arXiv subjects

Bo Peng

Publications and source records attributed to Bo Peng.

At least 361 records · Page 20Linked to original sources

arXiv2020

Co-occurrence Background Model with Superpixels for Robust Background Initialization

Background initialization is an important step in many high-level applications of video processing,ranging from video surveillance to video inpainting.However,this process is often affected by practical challenges such as illumination changes,background motion,camera jitter and intermittent movement,etc.In this paper,we develop a co-occurrence background model with superpixel segmentation for robust background initialization. We first introduce a novel co-occurrence background modeling method called as Co-occurrence Pixel-Block Pairs(CPB)to generate a reliable initial background model,and the superpixel segmentation is utilized to further acquire the spatial texture Information of foreground and background.Then,the initial background can be determined by combining the foreground extraction results with the superpixel segmentation information.Experimental results obtained from the dataset of the challenging benchmark(SBMnet)validate it's performance under various challenges.

cs.CV↗

arXiv2020

The FAST discovery of an Eclipsing Binary Millisecond Pulsar in the Globular Cluster M92 (NGC 6341)

We report the discovery of an eclipsing binary millisecond pulsar in the globular cluster M92 (NGC6341) with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). PSR J1717+4308A, or M92A, has a pulse frequency of 316.5~Hz (3.16~ms) and a dispersion measure of 35.45 pc cm$^{-3}$. The pulsar is a member of a binary system with an orbital period of 0.20~days around a low-mass companion which has a median mass of $\sim$0.18~\Ms. From observations so far, at least two eclipsing events have been observed in each orbit. The longer one lasted for ~5000~s in the orbital phase range 0.1--0.5. The other lasted for ~500~s and occurred between 1000--2000~s before or after the longer eclipsing event. The lengths of these two eclipsing events also change. These properties suggest that J1717+4308A is a ``red-back'' system with a low-mass main sequence or sub-giant companion. Timing observations of the pulsar and further searches of the data for additional pulsars are ongoing.

astro-ph.HE↗

arXiv2020

Spin-Valley Locking Effect in Defect States of Monolayer MoS$_2$

Valley pseudospin in two-dimensional (2D) transition-metal dichalcogenides (TMDs) allows optical control of spin-valley polarization and intervalley quantum coherence. Defect states in TMDs give rise to new exciton features and theoretically exhibit spin-valley polarization; however, experimental achievement of this phenomenon remains challenges. Here, we report unambiguous valley pseudospin of defect-bound localized excitons in CVD-grown monolayer MoS2; enhanced valley Zeeman splitting with an effective g-factor of -6.2 is observed. Our results reveal that all five d-orbitals and the increased effective electron mass contribute to the band shift of defect states, demonstrating a new physics of the magnetic responses of defect-bound localized excitons, strikingly different from that of A excitons. Our work paves the way for the manipulation of the spin-valley degrees of freedom through defects toward valleytronic devices.

cond-mat.mtrl-sci↗

arXiv2020

Equation of motion coupled-cluster approach for intrinsic losses in x-ray spectra

We present an equation of motion coupled cluster approach for calculating and understanding intrinsic inelastic losses in core level x-ray absorption spectra (XAS). The method is based on a factorization of the transition amplitude in the time-domain, which leads to a convolution of an effective one-body spectrum and the core-hole spectral function. The spectral function characterizes these losses in terms of shake-up excitations and satellites, and is calculated using a cumulant representation of the core-hole Green's function that includes non-linear corrections. The one-body spectrum also includes orthogonality corrections that enhance the XAS at the edge.

physics.chem-ph↗

arXiv2020

Enhanced Valley Zeeman Splitting in Fe-Doped Monolayer MoS2

The Zeeman effect offers unique opportunities for magnetic manipulation of the spin degree of freedom (DOF). Recently, valley Zeeman splitting, referring to the lifting of valley degeneracy, has been demonstrated in two-dimensional transition metal dichalcogenides (TMDs) at liquid helium temperature. However, to realize the practical applications of valley pseudospins, the valley DOF must be controllable by a magnetic field at room temperature, which remains a significant challenge. Magnetic doping in TMDs can enhance the Zeeman splitting, however, to achieve this experimentally is not easy. Here, we report unambiguous magnetic manipulation of valley Zeeman splitting at 300 K (g = -6.4) and 10 K (g = -11) in a CVD-grown Fe-doped MoS2 monolayer; the effective g factor can be tuned to -20.7 by increasing the Fe dopant concentration, which represents an approximately fivefold enhancement as compared to undoped MoS2. Our measurements and calculations reveal that the enhanced splitting and geff factors are due to the Heisenberg exchange interaction of the localized magnetic moments (Fe 3d electrons) with MoS2 through the d-orbital hybridization.

