arXiv subjects

Yifei Zhang

Publications and source records attributed to Yifei Zhang.

At least 217 records · Page 12Linked to original sources

arXiv2022

Significant Engagement Community Search on Temporal Networks: Concepts and Algorithms

Community search, retrieving the cohesive subgraph which contains the query vertex, has been widely touched over the past decades. The existing studies on community search mainly focus on static networks. However, real-world networks usually are temporal networks where each edge is associated with timestamps. The previous methods do not work when handling temporal networks. We study the problem of identifying the significant engagement community to which the user-specified query belongs. Specifically, given an integer k and a query vertex u, then we search for the subgraph H which satisfies (i) u $\in$ H; (ii) the de-temporal graph of H is a connected k-core; (iii) In H that u has the maximum engagement level. To address our problem, we first develop a top-down greedy peeling algorithm named TDGP, which iteratively removes the vertices with the maximum temporal degree. To boost the efficiency, we then design a bottom-up local search algorithm named BULS and its enhanced versions BULS+ and BULS*. Lastly, we empirically show the superiority of our proposed solutions on six real-world temporal graphs.

cs.SI↗

arXiv2022

COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning

Graph contrastive learning (GCL) improves graph representation learning, leading to SOTA on various downstream tasks. The graph augmentation step is a vital but scarcely studied step of GCL. In this paper, we show that the node embedding obtained via the graph augmentations is highly biased, somewhat limiting contrastive models from learning discriminative features for downstream tasks. Thus, instead of investigating graph augmentation in the input space, we alternatively propose to perform augmentations on the hidden features (feature augmentation). Inspired by so-called matrix sketching, we propose COSTA, a novel COvariance-preServing feaTure space Augmentation framework for GCL, which generates augmented features by maintaining a "good sketch" of original features. To highlight the superiority of feature augmentation with COSTA, we investigate a single-view setting (in addition to multi-view one) which conserves memory and computations. We show that the feature augmentation with COSTA achieves comparable/better results than graph augmentation based models.

cs.LG↗

arXiv2022

Charm and beauty isolation from heavy flavor decay electrons in p+p and Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV at LHC

We present an analysis on the heavy flavor hadron decay electrons with charm and beauty contributions decomposed via a data driven method in p+p and Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV at LHC. The transverse momentum $p_{\mathrm{T}}$ spectra, nuclear modification factor $R_{\mathrm{AA}}$ and azimuthal anisotropic flow $v_2$ distributions of electrons from charm and beauty decays are obtained. We find that the electron $R_{\mathrm{AA}}$ from charm ($R_{\mathrm{AA}}^{\mathrm{c\rightarrow e}}$) and beauty ($R_{\mathrm{AA}}^{\mathrm{b\rightarrow e}}$) decays are suppressed at $p_{\mathrm{T}}$ $>$ 2.0 and $p_{\mathrm{T}}$ $>$ 3.0 GeV/$c$ in Pb+Pb collisions, respectively, which indicates that charm and beauty interact with and lose their energy in the hot-dense medium. A less suppression of electron $R_{\mathrm{AA}}$ from beauty decays than that from charm decays at 2.0 $<$ $p_{\mathrm{T}}$ $<$ 8.0 GeV/$c$ is observed, which is consistent with the mass-dependent partonic energy loss scenario. A non-zero electron $v_2$ from beauty decays ($v_{2}^{\mathrm{b\rightarrow e}}$) is observed and in good agreement with ALICE measurement. At low $p_{\mathrm{T}}$ region from 1.0 to 3.0 GeV/$c$, a discrepancy between RHIC and LHC results is observed with 68\% confidence level, which suggests different degree of thermalization of beauty quark under different temperatures of the medium. At 3.0 GeV/$c$ $<$ $p_{\mathrm{T}}$ $<$ 7.0 GeV/$c$, $v_{2}^{\mathrm{b\rightarrow e}}$ deviates from a number-of-constituent-quark (NCQ) scaling hypothesis, which favors that beauty quark is unlikely thermalized in heavy-ion collisions at LHC energy.

nucl-ex↗

arXiv2022

Quasi-periodic oscillations of the X-ray burst from the magnetar SGR J1935+2154 and associated with the fast radio burst FRB 200428

