer polystyrene (PS) microsphere array is arranged on a silicon substrate, leading to this result. Foscenvivint cost The transfer of Ag nanoparticles onto the PDMS film, characterized by open nanocavity arrays formed by etching the PS microsphere array, is then accomplished through the liquid-liquid interface method. With an open nanocavity assistant, the preparation of a soft SERS sample composed of Ag@PDMS is performed. To simulate the electromagnetic properties of our sample, we relied on Comsol software. Empirical evidence confirms that the Ag@PDMS substrate, incorporating 50-nanometer silver particles, is capable of concentrating electromagnetic fields into the strongest localized hot spots in the spatial region. The Rhodamine 6 G (R6G) probe molecules encounter an exceptionally high sensitivity within the optimal Ag@PDMS sample, resulting in a limit of detection (LOD) of 10⁻¹⁵ mol/L and an enhancement factor (EF) of 10¹². Furthermore, the substrate demonstrates a remarkably consistent signal strength for probe molecules, with a relative standard deviation (RSD) of roughly 686%. Furthermore, the device is adept at discerning the presence of multiple molecules and is capable of performing instantaneous detection on non-planar surfaces.

Electronically reconfigurable transmit arrays (ERTAs) effectively marry the advantages of optical principles and coded metasurface mechanisms to spatial feeding, culminating in dynamic real-time beam manipulation. The intricate design of a dual-band ERTA is complicated by factors such as the substantial mutual coupling arising from dual-band operation, along with the independent phase control required for each band. This paper showcases a dual-band ERTA capable of completely independent beam manipulation across two distinct frequency bands. Within the aperture, two orthogonally polarized reconfigurable elements, arranged in an interleaved structure, create the dual-band ERTA. The utilization of polarization isolation and a cavity, grounded and backed, results in low coupling. For the independent adjustment of the 1-bit phase in each spectral band, a hierarchical bias methodology is expounded upon. A dual-band ERTA prototype, specifically designed, fabricated, and measured, consists of 1515 upper-band elements and 1616 lower-band components, serving as a proof-of-concept demonstration. Bioactivatable nanoparticle Independent manipulation of beams, using orthogonal polarization, has been ascertained through experimental results within the 82-88 GHz and 111-114 GHz frequency bands. The proposed dual-band ERTA, a prospective candidate, could be a viable choice for space-based synthetic aperture radar imaging.

The presented work explores a novel optical system designed for polarization image processing via geometric-phase (Pancharatnam-Berry) lenses. Lenses, acting as half-wave plates, exhibit a quadratic relationship between the fast (or slow) axis orientation and the radial coordinate; left and right circular polarizations have identical focal lengths, but with opposite signs. Accordingly, the input collimated beam was bifurcated into a converging beam and a diverging beam, bearing opposite circular polarizations. Optical processing systems, through coaxial polarization selectivity, gain a new degree of freedom, which makes it very appealing for applications such as imaging and filtering, particularly those which require polarization sensitivity. From these properties, a polarization-sensitive optical Fourier filter system is devised. A telescopic system grants access to two distinct Fourier transform planes, one allocated to each circular polarization. A second, symmetrical optical system is employed to merge the two light beams into a single final image. As a result, polarization-sensitive optical Fourier filtering can be employed, as demonstrated using uncomplicated bandpass filters.

For realizing neuromorphic computer hardware, analog optical functional elements, characterized by their high parallelism, rapid processing, and low power consumption, provide promising approaches. Analog optical implementations are facilitated by convolutional neural networks, leveraging the Fourier transform properties of strategically designed optical systems. Implementing optical nonlinearities within these neural network structures presents considerable challenges for efficiency. We investigate a three-layer optical convolutional neural network, utilizing a 4f imaging system for the linear stage, with the introduction of optical nonlinearity achieved through the absorption profile of a cesium atomic vapor cell.