arXiv subjects

Hong Yang

Publications and source records attributed to Hong Yang.

At least 91 records · Page 5Linked to original sources

arXiv2020

Prospective Multiple Antenna Technologies for Beyond 5G

Multiple antenna technologies have attracted large research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are used. Now that multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna applications to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. We need radically new approaches to achieve orders-of-magnitude improvements in these metrics and this will be connected to large technical challenges, many of which are yet to be identified. In this survey paper, we present a survey of three new multiple antenna related research directions that might play a key role in beyond 5G networks: Cell-free massive multiple-input multiple-output (MIMO), beamspace massive MIMO, and intelligent reflecting surfaces. More specifically, the fundamental motivation and key characteristics of these new technologies are introduced. Recent technical progress is also presented. Finally, we provide a list of other prospective future research directions.

cs.IT↗

arXiv2020

Exceptional point enhanced optical gyroscope in mechanical PT-symmetric system

As an important device for detecting rotation, high sensitivity gyroscope is required for practical applications. In recent years, exceptional point (EP) shows its potential in enhancing the sensitivity of sensing in optical cavity. Here we propose an EP enhanced optical gyroscope based on mechanical PT-symmetric system in microcavity. By pumping the two optical modes with different colors, i.e. blue and red detuning, an effective mechanical PT-symmetric system can be obtained and the system can be prepared in EP with appropriate parameters. Compared with the situation of diabolic point, EP can enhance the sensitivity of gyroscope with more than one order of magnitude in the weak perturbation regime. The results show the gyroscope can be enhanced effectively by monitoring mechanical modes rather than optical modes. Our work provides a promising approach to design gyroscope with higher sensitivity in optical microcavity and has potential values in some fields including fundamental physic and precision measurement.

physics.optics↗

arXiv2020

Multimode interference induced optical nonreciprocity and routing in an optical microcavity

Optical nonreciprocity and routing using optocal microcavities draw much atttention in recent years. Here, we report the results of the study on the nonreciprocity and routing using optomechanical multimode interference in an optical microcavity. The optomechanical system used here possesses multi-optical modes and a mechanical mode. Optomechanical induced transparency and absorption, appear in the system due to the interference between different paths. The system can present significant nonreciprocity and routing properties when appropriate parameters of the system are set. We design quantum devices, such as diode, circulator and router, which are important applications. Our work shows that optomechanical multimode system can be used as a promising platform for buliding photonic and quantum network.

physics.optics↗

arXiv2019

Deep Active Learning for Anchor User Prediction

Predicting pairs of anchor users plays an important role in the cross-network analysis. Due to the expensive costs of labeling anchor users for training prediction models, we consider in this paper the problem of minimizing the number of user pairs across multiple networks for labeling as to improve the accuracy of the prediction. To this end, we present a deep active learning model for anchor user prediction (DALAUP for short). However, active learning for anchor user sampling meets the challenges of non-i.i.d. user pair data caused by network structures and the correlation among anchor or non-anchor user pairs. To solve the challenges, DALAUP uses a couple of neural networks with shared-parameter to obtain the vector representations of user pairs, and ensembles three query strategies to select the most informative user pairs for labeling and model training. Experiments on real-world social network data demonstrate that DALAUP outperforms the state-of-the-art approaches.

cs.LG↗

arXiv2019

Manipulation of optomechanically induced transparency and absorption by indirectly coupling to an auxiliary cavity mode

We theoretically study the optomechanically induced transparency (OMIT) and absorption(OMIA) phenomena in a single microcavity optomechanical system, assisted by an indirectly-coupledauxiliary cavity mode. We show that the interference effect between the two optical modes playsan important role and can be used to control the multiple-pathway induced destructive or construc-tive interference effect. The three-pathway interference could induce an absorption dip within thetransparent window in the red sideband driving regime, while we can switch back and forth betweenOMIT and OMIA with the four-pathway interference. The conversion between the transparencypeak and absorption dip can be achieved by tuning the relative amplitude and phase of the multiplelight paths interference. Our system proposes a new platform to realize multiple pathways inducedtransparency and absorption in a single microcavity and a feasible way for realizing all-opticalinformation processing.