cond-mat.mtrl-sci↗

arXiv2020

Discovery and timing of pulsars in the globular cluster M13 with FAST

We report the discovery of a binary millisecond pulsar (namely PSR J1641+3627F or M13F) in the globular cluster M13 (NGC 6205) and timing solutions of M13A to F using observations made with the Five-hundred-metre Aperture Spherical radio Telescope (FAST). PSR J1641+3627F has a spin period of 3.00 ms and an orbital period of 1.4 days. The most likely companion mass is 0.16 M$_{\odot}$. M13A to E all have short spin periods and small period derivatives. We also confirm that the binary millisecond pulsar PSR J1641$+$3627E (also M13E) is a black widow with a companion mass around 0.02 M$_{\odot}$. We find that all the binary systems have low eccentricities compared to those typical for globular cluster pulsars and that they decrease with distance from the cluster core. This is consistent with what is expected as this cluster has a very low encounter rate per binary.

astro-ph.HE↗

arXiv2020

A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing Problems

Recent researches show that machine learning has the potential to learn better heuristics than the one designed by human for solving combinatorial optimization problems. The deep neural network is used to characterize the input instance for constructing a feasible solution incrementally. Recently, an attention model is proposed to solve routing problems. In this model, the state of an instance is represented by node features that are fixed over time. However, the fact is, the state of an instance is changed according to the decision that the model made at different construction steps, and the node features should be updated correspondingly. Therefore, this paper presents a dynamic attention model with dynamic encoder-decoder architecture, which enables the model to explore node features dynamically and exploit hidden structure information effectively at different construction steps. This paper focuses on a challenging NP-hard problem, vehicle routing problem. The experiments indicate that our model outperforms the previous methods and also shows a good generalization performance.

cs.LG↗

arXiv2020

The Fundamental Performance of FAST with 19-beam Receiver at L Band

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) passed national acceptance and is taking pilot cycle of 'Shared-Risk' observations. The 19-beam receiver covering 1.05-1.45 GHz was used for most of these observations. The electronics gain fluctuation of the system is better than 1\% over 3.5 hours, enabling enough stability for observations. Pointing accuracy, aperture efficiency and system temperature are three key parameters of FAST. The measured standard deviation of pointing accuracy is 7.9$''$, which satisfies the initial design of FAST. When zenith angle is less than 26.4$^\circ$, the aperture efficiency and system temperature around 1.4 GHz are $\sim$ 0.63 and less than 24 K for central beam, respectively. The measured value of these two parameters are better than designed value of 0.6 and 25 K, respectively. The sensitivity and stability of the 19-beam backend are confirmed to satisfy expectation by spectral HI observations toward N672 and polarization observations toward 3C286. The performance allows FAST to take sensitive observations in various scientific goals, from studies of pulsar to galaxy evolution.

astro-ph.IM↗

arXiv2020

Dirac dark matter in $U(1)_{B-L}$ with Stueckelberg mechanism

We investigate a $U(1)_{B-L}$ gauge extension of the Standard Model (SM) where the gauge boson mass is generated by the Stueckelberg mechanism. Three right-handed neutrinos are added to cancel the gauge anomaly and hence the neutrino masses can be explained. A new Dirac fermion could be a WIMP dark matter whose interaction with the SM sector is mediated by the new gauge boson. Assuming the perturbativity of the gauge coupling up to the Planck scale, we find that only the resonance region is feasible for the dark matter abundance. After applying the $ΔN_{eff}$ constraints from the current Planck experiment, the collider search constraints as well as the dark matter direct detection limits, we observe that the $B-L$ charge of dark matter satisfies $|Q_χ|>0.11$. Such a scenario might be probed conclusively by the projected CMB-S4 experiment, assuming the right-handed neutrinos are thermalized with the SM sector in the early universe.

hep-ph↗

arXiv2019

A PRESTO-based Parallel Pulsar Search Pipeline Used for FAST Drift Scan Data

We developed a pulsar search pipeline based on PRESTO (PulsaR Exploration and Search Toolkit). This pipeline simply runs dedispersion, FFT (Fast Fourier Transformation), and acceleration search in process-level parallel to shorten the processing time. With two parallel strategies, the pipeline can highly shorten the processing time in both the normal searches or acceleration searches. This pipeline was first tested with PMPS (Parkes Multibeam Pulsar Survery) data and discovered two new faint pulsars. Then, it was successfully used in processing the FAST (Five-hundred-meter Aperture Spherical radio Telescope) drift scan data with tens of new pulsar discoveries up to now. The pipeline is only CPU-based and can be easily and quickly deployed in computing nodes for testing purposes or data processes.