The origin(s) and mechanism(s) of fast radio bursts (FRBs), which are short radio pulses from cosmological distances, have remained a major puzzle since their discovery. We report a strong Quasi-Periodic Oscillation(QPO) of 40 Hz in the X-ray burst from the magnetar SGR J1935+2154 and associated with FRB 200428, significantly detected with the Hard X-ray Modulation Telescope (Insight-HXMT) and also hinted by the Konus-Wind data. QPOs from magnetar bursts have only been rarely detected; our 3.4 sigma (p-value is 2.9e-4) detection of the QPO reported here reveals the strongest QPO signal observed from magnetars (except in some very rare giant flares), making this X-ray burst unique among magnetar bursts. The two X-ray spikes coinciding with the two FRB pulses are also among the peaks of the QPO. Our results suggest that at least some FRBs are related to strong oscillation processes of neutron stars. We also show that we may overestimate the significance of the QPO signal and underestimate the errors of QPO parameters if QPO exists only in a fraction of the time series of a X-ray burst which we use to calculate the Leahy-normalized periodogram.

astro-ph.HE↗

arXiv2022

Statistical uncertainty estimation of higher-order cumulants with finite efficiency and its application in heavy-ion collisions

We derive the general analytical expressions for the statistical uncertainties of cumulants up to fourth order including an efficiency correction. The analytical expressions have been tested with a toy Monte Carlo model analysis. An application to the study of particle multiplicity fluctuations in heavy-ion collisions is investigated. In this derivation, a mathematical proof is given that the validity of an averaged efficiency correction and the fluctuations induced by the non-uniformity of efficiency can be eliminated. The estimation of statistical uncertainties using the analytical formulas is found to be significantly faster than the commonly used bootstrap method. The simplicity and efficiency of using the analytical formulas may be useful for massive data analysis in many fields.

nucl-th↗

arXiv2022

Ultra-compact nonvolatile phase shifter based on electrically reprogrammable transparent phase change materials

Energy-efficient programmable photonic integrated circuits (PICs) are the cornerstone of on-chip classical and quantum optical technologies. Optical phase shifters constitute the fundamental building blocks which enable these programmable PICs. Thus far, carrier modulation and thermo-optical effect are the chosen phenomena for ultrafast and low-loss phase shifters, respectively; however, the state and information they carry are lost once the power is turned off-they are volatile. The volatility not only compromises energy efficiency due to their demand for constant power supply, but also precludes them from emerging applications such as in-memory computing. To circumvent this limitation, we introduce a novel phase shifting mechanism that exploits the nonvolatile refractive index modulation upon structural phase transition of Sb$_{2}$Se$_{3}$, a bi-stable transparent phase change material. A zero-static power and electrically-driven phase shifter was realized on a foundry-processed silicon-on-insulator platform, featuring record phase modulation up to 0.09 $π$/$μ$m and a low insertion loss of 0.3 dB/$π$, which can be further improved upon streamlined design. We also pioneered a one-step partial amorphization scheme to enhance the speed and energy efficiency of PCM devices. A diverse cohort of programmable photonic devices were demonstrated based on the ultra-compact PCM phase shifter.

physics.optics↗

arXiv2022

The removal method and generation mechanism of spikes in Insight-HXMT/HE telescope

Spikes are some obvious sharp increases that appear on the raw light curves of High Energy X-ray telescope(HE) onboard Insight-HXMT, which could have influences on the data products like energy and power spectra. They are considered to be fake triggers generated by large signals. In this paper, we study the characteristic of the spikes and propose two methods to remove spikes from the raw data. According to the different influences on energy and power spectra, the best parameters for removing the spikes is selected and used in the Insight-HXMT data analysis software. The generation mechanism of spikes is also studied using the backup HE detectors on ground and the spikes can be reduced by the electronic design.