physics.optics↗

arXiv2019

GraphNAS: Graph Neural Architecture Search with Reinforcement Learning

Graph Neural Networks (GNNs) have been popularly used for analyzing non-Euclidean data such as social network data and biological data. Despite their success, the design of graph neural networks requires a lot of manual work and domain knowledge. In this paper, we propose a Graph Neural Architecture Search method (GraphNAS for short) that enables automatic search of the best graph neural architecture based on reinforcement learning. Specifically, GraphNAS first uses a recurrent network to generate variable-length strings that describe the architectures of graph neural networks, and then trains the recurrent network with reinforcement learning to maximize the expected accuracy of the generated architectures on a validation data set. Extensive experimental results on node classification tasks in both transductive and inductive learning settings demonstrate that GraphNAS can achieve consistently better performance on the Cora, Citeseer, Pubmed citation network, and protein-protein interaction network. On node classification tasks, GraphNAS can design a novel network architecture that rivals the best human-invented architecture in terms of test set accuracy.

cs.LG↗

arXiv2019

Bound state and non-Markovian dynamics of a quantum emitter around a surface plasmonic nanostructure

A bound state between a quantum emitter (QE) and surface plasmon polaritons (SPPs) can be formed, where the QE is partially stabilized in its excited state. We put forward a general approach for calculating the energy level shift at a negative frequency $ω$, which is just the negative of the nonresonant part for the energy level shift at positive frequency $-ω$. We also propose an efficient formalism for obtaining the long-time value of the excited-state population without calculating the eigenfrequency of the bound state or performing a time evolution of the system, in which the probability amplitude for the excited state in the steady limit is equal to one minus the integral of the evolution spectrum over the positive frequency range. With the above two quantities obtained, we show that the non-Markovian decay dynamics in the presence of a bound state can be obtained by the method based on the Green's function expression for the evolution operator. A general criterion for identifying the existence of a bound state is presented. These are numerically demonstrated for a QE located around a nanosphere and in a gap plasmonic nanocavity. These findings are instructive in the fields of coherent light-matter interactions.

cond-mat.mes-hall↗

arXiv2019

Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images

Goal: Squamous cell carcinoma of cervix is one of the most prevalent cancer worldwide in females. Traditionally, the most indispensable diagnosis of cervix squamous carcinoma is histopathological assessment which is achieved under microscope by pathologist. However, human evaluation of pathology slide is highly depending on the experience of pathologist, thus big inter- and intra-observer variability exists. Digital pathology, in combination with deep learning provides an opportunity to improve the objectivity and efficiency of histopathologic slide analysis. Methods: In this study, we obtained 800 haematoxylin and eosin stained slides from 300 patients suffered from cervix squamous carcinoma. Based on information from morphological heterogeneity in the tumor and its adjacent area, we established deep learning models using popular convolution neural network architectures (inception-v3, InceptionResnet-v2 and Resnet50). Then random forest was introduced to feature extractions and slide-based classification. Results: The overall performance of our proposed models on slide-based tumor discrimination were outstanding with an AUC scores > 0.94. While, location identifications of lesions in whole slide images were mediocre (FROC scores > 0.52) duo to the extreme complexity of tumor tissues. Conclusion: For the first time, our analysis workflow highlighted a quantitative visual-based slide analysis of cervix squamous carcinoma. Significance: This study demonstrates a pathway to assist pathologist and accelerate the diagnosis of patients by utilizing new computational approaches.

cs.CV↗

arXiv2019

PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras

We present the first purely event-based, energy-efficient approach for object detection and categorization using an event camera. Compared to traditional frame-based cameras, choosing event cameras results in high temporal resolution (order of microseconds), low power consumption (few hundred mW) and wide dynamic range (120 dB) as attractive properties. However, event-based object recognition systems are far behind their frame-based counterparts in terms of accuracy. To this end, this paper presents an event-based feature extraction method devised by accumulating local activity across the image frame and then applying principal component analysis (PCA) to the normalized neighborhood region. Subsequently, we propose a backtracking-free k-d tree mechanism for efficient feature matching by taking advantage of the low-dimensionality of the feature representation. Additionally, the proposed k-d tree mechanism allows for feature selection to obtain a lower-dimensional dictionary representation when hardware resources are limited to implement dimensionality reduction. Consequently, the proposed system can be realized on a field-programmable gate array (FPGA) device leading to high performance over resource ratio. The proposed system is tested on real-world event-based datasets for object categorization, showing superior classification performance and relevance to state-of-the-art algorithms. Additionally, we verified the object detection method and real-time FPGA performance in lab settings under non-controlled illumination conditions with limited training data and ground truth annotations.

