arXiv subjects

Tingting Liu

Publications and source records attributed to Tingting Liu.

At least 127 records · Page 7Linked to original sources

arXiv2020

Active control of electromagnetically induced transparency analogue in all-dielectric metamaterials loaded with graphene

Electromagnetically induced transparency (EIT) analogue in all-dielectric metamaterials with a high quality factor provides an effective route to enhance light-matter interaction at the nanoscale. In particular, the active control applied to it enables great degree of freedom for spatial light modulation and thus promises functional device applications with high flexible tunability. Here we load graphene into all-dielectric metamaterials and realize the remarkably high modulation depth in the transmission amplitude of the EIT resonance with the manipulation of graphene conductivity, via shifting the Fermi level or altering the layer number. The physical origin lies in the controllable light absorption through the interband loss of graphene in the near infrared. This work reveals a strategically important interaction mechanism between graphene and EIT resonance in all-dielectric metamaterials, and open avenues in designing a family of hybrid metadevices that permit promising applications to light modulation, switching and ultrasensitive biosensing.

physics.optics↗

arXiv2020

EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition

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 recommendation, 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 .

cs.CV↗

arXiv2020

Engineering light absorption at critical coupling via bound states in the continuum

Recent progress in nanophotonics is driven by the desire to engineer light-matter interaction in two-dimensional (2D) materials using high-quality resonances in plasmonic and dielectric structures. Here, we demonstrate a link between the radiation control at critical coupling and the metasurface-based bound states in the continuum (BIC) physics, and develop a generalized theory to engineer light absorption of 2D materials in coupling resonance metasurfaces. In a typical example of hybrid graphene-dielectric metasurfaces, we present the manipulation of absorption bandwidth by more than one order of magnitude by simultaneously adjusting the asymmetry parameter of silicon resonators governed by BIC and the graphene surface conductivity while the absorption efficiency maintains maximum. This work reveals the generalized role of BIC in the radiation control at critical coupling and provides promising strategies in engineering light absorption of 2D materials for high-efficiency optoelectronics device applications, e.g., light emission, detection and modulation.

physics.optics↗

arXiv2020

Regional Robust Secure Precise Wireless Transmission Design for Multi-user UAV Broadcasting System

In this paper, two regional robust secure precise wireless transmission (SPWT) schemes for multi-user unmanned aerial vehicle (UAV) :1) regional signal-to-leakage-and-noise ratio (SLNR) and artificial-noise-to-leakage-and-noise ratio (ANLNR) (R-SLNR-ANLNR) maximization and 2) point SLNR and ANLNR (P-SLNR-ANLNR) maximization, are proposed to tackle with the estimation errors of the target users' location. In SPWT system, the estimation error for SPWT can not be ignored. However the conventional robust methods in secure wireless communications optimize the beamforming vector in the desired positions only in statistical means and can not guarantee the security for each symbol. Proposed regional robust schemes are designed for optimizing the secrecy performance in the whole error region around the estimated location. Specifically, with known maximal estimation error, we define target region and wiretap region. Then design an optimal beamforming vector and an artificial noise projection matrix, which achieve the confidential signal in the target area having the maximal power while only few signal power is conserved in the potential wiretap region. Instead of considering the statistical distributions of the estimated errors into optimization, we optimize the SLNR and ANLNR of the whole target area, which significantly decreases the complexity. Moreover, the proposed schemes can ensure that the desired users are located in the optimized region, which are more practical than conventional methods. Simulation results show that our proposed regional robust SPWT design is capable of substantially improving the secrecy rate compared to the conventional non-robust method. The P-SLNR-ANLNR maximization-based method has the comparable secrecy performance with a lower complexity than that of the R-SLNR-ANLNR maximization-based method.

eess.SP↗

arXiv2020

The BAT AGN Spectroscopic Survey -- XVIII. Searching for Supermassive Black Hole Binaries in the X-rays

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 including 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.