astro-ph.IM↗

arXiv2019

Green's Function Coupled Cluster Simulation of the Near-valence Ionizations of DNA-fragments

Accurate description of the ionization process in DNA is crucial to the understanding of the DNA damage under exposure to ionizing radiation, and the exploration of the potential application of DNA strands in nano-electronics. In this work, by employing our recently developed Green's function coupled-cluster (GFCC) library on supercomputing facilities, we have studied the spectral functions of several guanine$-$cytosine (G$-$C) base pair structures ([G$-$C]$_n$, $n=1-3$) for the first time in a relatively broad near-valence regime ([-25.0,-5.0] eV) in the coupled-cluster with singles and doubles (CCSD) level. Our focus is to give a preliminary many-body coupled-cluster understanding and guideline of the vertical ionization energy (VIE), spectral profile, and ionization feature changes of these systems as the system size expands in this near-valence regime. The results show that, as the system size expands, even though the lowest VIEs keep decreasing, the changes of spectral function profile and the relative peak positions get unexpectedly smaller. Further analysis of the ionized states associated with the most intensive peak in the spectral functions reveals non-negligible $|2h,1p\rangle$'s in the ionized wave functions of the considered G$-$C base pair systems. The leading $|2h,1p\rangle$'s associated with the main ionizations from the cytosine part of the G$-$C base pairs feature a transition from the intra-base-pair cytosine $π\rightarrowπ^\ast$ excitation to the inter-base-pair electron excitation as the size of G$-$C base pairs expands, which also indicates the minimum quantum region in the many-body calculations of DNA systems.

physics.chem-ph↗

arXiv2019

On the generalization of GAN image forensics

Recently the GAN generated face images are more and more realistic with high-quality, even hard for human eyes to detect. On the other hand, the forensics community keeps on developing methods to detect these generated fake images and try to guarantee the credibility of visual contents. Although researchers have developed some methods to detect generated images, few of them explore the important problem of generalization ability of forensics model. As new types of GANs are emerging fast, the generalization ability of forensics models to detect new types of GAN images is absolutely an essential research topic. In this paper, we explore this problem and propose to use preprocessed images to train a forensic CNN model. By applying similar image level preprocessing to both real and fake training images, the forensics model is forced to learn more intrinsic features to classify the generated and real face images. Our experimental results also prove the effectiveness of the proposed method.

cs.CV↗

arXiv2019

Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning

Recently, generated images could reach very high quality, even human eyes could not tell them apart from real images. Although there are already some methods for detecting generated images in current forensic community, most of these methods are used to detect a single type of generated images. The new types of generated images are emerging one after another, and the existing detection methods cannot cope well. These problems prompted us to propose a scalable framework for multi-class classification based on deep metric learning, which aims to classify the generated images finer. In addition, we have increased the scalability of our framework to cope with the constant emergence of new types of generated images, and through fine-tuning to make the model obtain better detection performance on the new type of generated data.

cs.CV↗

arXiv2019

Probing stops in the coannihilation region at the HL-LHC: a comparative study of different processes

In the minimal supersymmetric model, the coannihilation of the lighter stop $\tilde{t}_1$ and bino-like dark matter $χ$ provides a feasible way to accommodate the correct dark matter relic abundance. In this scenario, due to the compressed masses, $\tilde{t}_1$ merely appears as missing energy at the LHC and thus the pair production of $\tilde{t}_1$ can only be probed by requiring an associated energetic jet. Meanwhile, since $\tilde{t}_2$ and $\tilde{b}_1$ are correlated in mass and mixing with $\tilde{t}_1$, the production of $\tilde{t}_2\tilde{t}_2^*$ or $\tilde{b}_1\tilde{b}_1^*$, each of which dominantly decays into $\tilde{t}_1$ plus $Z$, $h$ or $W$ boson, may serve as a complementary probe. We examine all these processes at the HL-LHC and find that the $2σ$ sensitivity to $χ$ mass can be as large as about 570 GeV, 600 GeV and 1.1 TeV from the production process of $\tilde{t}_1\tilde{t}_1^*+{\rm jet}$, $\tilde{t}_2\tilde{t}_2^*$ and $\tilde{b}_1\tilde{b}_1^*$, respectively.