cs.CV↗

arXiv2019

Level shift and decay dynamics of a quantum emitter around plasmonic nanostructure

We put forward a general approach for calculating the quantum energy level shift for emitter in arbitrary nanostructures, in which the energy level shift is expressed by the sum of the real part of the scattering photon Green function (GF) and a simple integral about the imaginary part of the photon GF in the real frequency range without principle value. Compared with the method of direct principal value integral over the positive frequency axis and the method by transferring into the imaginary axis, this method avoids the principle value integral and the calculation of the scattering GF with imaginary frequency. In addition, a much narrower frequency range about the scattering photon GF in enough to get a convergent result. It is numerically demonstrated in the case for a quantum emitter (QE) located around a nanosphere and in a gap plasmonic nanocavity. Quantum dynamics of the emitter is calculated by the time domain method through solving Schrödinger equation in the form of Volterra integral of the second kind and by the frequency domain method based on the Green's function expression for the evolution operator. It is found that the frequency domain method needs information of the scattering GF over a much narrower frequency range. In addition, reversible dynamics is observed. These findings are instructive in the fields of coherent light-matter interactions.

quant-ph↗

arXiv2019

Can Massive MIMO Support Uplink Intensive Applications?

Current outdoor mobile network infrastructure cannot support uplink intensive mobile applications such as connected vehicles that collect and upload large amount of real time data. Our investigation reveals that with maximum-ratio (MR) decoding, it is theoretically impossible to support such applications with cell-free Massive MIMO, and it requires a very large number of service antennas in single cell configuration, making it practically infeasible; but with zero-forcing (ZF) decoding, such applications can be easily supported by cell-free Massive MIMO with very moderate number of access points (AP's), and it requires a lot more service antennas in single cell configuration. Via the newly derived SINR expressions for cell-free Massive MIMO with ZF decoding we show that uplink power control is unnecessary, and that with 10 MHz effective bandwidth for uplink data transmission, in urban and suburban morphologies, on the 2 GHz band, 90 single antenna AP's per square kilometer and 32 single antenna AP's per square kilometer are enough to support 18 autonomous vehicles respectively. In rural morphology, using 450 MHz band, only 2 single antenna AP's per square kilometer is enough.

cs.IT↗

arXiv2019

Rigorous Results for the Ground States of the Spin-2 Bose-Hubbard Model

We present rigorous and universal results for the ground states of the $f=2$ spinor Bose-Hubbard model. The model includes three two-body on site interaction terms, two of which are spin dependent while the other one is spin independent. We prove that, depending only on the coefficients of the two spin dependent terms, the ground state exhibits maximum or minimum total spin or SU(5) ferromagnetism. Exact ground-state degeneracies and the forms of ground-state wave function are also determined in each case. All these results are valid regardless of dimension, lattice structure, or particle number. Our approach takes advantage of the symmetry of the Hamiltonian and employs mathematical tools including the Perron-Frobenius theorem and the Lie algebra $\mathfrak{so}(5)$.

cond-mat.quant-gas↗

arXiv2019

Finite element method for obtaining the regularized photon Green function in lossy material

Photon Green function (GF) is the vital and most decisive factor in the field of quantum light-matter interaction. It is divergent with two equal space arguments in arbitrary-shaped lossy structure and should be regularized. We introduce a finite element method for calculating the regularized GF. It is expressed by the averaged radiation electric field over the finite-size of the photon emitter. For emitter located in homogeneous lossy material, excellent agreement with the analytical results is found for both real cavity model and virtual cavity model. For emitter located in a metal nano-sphere, the regularized scattered GF, which is the difference between the regularized GF and the analytical regularized one in homogeneous space, agrees well with the analytical scattered GF.