astro-ph.HE↗

arXiv2020

Learning Vertex Representations for Bipartite Networks

Recent years have witnessed a widespread increase of interest in network representation learning (NRL). By far most research efforts have focused on NRL for homogeneous networks like social networks where vertices are of the same type, or heterogeneous networks like knowledge graphs where vertices (and/or edges) are of different types. There has been relatively little research dedicated to NRL for bipartite networks. Arguably, generic network embedding methods like node2vec and LINE can also be applied to learn vertex embeddings for bipartite networks by ignoring the vertex type information. However, these methods are suboptimal in doing so, since real-world bipartite networks concern the relationship between two types of entities, which usually exhibit different properties and patterns from other types of network data. For example, E-Commerce recommender systems need to capture the collaborative filtering patterns between customers and products, and search engines need to consider the matching signals between queries and webpages.

cs.SI↗

arXiv2019

Tunable anisotropic absorption in monolayer black phosphorus using critical coupling

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 99.65$\%$ 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.

physics.optics↗

arXiv2019

Tunable anisotropic perfect absorption in hyperbolic metamaterials based on black phosphorous/dielectric multilayer structures

Black phosphorus (BP) as a promising two-dimensional material with extraordinary optical properties constitutes an excellent building block in multilayer hyperbolic metamaterials. In this work, we design a multilayer structure composed of BP/dielectric layer stacking unit cells patterned on a gold mirror and theoretically demonstrate the tunable anisotropic absorption in the infrared regime. The electric dipole resonance between the adjacent unit cells drives the structure in the critical coupling state, and impedance of the structure matches to that of free space, showing the perfect absorption for one polarization direction, while the impedance mismatch for the other polarization direction leads to only 8.2$\%$ absorption at the same wavelength. The anisotropic absorption response of the proposed structure can be attributed to the intrinsic anisotropy of BP, which exhibits few dependence on the incident angle. Furthermore, we investigate the tunable optical absorption of the proposed structure with the electron doping of BP and the geometric parameters. These results demonstrate great potentials of BP in constituting multilayer hyperbolic metamaterials, and open up avenues in designing anisotropic metadevices with tunable spectral and polarization selectivity in the infrared regime.

physics.optics↗

arXiv2019

UAV-Enabled Uplink Non-Orthogonal Multiple Access System: Joint Deployment and Power Control

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 deployed 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.

eess.SP↗

arXiv2019

Black phosphorus-based anisotropic absorption structure in the mid-infrared

Black phosphorus (BP), an emerging two-dimensional (2D) material with intriguing optical properties, forms a promising building block in optics and photonics devices. In this work, we propose a simple structure composed of BP sandwiched by polymer and dielectric materials with low index contrast, and numerically demonstrate the perfect absorption mechanism via the critical coupling of guided resonances in the mid-infrared. Due to the inherent in-plane anisotropic feature of BP, the proposed structure exhibits highly polarization-dependent absorption characteristics, i.e., the optical absorption of the structure reaches 99.9$\%$ for TM polarization and only 3.2$\%$ for TE polarization at the same wavelength. Furthermore, the absorption peak and resonance wavelength can be flexibly tuned by adjusting the electron doping of BP, the geometrical parameters of the structure and the incident angles of light. With high efficiency absorption, the remarkable anisotropy, flexible tunability and easy-to-fabricate advantages, the proposed structure shows promising prospects in the design of polarization-selective and tunable high-performance devices in the mid-infrared, such as polarizers, modulators and photodetectors.

physics.optics↗

arXiv2019

Transmit Antenna Selection and Beamformer Design for Secure Spatial Modulation with rough CSI of Eve

