Recently, the study of acoustic vortex beams has attracted a great attention owing to its potential applications in medical ultrasound imaging and trapping particles. In some special applications of medical ultrasound, it generally needs the simultaneous realization of vortex focusing and asymmetric propagation in three-dimensional (3D) space. However, the design of a two-dimensional (2D) device with asymmetric acoustic vortex focusing (AAVF) remains a challenge. To overcome it, we experimentally demonstrate a 2D AAVF lens composed of three types of binary-phase mode converters. By simultaneously introducing the phase profiles of acoustic focusing and vortex caused by the mode converters, we design a 2DAAVF lens with the topological charge n = 2, i.e., the sound energy can pass through the lens from the upper side and forms a vortex focus in 3D space; however, it cannot transmit through the lens from the other side. The vortex focusing and asymmetric transmission arise from the phase manipulation and the conversion between the zero-order and first-order waves caused by the mode converters, respectively. The measured fractional bandwidth can reach about 0.19. The proposed lens has the advantages of high-performance AAVF, broad bandwidth and complex sound modulation in 3D space, which provides diverse routes for designing 3D multi-functional sound devices with promising applications in medical ultrasound.

Nonlinear photonic sources including semiconductor lasers have been recently utilized as ideal computation elements for information processing. They supply energy-efficient way and rich dynamics for classification and recognition tasks. In this work, we propose and numerically study the dynamics of complex photonic systems including high-β laser element with delayed feedback and functional current modulation, and employ nonlinear laser dynamics of near-threshold region for the application in reservoir computing. The results indicate a perfect (100%) recognition accuracy for the pattern recognition task and an accuracy about 98% for the Mackey-Glass chaotic sequences prediction. Therefore, the system shows an improvement of performance with low-power consumption. In particular, the error rate is an order of magnitude smaller than previous works. Furthermore, by changing the DC pump, we are able to modify the number of spontaneous emission photons of the system, which then allows us to explore how the laser noise impacts the performance of the reservoir computing system. Through manipulating these variables, we show a deeper understanding on the proposed system, which is helpful for the practical applications of reservoir computing.

Light is widely used in life science in both controlling and observing biological processes, yet a long-standing challenge of using light inside the tissue lies in the limited penetration depth of visible light. In the past decade, many in vivo light delivery methods using photonics and materials science tools have been developed, with recent demonstrations of non-invasive, deep-tissue light sources based on systemically delivered luminescent nanomaterials. In this perspective, we provide an overview for the principles of intravital nanoscopic light sources and discuss their advantages over existing methods for in vivo light delivery. We then highlight their recent applications in optogenetics neuromodulation and fluorescent imaging in live animals. We also present an outlook section about the feasibility of combining these non-invasive light sources with other modalities to expand the utilities of light in biology.

In this work, we propose a highly sensitive temperature sensor based on photonic spin Hall effect (PSHE). We find that, by involving the liquid crystal (LC) material, the spin spatial and angular shifts in PSHE are very sensitive to the tiny perturbation of temperature when the incident angle of light beam is near the Brewster and critical angles. Importantly, the phase transition from liquid crystal state to liquid state across the clearing point (CP) will lead to the transition of strong spin-orbit interaction to the weak one. During this process, we reveal that the sensitivity of our designed temperature sensor can reach a giant value with 8.27 cm/K which is one order of magnitude improvement compared with the previous Goos-Hänchen effect-based temperature sensor. This work provides an effective method for precisely determining the position of CP and actively manipulating the spin-orbit interaction.

The concentration induced permittivity change involves a dispersion which occurs at the resonant frequency, and is often not predictable by simulation using the traditional Cole-Cole model. To overcome this problem, a new Lorentz's model is proposed as a substitute for the Cole-Cole model. Under this new model, the glucose concentration is expected to be measured at the contact interface in the form of a resonant frequency shift. With the help of the model, a contact-based meander-line antenna sensor (CMS) is realized with a high ``sensitivity of 1.3158 dB/(mmol/L) in terms of d |S<sub>11</sub>|/dC, or of 17~18 MHz/(mmol/L) in terms of'' dω/dC. The model has been experimentally validated with in-vitro measurements and for proof-of-concept with in-vivo clinical investigations in the microwave frequency. Consistent with the predictions of model, a linear ``correlation is observed not only between the resonant frequency shift and the glucose concentration, but also between the S-parameters magnitude and glucose'' concentration.