physics.optics↗

arXiv2018

DART: Distribution Aware Retinal Transform for Event-based Cameras

We introduce a generic visual descriptor, termed as distribution aware retinal transform (DART), that encodes the structural context using log-polar grids for event cameras. The DART descriptor is applied to four different problems, namely object classification, tracking, detection and feature matching: (1) The DART features are directly employed as local descriptors in a bag-of-features classification framework and testing is carried out on four standard event-based object datasets (N-MNIST, MNIST-DVS, CIFAR10-DVS, NCaltech-101). (2) Extending the classification system, tracking is demonstrated using two key novelties: (i) For overcoming the low-sample problem for the one-shot learning of a binary classifier, statistical bootstrapping is leveraged with online learning; (ii) To achieve tracker robustness, the scale and rotation equivariance property of the DART descriptors is exploited for the one-shot learning. (3) To solve the long-term object tracking problem, an object detector is designed using the principle of cluster majority voting. The detection scheme is then combined with the tracker to result in a high intersection-over-union score with augmented ground truth annotations on the publicly available event camera dataset. (4) Finally, the event context encoded by DART greatly simplifies the feature correspondence problem, especially for spatio-temporal slices far apart in time, which has not been explicitly tackled in the event-based vision domain.

cs.CV↗

arXiv2018

Multi-Cell Massive MIMO in LoS

We consider a multi-cell Massive MIMO system in a line-of-sight (LoS) propagation environment, for which each user is served by one base station, with no cooperation among the base stations. Each base station knows the channel between its service antennas and its users, and uses these channels for precoding and decoding. Under these assumptions we derive explicit downlink and uplink effective SINR formulas for maximum-ratio (MR) processing and zero-forcing (ZF) processing. We also derive formulas for power control to meet pre-determined SINR targets. A numerical example demonstrating the usage of the derived formulas is provided.

eess.SP↗

arXiv2018

Antenna Count for Massive MIMO: 1.9 GHz versus 60 GHz

If we assume line-of-sight propagation and perfect channel state information at the base station -- consistent with slow moving terminals -- then a direct performance comparison between single-cell Massive MIMO at PCS and mmWave frequency bands is straightforward and highly illuminating. Line-of-sight propagation is considered favorable for mmWave because of minimal attenuation, and its facilitation of hybrid beamforming to reduce the required number of active transceivers. We quantify the number of mmWave (60 GHz) service antennas that are needed to duplicate the performance of a specified number of PCS (1.9 GHz) service antennas. As a baseline we consider a modest PCS deployment of 128 antennas serving 18 terminals. We find that, to achieve the same per-terminal max-min 95%-likely downlink throughput, 10000 mmWave antennas are needed. To match the total antenna area of the PCS array would require 128000 half-wavelength mmWave antennas, but a much reduced number is adequate because the large number of antennas also confers greater channel orthogonality. The principal alleged benefit of mmWave technology--vast amounts of inexpensive spectrum--is at least partially offset by the complexity of possibly unwieldy amounts of hardware.

cs.IT↗

arXiv2018

Polarization-dependent property of dipole-dipole interaction mediated by localized surface plasmon of an Ag nanosphere

The effect of the dipole polarization on the quantum dipole dipole interaction near an Ag nanosphere (ANS) is investigated. A theoretical formalism in terms of classical Green function is developed for the transfer rate and the potential energy of the dipole dipole interaction (DDI) between two polarized dipoles. It is found that a linear transition dipole can couple to a left circularly polarized transition dipole much stronger than to a right circularly polarized transition dipole. This polarization selectivity exists over a wide frequency range and is robust against the variation of the dipoles' position or the radius of the ANS. In contrast, a right circularly polarized transition dipole, can change sharply from coupling strongly to another right circularly polarized dipole to coupling strongly to a left circularly polarized dipole with varying frequency. However, if the two dipoles are placed in the same radial direction of the sphere, the right circularly polarized transition dipole can only couple to the dipole with the same polarization while not to the left circularly polarized transition dipole. These findings may be used in solid-state quantum-information processing based on the DDI.

quant-ph↗

arXiv2017

Uniform Quantification of Correlations for Bipartite Systems

Based on the relative entropy, we give a unified characterization of quantum correlations for nonlocality, steerability, discord and entanglement for any bipartite quantum states. For two-qubit states we show that the quantities obtained from quantifying nonlocality, steerability, entanglement and discord have strictly monotonic relationship. As for examples, the Bell diagonal states are studied in detail.

quant-ph↗