The security of spatial modulation (SM) aided networks can always be improved by reducing the desired link's power at the cost of degrading its bit error ratio performance and assuming the power consumed to artificial noise (AN) projection (ANP). We formulate the joint optimization problem of maximizing the secrecy rate (Max-SR) over the transmit antenna selection and ANP in the context of secure SM-aided networks, which is mathematically a non-linear mixed integer programming problem. In order to solve this problem, we provide a pair of solutions, namely joint and separate solutions. Specifically, an accurate approximation of the SR is used for reducing the computational complexity, and the optimal AN covariance matrix (ANCM) is found by convex optimization for any given active antenna group (AAG). Then, given a large set of AAGs, simulated annealing mechanism is invoked for optimizing the choice of AAG, where the corresponding ANCM is recomputed by this optimization method as well when the AAG changes. To further reduce the complexity of the above-mentioned joint optimization, a low-complexity two-stage separate optimization method is also proposed. Furthermore, when the number of transmit antennas tends to infinity, the Max-SR problem becomes equivalent to that of maximizing the ratio of the desired user's signal-to-interference-plus-noise ratio to the eavesdropper's. Thus our original problem reduces to a fractional programming problem, hence a significant computational complexity reduction can be achieved for the optimization problem. Our simulation results show that the proposed algorithms outperform the existing leakage-based null-space projection scheme in terms of the SR performance attained, and drastically reduces the complexity at a slight SR performance reduction.

eess.SP↗

arXiv2019

Enhancement of Power Equipment Management Using Knowledge Graph

Accurate retrieval of the power equipment information plays an important role in guiding the full-lifecycle management of power system assets. Because of data duplication, database decentralization, weak data relations, and sluggish data updates, the power asset management system eager to adopt a new strategy to avoid the information losses, bias, and improve the data storage efficiency and extraction process. Knowledge graph has been widely developed in large part owing to its schema-less nature. It enables the knowledge graph to grow seamlessly and allows new relations addition and entities insertion when needed. This study proposes an approach for constructing power equipment knowledge graph by merging existing multi-source heterogeneous power equipment related data. A graph-search method to illustrate exhaustive results to the desired information based on the constructed knowledge graph is proposed. A case of a 500 kV station example is then demonstrated to show relevant search results and to explain that the knowledge graph can improve the efficiency of power equipment management.

cs.AI↗

arXiv2019

Performance Analysis of Directional Modulation with Finite-quantized RF Phase Shifters in Analog Beamforming Structure

The radio frequency (RF) phase shifter with finite quantization bits in analog beamforming (AB) structure forms quantization error (QE) and causes a performance loss of received signal to interference plus noise ratio (SINR) at the receiver (called Bob). By using the law of large numbers in probability theory, the closed-form expression of SINR performance loss is derived to be inversely proportional to the square of sinc (or sin(x)/x) function. Here, a phase alignment method is applied in directional modulation transmitter with AB structure. Also, the secrecy rate (SR) expression is derived with QE. From numerical simulation results, we find that the SINR performance loss gradually decreases as the number L of quantization bits increases. This loss is less than 0.3dB when L is larger than or equal to 3. As L exceeds 5, the SINR performance loss at Bob can be approximately trivial. Similarly, SR performance loss gradually reduces as L increases. In particular, the SR performance loss is about 0.1 bits/s/Hz for L=3 at signal-to-noise ratio of 15dB.

cs.IT↗

arXiv2019

Strong interaction between graphene and localized hot spots in all-dielectric metasurfaces

The active photonics based on the two-dimensional material graphene has attracted enormous interests for developing the tunable and compact optical devices with high efficiency. Here we integrate graphene into the Fano-resonant all-dielectric metasurfaces consisting of silicon split resonators, and systematically investigate the strong interaction between graphene and the highly localized hot inside feed gaps in the near infrared regime. The numerical results show that the integrated graphene can substantially reduce the Fano resonance due to the coupling effect between the intrinsic absorption of graphene with enhanced electric field in the localized hotspot. With the manipulation of the surface conductivity via varying Fermi level and the layer number of graphene, the Fano resonance strength obtains a significant modulation and is even switched off. This works provides a great degree of freedom to tailor light-matter interaction at the nanoscale and opens up the avenues for actively tunable and integrated nanophotonic device applications, such as the optical biosensing, slow light and enhanced nonlinear effects.

physics.optics↗

arXiv2018

Alternating Iterative Secure Structure between Beamforming and Power Allocation for UAV-aided Directional Modulation Networks