astro-ph.IM↗

arXiv2022

Graph-adaptive Rectified Linear Unit for Graph Neural Networks

Graph Neural Networks (GNNs) have achieved remarkable success by extending traditional convolution to learning on non-Euclidean data. The key to the GNNs is adopting the neural message-passing paradigm with two stages: aggregation and update. The current design of GNNs considers the topology information in the aggregation stage. However, in the updating stage, all nodes share the same updating function. The identical updating function treats each node embedding as i.i.d. random variables and thus ignores the implicit relationships between neighborhoods, which limits the capacity of the GNNs. The updating function is usually implemented with a linear transformation followed by a non-linear activation function. To make the updating function topology-aware, we inject the topological information into the non-linear activation function and propose Graph-adaptive Rectified Linear Unit (GReLU), which is a new parametric activation function incorporating the neighborhood information in a novel and efficient way. The parameters of GReLU are obtained from a hyperfunction based on both node features and the corresponding adjacent matrix. To reduce the risk of overfitting and the computational cost, we decompose the hyperfunction as two independent components for nodes and features respectively. We conduct comprehensive experiments to show that our plug-and-play GReLU method is efficient and effective given different GNN backbones and various downstream tasks.

cs.LG↗

arXiv2021

Effect of non-uniform efficiency on higher-order cumulants in heavy-ion collisions

We perform a systematic study on the effect of non-uniform track efficiency correction in higher-order cumulant analysis in heavy-ion collisions. Through analytical derivation, we find that the true values of cumulants can be successfully reproduced by the efficiency correction with an average of the realistic detector efficiency for particles with the same charges within each single phase space. The theoretical conclusions are supported by a toy model simulation by tuning the non-uniformity of the efficiency employed in the track-by-track efficiency correction method. The valid averaged efficiency is found to suppress the statistical uncertainties of the reproduced cumulants dramatically. Thus, usage of the averaged efficiency requires a careful study of phase space dependence. This study is important for carrying out precision measurements of higher-order cumulants in heavy-ion collision experiments at present and in future.

physics.data-an↗

arXiv2021

Cavity Induced Extraordinary Optical Transmission and Active Modulation with Graphene

Extraordinary optical transmission (EOT) is a phenomenon of exceptional light transmission through a metallic film with hole arrays enhanced by surface plasmon (SP) resonance, which stimulates renewed research hotspots in metamaterials, subwavelength optics, and plasmonics. Below the frequency of the first order SP mode, f_pl0, the metallic film typically shows strong reflection and no EOT. Here, we report an unusual EOT phenomenon below fpl0, i.e., beyond the long-held spectral boundary of classic EOTs. It is induced by a novel bound surface state in a Fabry-Perot(F-P) cavity comprising a holey gold film and a silicon-air interface. By tailoring the cavity length, EOT phenomenon has been pushed deep into the sub-wavelength region by a factor of as large as 20%, and EOT frequency comb with cavity function has been achieved. Due to the enhanced slow-wave effect as the frequency approaches fpl0, the cavity induced EOT gradually merges with the first order SP EOT. Distinguishing from the classic EOT phenomenon, no transmission zero is found between these two EOTs, which dramatically broadens the EOT bandwidth by a factor of 10 at terahertz (THz) frequencies. Furthermore, the EOT transmittance is actively modulated with graphene, achieving a large modulation range from 0.5 to 0.25 under a sub-volt bias from -0.3 to 0.5 V at 500 GHz. To the best of the authors' knowledge, both the modulation range and the low bias are among the best for active EOT devices with graphene to date. Such a structure provides a new strategy for miniaturizing sensing devices, high-power sources, and broadband photonics as well as their active control in the THz regime.

physics.optics↗

arXiv2021

In-orbit timing calibration of the Insight-Hard X-ray Modulation Telescope

We describe the timing system and the timing calibration results of the three payloads on-board the Insight-Hard X-ray Modulation Telescope (Insight-HXMT). These three payloads are the High Energy X-ray telescope (HE, 20-250 keV), the Medium Energy X-ray telescope (ME, 5-30 keV) and the low Energy X-ray telescope (LE, 1-10 keV). We present a method to correct the temperature-dependent period response and the long-term variation of the on-board crystal oscillator, especially for ME that does not carry a temperature-compensated crystal oscillator. The time of arrivals (ToAs) of the Crab pulsar are measured to evaluate the accuracy of the timing system. As the ephemeris of the Crab pulsar given by Jodrell Bank observatory has systematic errors around 40 μs (Rots et al. 2014), we use the quasi-simultaneous observations of the X-ray Timing Instrument (XTI) on-board the Neutron star Interior Composition Explorer (NICER) to produce the Crab ephemerides and to verify the timing system of Insight-HXMT. The energy-dependent ToAs' offsets relative to the NICER measurements including physical and instrumental origins are about 24.7μs, 10.1μs and 864.7μs, and the systematic errors of the timing system are determined as 12.1μs, 8.6μs, and 15.8μs, for HE, ME and LE respectively.

