The ability to engineer nonlinear optical processes in all-dielectric nanostructures is both of fundamental interest and highly desirable for high-performance, robust, and miniaturized nonlinear optical devices. Herein, we propose a novel paradigm fo
r the efficient tuning of second-harmonic generation (SHG) process in dielectric nanoantennas by integrating with chalcogenide phase change material. In a design with Ge$_{2}$Sb$_{2}$Te$_{5}$ (GST) film sandwiched between the AlGaAs nanoantennas and AlO$_{x}$ substrate, the nonlinear SHG signal from the AlGaAs nanoantennas can be boosted via the resonantly localized field induced by the optically-induced Mie-type resonances, and further modulated by exploiting the GST amorphous-to-crystalline phase change in a non-volatile, multi-level manner. The tuning strategy originates from the modulation of resonant conditions by changes in the refractive index of GST. With a thorough examination of tuning performances for different nanoantenna radii, a maximum modulation depth as high as 540$%$ is numerically demonstrated. This work not only reveals out the potential of GST in optical nonlinearity control, but also provides promising strategy in smart designing tunable and reconfigurable nonlinear optical devices, e.g., light emitters, modulators, and sensors.
Promoting performance of generation and transport of hot carriers in metal/semiconductor junctions is critical for harvesting energy of hot carriers. However, the low injection efficiency of hot carriers generated in the commonly used noble metals su
ch as Au hinder the applications of hot-carrier devices. Here, we proposed that metallic TiN might be a better plasmonic material than the noble metals for generating and transporting hot carriers, based on first-principles calculations and Monte Carlo simulations. For the TiN/TiO2 junction, the concentration of hot carriers near the Fermi level is high, the lifetime and mean free path of the hot carriers are long, and the injection efficiency is large. The optimal injection efficiency could be achieved in a core/shell cylindrical TiN/TiO2 junction with the thickness of TiN ~ 5 nm and the incident photon energy ~ 0.6 eV.
Pulsar timing array (PTA) experiments are becoming increasingly sensitive to gravitational waves (GWs) in the nanohertz frequency range, where the main astrophysical sources are the supermassive black hole binaries (SMBHBs) which are expected to resi
de in the centers of galaxies. Some of these individual SMBHBs may power active galactic nuclei (AGNs), and thus their binary parameters could be obtained electromagnetically, which makes it possible to apply electromagnetic (EM) information to aid the search for a GW signal in PTA data. In this work, we investigate the effects of such an EM-informed search on binary detection and parameter estimation by performing mock data analyses on simulated PTA datasets. We find that by applying EM priors, the Bayes factor of the signal increases by a factor of a few to an order of magnitude, and thus an EM-informed targeted search is able to find hints of a signal when an uninformed search fails to find any. By combining EM and GW data, one can achieve an overall improvement in parameter estimation, regardless of the sources sky location or GW frequency. We discuss the implications for the multimessenger studies of SMBHBs with PTAs.
The research of two-dimensional (2D) materials with atomic-scale thicknesses and unique optical properties has become a frontier in photonics and electronics. Borophene, a newly reported 2D material provides a novel building block for nanoscale mater
ials and devices. We present a simple borophene-based absorption structure to boost the light-borophene interaction via critical coupling in the visible wavelengths. The proposed structure consists of borophene monolayer deposited on a photonic crystal slab backed with a metallic mirror. The numerical simulations and theoretical analysis show that the light absorption of the structure can be remarkably enhanced as high as 99.80% via critical coupling mechanism with guided resonance, and the polarization-dependent absorption behaviors are demonstrated due to the strong anisotropy of borophene. We also examine the tunability of the absorption behaviors by adjusting carrier density and lifetime of borophene, air hole radius in the slab, the incident angle and polarization angle. The proposed absorption structure provides novel access to the flexible and effective manipulation of light-borophene interactions in the visible, and shows a good prospect for the future borophene-based electronic and photonic devices.
Enhanced optical absorption in two-dimensional (2D) materials has recently moved into the focus of nanophotonics research. In this work, we present a gain-assisted method to achieve critical coupling and demonstrate the maximum absorption in undoped
monolayer graphene in the near-infrared. In a two-port system composed of photonic crystal slab loaded with graphene, the gain medium is introduced to adjust the dissipative rate to match the radiation rate for the critical coupling, which is accessible without changing the original structural geometry. The appropriate tuning of the gain coefficient also enables the critical coupling absorption within a wide wavelength regime for different coupling configurations. This work provides a powerful guide to manipulate light-matter interaction in 2D materials and opens up a new path to design ultra-compact and high-performance 2D material optical devices.