In unmanned aerial vehicle (UAV) networks, directional modulation (DM) is adopted to improve the secrecy rate (SR) performance. Alice, a ground base station, behaves as a control center, and Bob is a UAV of flying along a linear flight trajectory who optimizes its SR performance by dynamically adjusting its beamforming vectors and power allocation (PA) strategy. Per fixed time interval during the Bob's flight process, the transmit beamforming vectors for useful messages and AN projection are given by the rule of maximizing signal-to-leakage-and-noise ratio (Max-SLNR) and maximizing AN-and-leakage-to-noise ratio (ANLNR), and the optimal PA strategy is based on maximizing SR (Max-SR). More importantly, an alternating iterative structure (AIS) between beamforming and PA is proposed to further improve the SR performance. Simulation results show that the proposed AIS converges rapidly, and can achieve substantial SR gains over Max-SLNR plus Max-ANLNR with fixed PA such as PA factor $β=$ 0.5, and 0.9. In particular, in the case of small-scale antenna array, the SR performance gain achieved by the proposed AIS is more attractive. Additionally, as the number of antennas tends to be large-scale, the average SR performance of the proposed AIS approaches an SR ceil.

cs.IT↗

arXiv2018

Synthesizing and Controlling Helical Indirect Exchange Interactions at Nonequilibrium

We study the nonequilibrium effects of spin and/or electric currents on the helical indirect exchange interactions of local spins that embedded in general open electronic systems. Especially, besides the synthesized anisotropic Heisenberg interactions, we find that the synthetic helical indirect exchange interactions possess two parts: antisymmetric (Dzyaloshinskii-Moriya interaction) and symmetric (Kaplan-Shekhtman-Entin-Wohlman-Aharony interaction), which are all formulated in terms of Keldysh nonequilibrium Green's functions. The presence of either spin-orbit coupling or spin polarized currents alone is able to synthesize and control the antisymmetric Dzyaloshinskii-Moriya exchange interactions, as the same direction as spin splitting. However, the appearance of symmetric Kaplan-Shekhtman-Entin-Wohlman-Aharony interactions requires both, i.e., the spin-orbit coupling and spin polarized currents with different splitting directions. Our results show the detailed scheme of controlling the sign, magnitude, and direction of indirect Dzyaloshinskii-Moriya vectors and Kaplan-Shekhtman-Entin-Wohlman-Aharony interactions at nonequilibrium in open quantum devices.

cond-mat.mes-hall↗

arXiv2018

Independently tunable dual-spectral electromagnetically induced transparency in a terahertz metal-graphene metamaterial

We theoretically investigate the interaction between the conductive graphene layer with the dual-spectral electromagnetically induced transparency (EIT) metamaterial and achieve independent amplitude modulation of the transmission peaks in terahertz (THz) regime. The dual-spectral EIT resonance results from the strong near field coupling effects between the bright cut wire resonator (CWR) in the middle and two dark double-split ring resonators (DSRRs) on the two sides. By integrating monolayer graphene under the dark mode resonators, the two transmission peaks of the EIT resonance can exhibit independent amplitude modulation via shifting the Fermi level of the corresponding graphene layer. The physical mechanism of the modulation can be attributed to the variation of damping factors of the dark mode resonators arising from the tunable conductivity of graphene. This work shows great prospects in designing multiple-spectral THz functional devices with highly flexible tunability and implies promising applications in multi-channel selective switching, modulation and slow light.

physics.optics↗

arXiv2018

Actively tunable slow light in a terahertz hybrid metal-graphene metamaterial

We theoretically and numerically demonstrate an actively tunable slow light in a hybrid metal-graphene metamaterial in the terahertz (THz) regime. In the unit cell, the near field coupling between the metallic elements including the bright cut wire resonator and the dark double split-ring resonator gives rises to a pronounced transmission peak. By positioning a monolayer graphene under the dark mode resonator, an active modulation of the near field coupling is achieved via shifting the Fermi level of graphene. The physical origin can be attributed to the variation in the damping rate of the dark mode resonator arising from the conductive effect of graphene. Accompanied with the actively tunable near filed coupling effect is the dynamically controllable phase dispersion, allowing for the highly tunable slow light effect. This work offers an alternative way to design compact slow light devices in the THz regime for future optical signal processing applications.

physics.optics↗