astro-ph.HE↗

arXiv2021

Towards Low-loss 1-bit Quantization of User-item Representations for Top-K Recommendation

Due to the promising advantages in space compression and inference acceleration, quantized representation learning for recommender systems has become an emerging research direction recently. As the target is to embed latent features in the discrete embedding space, developing quantization for user-item representations with a few low-precision integers confronts the challenge of high information loss, thus leading to unsatisfactory performance in Top-K recommendation. In this work, we study the problem of representation learning for recommendation with 1-bit quantization. We propose a model named Low-loss Quantized Graph Convolutional Network (L^2Q-GCN). Different from previous work that plugs quantization as the final encoder of user-item embeddings, L^2Q-GCN learns the quantized representations whilst capturing the structural information of user-item interaction graphs at different semantic levels. This achieves the substantial retention of intermediate interactive information, alleviating the feature smoothing issue for ranking caused by numerical quantization. To further improve the model performance, we also present an advanced solution named L^2Q-GCN-anl with quantization approximation and annealing training strategy. We conduct extensive experiments on four benchmarks over Top-K recommendation task. The experimental results show that, with nearly 9x representation storage compression, L^2Q-GCN-anl attains about 90~99% performance recovery compared to the state-of-the-art model.

cs.IR↗

arXiv2021

Sweeping Plasma Frequency of Terahertz Surface Plasmon Polaritons with Graphene

Plasma frequency is the spectral boundary for low-loss propagation and evanescent decay of surface plasmon polariton (SPP) waves, which corresponds to a high cut-off phenomenon and is typically utilized for identifying SPPs. At terahertz (THz) frequencies, a metal line with periodic metallic grooves can mimic the conventional optical SPPs, which is referred to as designer SPPs. Theoretically, the plasma frequency of THz SPPs decreases as the groove depth increases. Here, by replacing the metallic grooves with graphene sheets, dynamically sweeping SPP plasma frequency is demonstrated for the first time. The metal-graphene hybrid structure comprises a metal line with periodic graphene grooves, a thin-layer ion gel for gating graphene, and metallic tips for uniforming gate field. As the chemical potential changes, the average conductivity of graphene is modulated so that the effective depth of the graphene grooves changes, which sweeps the plasma frequency of THz SPPs consequently. Both simulated and experimental data demonstrate a red shift of plasma frequency from 195 to 180 GHz at a low bias from -0.5 to 0.5 V. The proposed structure reveals a novel approach to control the on/off status of SPP propagation in the THz range.

physics.optics↗

arXiv2021

Non-extensive statistical distributions of charmed meson production in Pb-Pb and pp($\overline{\text{p}}$) collisions

The mid-rapidity transverse-momentum spectra of charmed meson in Pb-Pb and pp($\overline{\text{p}}$) collisions are analyzed by Tsallis-Pareto distribution derived from non-extensive statistics. We perform uniform descriptions for both small and large systems over a wide range of collision energy and hadron transverse momentum. By establishing the relation between the event multiplicity and the Tsallis parameters, we observe that there is significant linearity between thermal temperature and Tsallis-q parameter in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 2.76 TeV and 5.02 TeV. And the slope of the T $-$ (q - 1) parameter is positively correlated with the hadron mass. In addition, the charm mesons have higher thermal temperature than the light hadrons at the same q - 1, indicating that charmed flavor requires a higher temperature to achieve the same degree of non-extensive as light flavors in the heavy-ion collision. The same fit is performed to the transverse momentum spectra of charmed meson in pp($\overline{\text{p}}$) collision over a large energy range with Tsallis-Pareto distribution. It is found that the thermal temperature increases with system energy while the q parameter shows a saturated trend and stops at pp($\overline{\text{p}}$) limit, q - 1 = 0.142 $\pm$ 0.010. Meanwhile, the results of most peripheral Pb-Pb collisions are found to approach the pp($\overline{\text{p}}$) limit, which suggests that less medium effect and more in similarity with pp($\overline{\text{p}}$) collisions are found in more peripheral heavy-ion collisions.