In recent years, topological states in photonic artificial structures have attracted great attention due to their robustness against certain disorders and perturbations. To readily understand the underlying principles, topological edge modes in one-dimensional (1D) system have been widely investigated, which bring aboutthe discovery of novel optical phenomena and devices. In this article, we review our recent advances in topological edge modes. We introduce the connection between topological orders and effective electromagnetic parameters of photonic artificial structures in band gaps, discuss experimental demonstration of robust topological modes and their potential applications in wireless power transfer, sensing and field of optics, and give a brief introduction of future opportunities in 1D topological photonics.

Microwave staring correlated imaging (MSCI) is a super-resolution imaging technique based on temporal-spatial stochastic radiation fields (TSSRFs), which requires an accurate calculation of the electromagnetic field at the imaging plane. However, systematic errors always exist in practice, such as the time synchronization and frequency synchronization errors of radar systems, which make it difficult to calculate the required TSSRFs accurately, and this deteriorates the imaging results. Meanwhile, some imaging algorithms have problems such as high computational complexity. In this paper, an intelligent MSCI method based on the deep neural network (DNN) is proposed, which can accomplish imaging directly from the echoes, avoiding the computation of TSSRFs. A multi-level residual convolutional neural network (MRCNN) is developed for the DNN, and simulations and experiments are carried out to obtain the dataset for training and testing the MRCNN. Compared with the conventional MSCI methods, the imaging results verify the effectiveness of intelligent MSCI in terms of imaging quality and computational efficiency.

As one of the most important technologies for the next generation very-large scale integrated circuit fabrication, extreme ultraviolet (EUV) lithography has attracted more and more attention in recent years. However, in EUV lithography, the optical distortion of the printed image on wafer always has negative impacts on the imaging performance. Thus, to enhance the imaging performance of EUV system, especially for small critical dimensions, in this work, a novel optical proximity correction (OPC) system based on the deep learning technique is proposed. It includes a forward module and an inverse module, where the forward module is employed to fast and accurately map the mask to the corresponding near field of the plane above the stack to help the construction of training dataset for the inverse module operation, and the inverse module is employed to fast and accurately map the target printed image to the corrected mask. Numerical examples demonstrate that compared with traditional full-wave simulation, the forward module can greatly improve the computational efficiency including the required running time and memory. Meanwhile, different from time consuming iterative OPC methods, the corrected mask can be immediately obtained as the target printed image is input using the trained inverse module.

We extended the previous 2D method of BBGF-MST (Broadband Green's function-Multiple Scattering Theory) approach to 3D problems in periodic structures. Band Structures and Band Field Solutions are calculated. A feature of BBGF is that the lattice Green's functions are broadband so that the coefficients of the spherical wave expansions are calculated rapidly for many frequencies. These are then used for speedy calculations of the matrix elements of the KKR (Korringa-Kohn-Rostoker) eigenvalue equation. Using BBGF-MST, a low order matrix eigenvalue equation for the bands is derived. For the first two bands, the dimension of the KKR matrix equation is only 4 by 4. With the use of BBGF, the CPU requirement for the BBGF-MST technique is 0.27 secondson a standard laptop for solving the KKR eigenvalue equation. Numerical results of the band diagrams are illustrated. Higher order spherical waves are next used to calculate the normalized band field solutions for the entire cell.

Optical analog computing has recently sparked growing interest due to the appealing characteristics of low energy consumption, parallel processing, and ultrafast speed, spawning it complementary to conventional electronic computing. As the basic computing unit, optical logic operation plays a pivotal role for integrated photonics. However, the reported optical logic operations are volumetric and single-functional, which considerably hinders the practical cascadability and complex computing requirement. Here, we propose an on-chip combinational optical logic circuit using inverse design. By precisely engineering the scattering matrix of each small-footprint logic gate, all basic optical logic gates (OR, XOR, NOT, AND, XNOR, NAND, and NOR) are realized. On this foundation, we explore the assembly of these basic logic gates for general-purpose combinational logic circuits, including optical half-adder and code converter. Our work provides a path for the development of integrated, miniaturized, and cascadable photonic processor for future optical computing technologies.