arXiv subjects

Ying Li

Publications and source records attributed to Ying Li.

At least 415 records · Page 23Linked to original sources

arXiv2020

Diffusive non-reciprocity and thermal diode

Wave propagation and diffusion in linear materials preserve local reciprocity in terms of a symmetric Green's function. For wave propagations, the relation between the fields entering and leaving a system is more relevant than the detailed information about the fields inside it. In such cases, the global reciprocity of the scattering off a system through several ports is more important, which is defined as the symmetric transmission between the scattering channels. When a two-port system supports non-reciprocal (electromagnetic, acoustic) wave propagation, it is a (optical, phonon) diode directly following the definition. However, to date no concrete definition or discussion has been made on the global reciprocity of diffusive processes through a multiple-port system. It thus remains unclear what are the differences and relations between the three concepts, namely local non-reciprocity, global non-reciprocity, and diode effect in diffusion. Here, we provide theoretical analysis on the frequency-domain Green's function and define the global reciprocity of heat diffusion through a two-port system, which has a different setup from that of a thermal diode. We further prove the equivalence between a heat transfer system with broken steady-state global reciprocity and a thermal diode, assuming no temperature-dependent heat generation. The validities of some typical mechanisms in breaking the diffusive reciprocity and making a thermal diode have been discussed. Our results set a general background for future studies on symmetric and asymmetric diffusive processes.

physics.app-ph↗

arXiv2020

A GCICA Grant-Free Random Access Scheme for M2M Communications in Crowded Massive MIMO Systems

A high success rate of grant-free random access scheme is proposed to support massive access for machine-to-machine communications in massive multipleinput multiple-output systems. This scheme allows active user equipments (UEs) to transmit their modulated uplink messages along with super pilots consisting of multiple sub-pilots to a base station (BS). Then, the BS performs channel state information (CSI) estimation and uplink message decoding by utilizing a proposed graph combined clustering independent component analysis (GCICA) decoding algorithm, and then employs the estimated CSIs to detect active UEs by utilizing the characteristic of asymptotic favorable propagation of massive MIMO channel. We call this proposed scheme as GCICA based random access (GCICA-RA) scheme. We analyze the successful access probability, missed detection probability, and uplink throughput of the GCICA-RA scheme. Numerical results show that, the GCICA-RA scheme significantly improves the successful access probability and uplink throughput, decreases missed detection probability, and provides low CSI estimation error at the same time.

cs.IT↗

arXiv2020

Methodology for In-flight Flat-field Calibration of the Lyman-alpha Solar Telescope (LST)

Flat-field reflects the non-uniformity of the photometric response at the focal plane of an instrument, which uses digital image sensors, such as Charge Coupled Device (CCD) and Complementary Metal-Oxide-Semiconductor (CMOS). This non-uniformity must corrected before being used for scientific research. In this paper, we assess various candidate methods via simulation using available data so as to figure the in-flight flat-field calibration methodology for the Lyman-alpha Solar Telescope (LST). LST is one of the payloads for the Advanced Space-based Solar Observatory (ASO-S) mission and consists of three instruments: a White-light Solar Telescope (WST), a Solar Disk Imager (SDI) and a dual-waveband Solar Corona Imager (SCI). In our simulations, data from the Helioseismic and Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) mission are used. Our results show that the normal KLL method is appropriate for in-flight flat-field calibration of WST and implementing a transmissive diffuser is applicable for SCI. For the in-flight flat-field calibration of SDI, we recommend the KLL method with off-pointing images with defocused resolution of around 18", and use the local correlation tracking (LCT) algorithm instead of limb-fitting to determine the relative dis-placements between different images.

astro-ph.SR↗

arXiv2020

Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning

Recently, hyperspectral image (HSI) classification approaches based on deep learning (DL) models have been proposed and shown promising performance. However, because of very limited available training samples and massive model parameters, DL methods may suffer from overfitting. In this paper, we propose an end-to-end 3-D lightweight convolutional neural network (CNN) (abbreviated as 3-D-LWNet) for limited samples-based HSI classification. Compared with conventional 3-D-CNN models, the proposed 3-D-LWNet has a deeper network structure, less parameters, and lower computation cost, resulting in better classification performance. To further alleviate the small sample problem, we also propose two transfer learning strategies: 1) cross-sensor strategy, in which we pretrain a 3-D model in the source HSI data sets containing a greater number of labeled samples and then transfer it to the target HSI data sets and 2) cross-modal strategy, in which we pretrain a 3-D model in the 2-D RGB image data sets containing a large number of samples and then transfer it to the target HSI data sets. In contrast to previous approaches, we do not impose restrictions over the source data sets, in which they do not have to be collected by the same sensors as the target data sets. Experiments on three public HSI data sets captured by different sensors demonstrate that our model achieves competitive performance for HSI classification compared to several state-of-the-art methods