hep-ex↗

arXiv2021

Dense Semantic Contrast for Self-Supervised Visual Representation Learning

Self-supervised representation learning for visual pre-training has achieved remarkable success with sample (instance or pixel) discrimination and semantics discovery of instance, whereas there still exists a non-negligible gap between pre-trained model and downstream dense prediction tasks. Concretely, these downstream tasks require more accurate representation, in other words, the pixels from the same object must belong to a shared semantic category, which is lacking in the previous methods. In this work, we present Dense Semantic Contrast (DSC) for modeling semantic category decision boundaries at a dense level to meet the requirement of these tasks. Furthermore, we propose a dense cross-image semantic contrastive learning framework for multi-granularity representation learning. Specially, we explicitly explore the semantic structure of the dataset by mining relations among pixels from different perspectives. For intra-image relation modeling, we discover pixel neighbors from multiple views. And for inter-image relations, we enforce pixel representation from the same semantic class to be more similar than the representation from different classes in one mini-batch. Experimental results show that our DSC model outperforms state-of-the-art methods when transferring to downstream dense prediction tasks, including object detection, semantic segmentation, and instance segmentation. Code will be made available.

cs.CV↗

arXiv2021

An experimental review of open heavy flavor and quarkonium production at RHIC

Open heavy flavor and quarkonium are unique probes of the hot-dense medium produced in heavy-ion collisions. Their production in p+p collisions also provide important test of QCD. In this paper, we review the selected results on open heavy flavor and quarkonium in p+p and heavy-ion collisions achieved at RHIC. Physics implications are also discussed.

nucl-ex↗

arXiv2021

Exploring Instance Relations for Unsupervised Feature Embedding

Despite the great progress achieved in unsupervised feature embedding, existing contrastive learning methods typically pursue view-invariant representations through attracting positive sample pairs and repelling negative sample pairs in the embedding space, while neglecting to systematically explore instance relations. In this paper, we explore instance relations including intra-instance multi-view relation and inter-instance interpolation relation for unsupervised feature embedding. Specifically, we embed intra-instance multi-view relation by aligning the distribution of the distance between an instance's different augmented samples and negative samples. We explore inter-instance interpolation relation by transferring the ratio of information for image sample interpolation from pixel space to feature embedding space. The proposed approach, referred to as EIR, is simple-yet-effective and can be easily inserted into existing view-invariant contrastive learning based methods. Experiments conducted on public benchmarks for image classification and retrieval report state-of-the-art or comparable performance.

cs.CV↗

arXiv2021

The design of the Ali CMB Polarization Telescope receiver

Ali CMB Polarization Telescope (AliCPT-1) is the first CMB degree-scale polarimeter to be deployed on the Tibetan plateau at 5,250m above sea level. AliCPT-1 is a 90/150 GHz 72 cm aperture, two-lens refracting telescope cooled down to 4 K. Alumina lenses, 800mm in diameter, image the CMB in a 33.4° field of view on a 636mm wide focal plane. The modularized focal plane consists of dichroic polarization-sensitive Transition-Edge Sensors (TESes). Each module includes 1,704 optically active TESes fabricated on a 150mm diameter silicon wafer. Each TES array is read out with a microwave multiplexing readout system capable of a multiplexing factor up to 2,048. Such a large multiplexing factor has allowed the practical deployment of tens of thousands of detectors, enabling the design of a receiver that can operate up to 19 TES arrays for a total of 32,376 TESes. AliCPT-1 leverages the technological advancements in the detector design from multiple generations of previously successful feedhorn-coupled polarimeters, and in the instrument design from BICEP-3, but applied on a larger scale. The cryostat receiver is currently under integration and testing. During the first deployment year, the focal plane will be populated with up to 4 TES arrays. Further TES arrays will be deployed in the following years, fully populating the focal plane with 19 arrays on the fourth deployment year. Here we present the AliCPT-1 receiver design, and how the design has been optimized to meet the experimental requirements.

astro-ph.IM↗