Optical Computing: Status and Perspectives

Optical directional differential operation enabled visual chirality detection

Directional differential operation can extract the changes of directional information from complex signals, and plays an important role in target recognition and texture image processing. Here, we propose an optical directional differential operation based on large cross-polarization rotation, and realize the visual detection of chiral enantiomers. By using cross-polarization rotation in a specified direction, we design a corresponding directional spatial spectral transfer function whose transmission efficiency increases as the incident angle approaches the Brewster angle. The differential direction can be adjusted by changing the initial polarization state, and can be used to detect the concentration of chiral solutions. Finally, we apply the directional differential operation to achieve the visual detection of chiral enantiomers.

Reconfigurable metamaterial processing units that solve arbitrary linear calculus equations

Calculus equations serve as fundamental frameworks in mathematics, enabling describing an extensive range of natural phenomena and scientific principles, such as thermodynamics and electromagnetics. Analog computing with electromagnetic waves presents an intriguing opportunity to solve calculus equations with unparalleled speed, while facing an inevitable tradeoff in computing density and equation reconfigurability. Here, we propose a reconfigurable metamaterial processing unit (MPU) that solves arbitrary linear calculus equations at a very fast speed. Subwavelength kernels based on inverse-designed pixel metamaterials are used to perform calculus operations on time-domain signals. In addition, feedback mechanisms and reconfigurable components are used to formulate and solve calculus equations with different orders and coefficients. A prototype of this MPU with a compact planar size of 0.93λ0×0.93λ0 (λ0 is the free-space wavelength) is constructed and evaluated in microwave frequencies. Experimental results demonstrate the MPU's ability to successfully solve arbitrary linear calculus equations. With the merits of compactness, easy integration, reconfigurability, and reusability, the proposed MPU provides a potential route for integrated analog computing with high speed of signal processing.

Multiphysics simulations of a cylindrical waveguide optical switch using phase change materials on silicon

This work presents the design and multiphysics simulation of a cylindrical waveguide-based optical switch using germanium-antimony-tellurium (GST) as an active phase change material. The innovative cylindrical architecture is theoretically analyzed and evaluated at 1550 nm wavelength for telecommunication applications. The dispersion relation is derived analytically for the first time to model the optical switch, while finite element method (FEM) and finite difference time domain (FDTD) techniques are utilized to simulate the optical modes, light propagation, and phase change dynamics. The fundamental TE01 and HE11 modes are studied in detail, enabling switching between low-loss amorphous and high-loss crystalline GST phases. Increasing the GST thickness is found to increase absorption loss in the crystalline state but also slows down phase transition kinetics, reducing switching speeds. A 10 nm GST layer results in competitive performance metrics of 0.79 dB insertion loss, 13.47 dB extinction ratio, 30 nJ average power consumption, and 3.5 Mb/s bit rate. The combined optical, thermal, and electrical simulation provides comprehensive insights towards developing integrated non-volatile photonic switches and modulators utilizing phase change materials.

Exploring Types of Photonic Neural Networks for Imaging and Computing-A Review

Photonic neural networks (PNNs), utilizing light-based technologies, show immense potential in artificial intelligence (AI) and computing. Compared to traditional electronic neural networks, they offer faster processing speeds, lower energy usage, and improved parallelism. Leveraging light's properties for information processing could revolutionize diverse applications, including complex calculations and advanced machine learning (ML). Furthermore, these networks could address scalability and efficiency challenges in large-scale AI systems, potentially reshaping the future of computing and AI research. In this comprehensive review, we provide current, cutting-edge insights into diverse types of PNNs crafted for both imaging and computing purposes. Additionally, we delve into the intricate challenges they encounter during implementation, while also illuminating the promising perspectives they introduce to the field.

A Review on Photonic Sensing Technologies: Status and Outlook

In contemporary science and technology, photonic sensors are essential. They may be made to be extremely resistant to some physical parameters while also being extremely sensitive to other physical variables. Most photonic sensors may be incorporated on chips and operate with CMOS technology, making them suitable for use as extremely sensitive, compact, and affordable sensors. Photonic sensors can detect electromagnetic (EM) wave changes and convert them into an electric signal due to the photoelectric effect. Depending on the requirements, scientists have found ways to develop photonic sensors based on several interesting platforms. In this work, we extensively review the most generally utilized photonic sensors for detecting vital environmental parameters and personal health care. These sensing systems include optical waveguides, optical fibers, plasmonics, metasurfaces, and photonic crystals. Various aspects of light are used to investigate the transmission or reflection spectra of photonic sensors. In general, resonant cavity or grating-based sensor configurations that work on wavelength interrogation methods are preferred, so these sensor types are mostly presented. We believe that this paper will provide insight into the novel types of available photonic sensors.

Polarization-Sensitive Patterning of Azopolymer Thin Films Using Multiple Structured Laser Beams

The polarization sensitivity of azopolymers is well known. Therefore, these materials are actively used in many applications of photonics. Recently, the unique possibilities of processing such materials using a structured laser beam were demonstrated, which revealed the key role of the distribution of polarization and the longitudinal component of light in determining the shape of the nano- and microstructures formed on the surfaces of thin azopolymer films. Here, we present numerical and experimental results demonstrating the high polarization sensitivity of thin azopolymer films to the local polarization state of an illuminating structured laser beam consisting of a set of light spots. To form such arrays of spots with a controlled distribution of polarization, different polarization states of laser beams, both homogeneous and locally inhomogeneous, were used. The results obtained show the possibility of implementing a parallel non-uniform patterning of thin azopolymer films depending on the polarization distribution of the illuminating laser beam. We believe that the demonstrated results will not only make it possible to implement the simultaneous detection of local polarization states of complex-shaped light fields but will also be used for the high-performance fabrication of diffractive optical elements and metasurfaces.

Dividing the Topological Charge of a Laguerre-Gaussian Beam by 2 Using an Off-Axis Gaussian Beam

In optical computing machines, many parameters of light beams can be used as data carriers. If the data are carried by optical vortices, the information can be encoded by the vortex topological charge (TC). Thus, some optical mechanisms are needed for performing typical arithmetic operations with topological charges. Here, we investigate the superposition of a single-ringed (zero-radial-index) Laguerre-Gaussian (LG) beam with an off-axis Gaussian beam in the waist plane. Analytically, we derive at which polar angles intensity nulls can be located and define orders of the optical vortices born around these nulls. We also reveal which of the vortices contribute to the total TC of the superposition and which are compensated for by the opposite-sign vortices. If the LG beam has a TC of m, TC of the superposition is analytically shown to equal [m/2] or [m/2] + 1, where [] means an integer part of the fractional number. Thus, we show that the integer division of the TC by two can be done by superposing the LG beam with an off-axis Gaussian beam. Potential application areas are in optical computing machines and optical data transmission.

Flexible Transient Resistive Memory Based on Biodegradable Composites

Physical transient electronics have attracted more attention as the basis for building green electronics and biomedical devices. However, there are difficulties in selecting materials for the fabricated devices to take into account both biodegradability and high performance. In this paper, a physically transient resistive random-access memory (RRAM) device was fabricated by using egg protein and graphene quantum dot composites as active layers. The sandwich structure composed of Al/EA:GQD/ITO shows a good write-once-multiple-read memory characteristic, and the introduced GQD improves the switching current ratio of the device. By using the sensitivity of GQDs to ultraviolet light, the logic operation of the "OR gate" is completed. Furthermore, the device exhibits a physical transient behavior and good biodegradability due to the dissolution behavior in deionized water. These results suggest that the device is a favorable candidate for the construction of memory elements for transient electronic systems.