cs.CV↗

arXiv2020

Cirrus: A Long-range Bi-pattern LiDAR Dataset

In this paper, we introduce Cirrus, a new long-range bi-pattern LiDAR public dataset for autonomous driving tasks such as 3D object detection, critical to highway driving and timely decision making. Our platform is equipped with a high-resolution video camera and a pair of LiDAR sensors with a 250-meter effective range, which is significantly longer than existing public datasets. We record paired point clouds simultaneously using both Gaussian and uniform scanning patterns. Point density varies significantly across such a long range, and different scanning patterns further diversify object representation in LiDAR. In Cirrus, eight categories of objects are exhaustively annotated in the LiDAR point clouds for the entire effective range. To illustrate the kind of studies supported by this new dataset, we introduce LiDAR model adaptation across different ranges, scanning patterns, and sensor devices. Promising results show the great potential of this new dataset to the robotics and computer vision communities.

cs.CV↗

arXiv2020

Second Moment Estimator for An AR(1) Model Driven by A Long Memory Gaussian Noise

In this paper, we consider an inference problem for the first order autoregressive process driven by a long memory stationary Gaussian process. Suppose that the covariance function of the noise can be expressed as $\abs{k}^{2H-2}$ times a function slowly varying at infinity. The fractional Gaussian noise and the fractional ARIMA model and some others Gaussian noise are special examples that satisfy this assumption. We propose a second moment estimator and prove the strong consistency and give the asymptotic distribution. Moreover, when the limit distribution is Gaussian, we give the upper Berry-Esséen bound by means of Fourth moment theorem.

math.ST↗

arXiv2020

Robust Correlation Tracking via Multi-channel Fused Features and Reliable Response Map

Benefiting from its ability to efficiently learn how an object is changing, correlation filters have recently demonstrated excellent performance for rapidly tracking objects. Designing effective features and handling model drifts are two important aspects for online visual tracking. This paper tackles these challenges by proposing a robust correlation tracking algorithm (RCT) based on two ideas: First, we propose a method to fuse features in order to more naturally describe the gradient and color information of the tracked object, and introduce the fused features into a background aware correlation filter to obtain the response map. Second, we present a novel strategy to significantly reduce noise in the response map and therefore ease the problem of model drift. Systematic comparative evaluations performed over multiple tracking benchmarks demonstrate the efficacy of the proposed approach.

cs.CV↗

arXiv2020

Study of Quasi-two-body $B_{(s)}\to ϕ(f_0(980)/f_2(1270)\to)ππ$ Decays in Perturbative QCD Approach

In 2017, LHCb collaboration reported their first observation of the rare decays $B_s \to ϕ(f_0(980)$ $/f_2(1270) \to ) π^+π^-$ and the evidence of $B^0 \to ϕ(f_0(980)/f_2(1270)\to)π^+π^-$. Motivated by this, we study these quasi-two-body decays in the perturbative QCD approach. The branching fractions, $CP$ asymmetries and the polarization fractions are calculated. We find that within the appropriate two-meson wave functions, the calculated branching fractions are in agreement with the measurements of LHCb. Based on the narrow-width approximation, We also calculate the branching fractions of the quasi-two-body $B_{d,s}\to ϕ(f_0(980)/f_2(1270)\to) π^0π^0$ and $B_{d,s}\to ϕ(f_2(1270)\to) K^+K^-$, and hope the predictions to be tested in the ongoing LHCb and Belle II experiments. Moreover, the processes $B_{d,s}\to ϕf_2(1270)$ are also analyzed under this approximation. We note that the $CP$ asymmetries of these decays are very small, because these decays are either penguin dominant or pure penguin processes.