As vehicles playing an increasingly important role in peoples daily life, requirements on safer and more comfortable driving experience have arisen. Connected vehicles (CVs) can provide enabling technologies to realize these requirements and have att
racted widespread attentions from both academia and industry. These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications. Computation offloading techniques, such as cloud, edge, and fog computing, can help CVs process computation-intensive and large-scale computing tasks. Additionally, different cloud/edge/fog computing architectures are suitable for supporting different types of CV applications with highly different QoS requirements, which demonstrates the importance of the computing architecture design. However, most of the existing surveys on cloud/edge/fog computing for CVs overlook the computing architecture design, where they (i) only focus on one specific computing architecture and (ii) lack discussions on benefits, research challenges, and system requirements of different architectural alternatives. In this paper, we provide a comprehensive survey on different architectural design alternatives based on cloud/edge/fog computing for CVs. The contributions of this paper are: (i) providing a comprehensive literature survey on existing proposed architectural design alternatives based on cloud/edge/fog computing for CVs, (ii) proposing a new classification of computing architectures based on cloud/edge/fog computing for CVs: computation-aided and computation-enabled architectures, (iii) presenting a holistic comparison among different cloud/edge/fog computing architectures for CVs based on functional requirements of CV systems, including advantages, disadvantages, and research challenges.
Printed Mathematical expression recognition (PMER) aims to transcribe a printed mathematical expression image into a structural expression, such as LaTeX expression. It is a crucial task for many applications, including automatic question recommendat
ion, automatic problem solving and analysis of the students, etc. Currently, the mainstream solutions rely on solving image captioning tasks, all addressing image summarization. As such, these methods can be suboptimal for solving MER problem. In this paper, we propose a new method named EDSL, shorted for encoder-decoder with symbol-level features, to identify the printed mathematical expressions from images. The symbol-level image encoder of EDSL consists of segmentation module and reconstruction module. By performing segmentation module, we identify all the symbols and their spatial information from images in an unsupervised manner. We then design a novel reconstruction module to recover the symbol dependencies after symbol segmentation. Especially, we employ a position correction attention mechanism to capture the spatial relationships between symbols. To alleviate the negative impact from long output, we apply the transformer model for transcribing the encoded image into the sequential and structural output. We conduct extensive experiments on two real datasets to verify the effectiveness and rationality of our proposed EDSL method. The experimental results have illustrated that EDSL has achieved 92.7% and 89.0% in evaluation metric Match, which are 3.47% and 4.04% higher than the state-of-the-art method. Our code and datasets are available at https://github.com/abcAnonymous/EDSL .
Theory predicts that a supermassive black hole binary (SMBHB) could be observed as a luminous active galactic nucleus (AGN) that periodically varies on the order of its orbital timescale. In X-rays, periodic variations could be caused by mechanisms i
ncluding relativistic Doppler boosting and shocks. Here we present the first systematic search for periodic AGNs using $941$ hard X-ray light curves (14-195 keV) from the first 105 months of the Swift Burst Alert Telescope (BAT) survey (2004-2013). We do not find evidence for periodic AGNs in Swift-BAT, including the previously reported SMBHB candidate MCG+11$-$11$-$032. We find that the null detection is consistent with the combination of the upper-limit binary population in AGNs in our adopted model, their expected periodic variability amplitudes, and the BAT survey characteristics. We have also investigated the detectability of SMBHBs against normal AGN X-ray variability in the context of the eROSITA survey. Under our assumptions of a binary population and the periodic signals they produce which have long periods of hundreds of days, up to $13$% true periodic binaries can be robustly distinguished from normal variable AGNs with the ideal uniform sampling. However, we demonstrate that realistic eROSITA sampling is likely to be insensitive to long-period binaries because longer observing gaps reduce their detectability. In contrast, large observing gaps do not diminish the prospect of detecting binaries of short, few-day periods, as 19% can be successfully recovered, the vast majority of which can be identified by the first half of the survey.
We present a monolayer black phosphorus (BP)-based metamaterial structure for tunable anisotropic absorption in the mid-infrared. Based on the critical coupling mechanism of guided resonance, the structure realizes the high absorption efficiency of 9
9.65$%$ for TM polarization, while only 2.61$%$ at the same wavelength for TE polarization due to the intrinsic anisotropy of BP. The absorption characteristics can be flexibly controlled by changing critical coupling conditions, including the electron doping of BP, geometric parameters and incident angles of light. The results show feasibility in designing high-performance BP-based optoelectronic devices with spectral tunability and polarization selectivity.
In order to overcome the inherent latency in multi-user unmanned aerial vehicle (UAV) networks with orthogonal multiple access (OMA). In this paper, we investigate the UAV enabled uplink non-orthogonal multiple access (NOMA) network, where a UAV is d
eployed to collect the messages transmitted by ground users. In order to maximize the sum rate of all users and to meet the quality of service (QoS) requirement, we formulate an optimization problem, in which the UAV deployment position and the power control are jointly optimized. This problem is non-convex and some variables are binary, and thus it is a typical NP hard problem. In this paper, an iterative algorithm is proposed with the assistance of successive convex approximate (SCA) technique and the penalty function method. In order to reduce the high computational complexity of the iterative algorithm, a low complexity approximation algorithm is then proposed, which can achieve a similar performance compared to the iterative algorithm. Compared with OMA scheme and conventional NOMA scheme, numerical results show that our proposed algorithms can efficiently improve the sum rate.