hep-ph↗

arXiv2019

CNN-based Dual-Chain Models for Knowledge Graph Learning

Knowledge graph learning plays a critical role in integrating domain specific knowledge bases when deploying machine learning and data mining models in practice. Existing methods on knowledge graph learning primarily focus on modeling the relations among entities as translations among the relations and entities, and many of these methods are not able to handle zero-shot problems, when new entities emerge. In this paper, we present a new convolutional neural network (CNN)-based dual-chain model. Different from translation based methods, in our model, interactions among relations and entities are directly captured via CNN over their embeddings. Moreover, a secondary chain of learning is conducted simultaneously to incorporate additional information and to enable better performance. We also present an extension of this model, which incorporates descriptions of entities and learns a second set of entity embeddings from the descriptions. As a result, the extended model is able to effectively handle zero-shot problems. We conducted comprehensive experiments, comparing our methods with 15 methods on 8 benchmark datasets. Extensive experimental results demonstrate that our proposed methods achieve or outperform the state-of-the-art results on knowledge graph learning, and outperform other methods on zero-shot problems. In addition, our methods applied to real-world biomedical data are able to produce results that conform to expert domain knowledge.

cs.CL↗

arXiv2019

Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval

Sketch-based image retrieval (SBIR) is a challenging task due to the large cross-domain gap between sketches and natural images. How to align abstract sketches and natural images into a common high-level semantic space remains a key problem in SBIR. In this paper, we propose a novel semi-heterogeneous three-way joint embedding network (Semi3-Net), which integrates three branches (a sketch branch, a natural image branch, and an edgemap branch) to learn more discriminative cross-domain feature representations for the SBIR task. The key insight lies with how we cultivate the mutual and subtle relationships amongst the sketches, natural images, and edgemaps. A semi-heterogeneous feature mapping is designed to extract bottom features from each domain, where the sketch and edgemap branches are shared while the natural image branch is heterogeneous to the other branches. In addition, a joint semantic embedding is introduced to embed the features from different domains into a common high-level semantic space, where all of the three branches are shared. To further capture informative features common to both natural images and the corresponding edgemaps, a co-attention model is introduced to conduct common channel-wise feature recalibration between different domains. A hybrid-loss mechanism is designed to align the three branches, where an alignment loss and a sketch-edgemap contrastive loss are presented to encourage the network to learn invariant cross-domain representations. Experimental results on two widely used category-level datasets (Sketchy and TU-Berlin Extension) demonstrate that the proposed method outperforms state-of-the-art methods.

cs.CV↗

arXiv2019

Electromagnetically induced transparency at a chiral exceptional point

Electromagnetically induced transparency, as a quantum interference effect to eliminate optical absorption in an opaque medium, has found extensive applications in slow light generation, optical storage, frequency conversion, optical quantum memory as well as enhanced nonlinear interactions at the few-photon level in all kinds of systems. Recently, there have been great interests in exceptional points, a spectral singularity that could be reached by tuning various parameters in open systems, to render unusual features to the physical systems, such as optical states with chirality. Here we theoretically and experimentally study transparency and absorption modulated by chiral optical states at exceptional points in an indirectly-coupled resonator system. By tuning one resonator to an exceptional point, transparency or absorption occurs depending on the chirality of the eigenstate. Our results demonstrate a new strategy to manipulate the light flow and the spectra of a photonic resonator system by exploiting a discrete optical state associated with specific chirality at an exceptional point as a unique control bit, which opens up a new horizon of controlling slow light using optical states. Compatible with the idea of state control in quantum gate operation, this strategy hence bridges optical computing and storage.

physics.optics↗

arXiv2019

Layer Dependence of Stacking Order in Nonencapsulated Few-layer CrI3

Long-range magnetic orders in atomically thin ferromagnetic CrI3 give rise to new fascinating physics and application perspectives. The physical properties of two-dimensional (2D) ferromagnetism CrI3 are significantly influenced by interlayer spacing and stacking order, which are sensitive to the hydrostatic pressure and external environments. However, there remains debate on the stacking order at low temperature. Here, we study the interlayer coupling and stacking order of non-encapsulated 2-5 layer and bulk CrI3 at 10 K by Raman spectroscopy; demonstrate a rhombohedral stacking in both antiferromagnetic and ferromagnetic CrI3. The opposite helicity dependence of Ag and Eg modes arising from phonon symmetry further validate the rhombohedral stacking. An anomalous temperature-dependent behavior is observed due to spin-phonon coupling below 60 K. Our work provides insights into the interlayer coupling and stacking orders of 2D ferromagnetic materials.

cond-mat.mtrl-sci↗