hep-ph↗

arXiv2020

Investigation of Effects of New Physics in $c\to (s,d)\ell^+ν_\ell$ Transitions

Recent anomalies in decays induced by $b\to c \ell^- \barν_\ell$ transitions raise the question about such phenomena in the $D$ decays induced by $c\to (s,d)\ell^+ν_\ell$ transitions. In the experimental side, current measurements on the pure leptonic and semileptonic $D$ decays agree with the standard model predictions, such agreements can be used to constrain the new physics (NP) contributions. In this work, we extend the standard model by assuming general effective Hamiltonians describing the $c\to (s,d)\ell^+ν_\ell$ transitions including the full set of the four-fermion operators. Within the latest experimental data, we perform a minimum $χ^2$ fit of the Wilson coefficient corresponding to each operator. The results show that the Wilson coefficients of scalar operators in muon sector are at the order of ${\cal O}(10^{-2})$, and others are at the order of ${\cal O}(10^{-3})$. The lepton flavor universality could be violated by the scalar operators. We also calculate the branching fractions, the forward-backward asymmetries and polarizations of final vector mesons and leptons with the fitted Wilson coefficients of scalar and tensor operators. It is found that the pure leptonic decays are very sensitive to the scalar operators. The effects of NP on the semileptonic decays with electron are negligible, while for the semileptonic decays with muon the effects of scalar operators will show up in the forward-backward asymmetries and polarizations of muon of $D \to Pμ^+ ν_μ$. The future measurements in BESIII and Belle II experiments will help us to test effects of NP and to further test new physics models.

hep-ph↗

arXiv2020

Frequency ratio of an $^{115}$In$^+$ ion clock and a $^{87}$Sr optical lattice clock

We report on the first frequency ratio measurement of an $^{115}$In+ single ion clock and a $^{87}$Sr optical lattice clock. A hydrogen maser serves as a reference oscillator to measure the ratio by independent optical combs. Over more than 90 000 seconds of measurement time, the frequency ratio $f_{\rm{In^+}}/f_{\rm{Sr}}$ is determined to be 2.952 748 749 874 863 4(21) with relative uncertainty of $7.0 \times 10^{-16}$. The measurement creates a new connection in the network of frequency ratios of optical clocks.

physics.atom-ph↗

arXiv2020

Pushing The Limit of Type I Codebook For FDD Massive MIMO Beamforming: A Channel Covariance Reconstruction Approach

There is a fundamental trade-off between the channel representation resolution of codebooks and the overheads of feedback communications in the fifth generation new radio (5G NR) frequency division duplex (FDD) massive multiple-input and multiple-output (MIMO) systems. In particular, two types of codebooks (namely Type I and Type II codebooks) are introduced with different resolution and overhead requirements. Although the Type I codebook based scheme requires lower feedback overhead, its channel state information (CSI) reconstruction and beamforming performance are not as good as those from the Type II codebook based scheme. However, since the Type I codebook based scheme has been widely used in 4G systems for many years, replacing it by the Type II codebook based scheme overnight is too costly to be an option. Therefore, in this paper, using Type I codebook, we leverage advances in cutting plane method to optimize the CSI reconstruction at the base station (BS), in order to close the gap between these two codebook based beamforming schemes. Numerical results based on channel samples from QUAsi Deterministic RadIo channel GenerAtor (QuaDRiGa) are presented to show the excellent performance of the proposed algorithm in terms of beamforming vector acquisition.

eess.SP↗

arXiv2020

UAV LiDAR Point Cloud Segmentation of A Stack Interchange with Deep Neural Networks

Stack interchanges are essential components of transportation systems. Mobile laser scanning (MLS) systems have been widely used in road infrastructure mapping, but accurate mapping of complicated multi-layer stack interchanges are still challenging. This study examined the point clouds collected by a new Unmanned Aerial Vehicle (UAV) Light Detection and Ranging (LiDAR) system to perform the semantic segmentation task of a stack interchange. An end-to-end supervised 3D deep learning framework was proposed to classify the point clouds. The proposed method has proven to capture 3D features in complicated interchange scenarios with stacked convolution and the result achieved over 93% classification accuracy. In addition, the new low-cost semi-solid-state LiDAR sensor Livox Mid-40 featuring a incommensurable rosette scanning pattern has demonstrated its potential in high-definition urban mapping.

cs.CV↗

arXiv2020

Self-consistent tomography of temporally correlated errors

The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation. Noise with temporal correlations, e.g. low-frequency noise and context-dependent noise, is common in quantum computation devices and sometimes even significant. However, conventional tomography methods have not been developed for obtaining an error model describing temporal correlations. In this paper, we propose self-consistent tomography protocols to obtain a model of temporally correlated errors, and we demonstrate that our protocols are efficient for low-frequency noise and context-dependent noise.

quant-ph↗

arXiv2020

Simple model for large CP violation in charm decays, B-physics anomalies, muon g-2, and Dark Matter

We present a minimal extension of the Standard Model that can simultaneously account for the anomalies in semi-leptonic B meson decays and the muon g-2, give large CP violation in charm decays (up to the value recently measured by LHCb), and provide thermal-relic dark matter, while evading all constraints set by other flavour observables, LHC searches, and dark matter experiments. This is achieved by introducing only four new fields: a vectorlike quark, a vectorlike lepton, and two scalar fields (a singlet and a doublet) that mix due to the electroweak symmetry breaking and provide the dark matter candidate. The singlet-doublet mixing induces chirally-enhanced dipole transitions, which are crucial for the explanation of the muon g-2 discrepancy and the large charm CP violation, and allows to achieve the observed dark matter density in wide regions of the parameter space.

hep-ph↗

arXiv2020

The Light Sgoldstino Phenomenology: Explanations for the Muon $(g-2)$ Deviation and KOTO Anomaly

In this work, we study the long-standing experimental anomaly in muon $(g-2)$ and also recent anomalous excess in $K_L\to π^0+ν\barν$ at the J-PARC KOTO experiment with sgoldstino. After supersymmetry breaking, the interactions between quarks and sgoldstino ($s$) make the decays $K\to π+s$ sizable through loop diagrams, which affects the measurements of decays $K\to π+\mathrm{invisible}$. Furthermore, the couplings between photons and sgoldstino contribute to $Δa_μ$ as well as the bino-slepton contribution. With satisfying all known experimental constraints such as from NA62, E949, E137, Orsay, KTEV and CHARM experiments, these two anomalies can be explained simultaneously. The mass of CP-even sgoldstino is close to the neutral pion mass which does not violate the Grossman-Nir bound. The parameter space can be further tested in future NA62, DUNE experiments, as well as experiments in the LHC.

hep-ph↗

arXiv2020

Fault-tolerant fidelity based on few-qubit codes: Parity-check circuits for biased error channels

In the shallow sub-threshold regime, fault-tolerant quantum computation requires a tremendous amount of qubits. In this paper, we study the error correction in the deep sub-threshold regime. We estimate the physical error rate for achieving the logical error rates of $10^{-6} - 10^{-15}$ using few-qubit codes, i.e. short repetition codes, small surface codes and the Steane code. Error correction circuits that are efficient for biased error channels are identified. Using the Steane code, when error channels are biased with a ratio of $10^{-3}$, the logical error rate of $10^{-15}$ can be achieved with the physical error rate of $10^{-5}$, which is much higher than the physical error rate of $10^{-9}$ for depolarising errors.

quant-ph↗

arXiv2020

Perturbative tomography of small errors in quantum gates

We propose an efficient protocol to fully reconstruct a set of high-fidelity quantum gates. Usually, the efficiency of reconstructing high-fidelity quantum gates is limited by the sampling noise. Our protocol is based on a perturbative approach and has two stages. In the first stage, the initial part of noisy quantum gates is reconstructed by measuring traces of maps, and the trace can be measured by amplifying the noise in a way similar to randomised benchmarking and quantum spectral tomography. In the second stage, by amplifying the non-unital part using the unital part, we can efficiently reconstruct the non-unital part. We show that the number of measurements needed in our protocol scales logarithmically with the error rate of gates.

quant-ph↗

arXiv2020

Breaking Anti-$\mathcal{PT}$ Symmetry by Spinning a Resonator

Non-Hermitian systems, with symmetric or antisymmetric Hamiltonians under the parity-time ($\mathcal{PT}$) operations, can have entirely real eigenvalues. This fact has led to surprising discoveries such as loss-induced lasing and topological energy transfer. A merit of anti-$\mathcal{PT}$ systems is free of gain, but in recent efforts on making anti-$\mathcal{PT}$ devices, nonlinearity is still required. Here, counterintuitively, we show how to achieve anti-$\mathcal{PT}$ symmetry and its spontaneous breaking in a linear device by spinning a lossy resonator. Compared with a Hermitian spinning device, significantly enhanced optical isolation and ultrasensitive nanoparticle sensing are achievable in the anti-$\mathcal{PT}$-broken phase. In a broader view, our work provides a new tool to study anti-$\mathcal{PT}$ physics, with such a wide range of applications as anti-$\mathcal{PT}$ lasers, anti-$\mathcal{PT}$ gyroscopes, and anti-$\mathcal{PT}$ topological photonics or optomechanics.

physics.optics↗