arXiv subjects

Yang Zhong

Publications and source records attributed to Yang Zhong.

63 records · Page 4Linked to original sources

arXiv2018

Estimation of the chiral magnetic effect considering the magnetic field response of the QGP medium

The magnetic field plays a major role in the searching of the chiral magnetic effect in relativistic heavy-ion collisions. If the lifetime of the magnetic field is too short, as expected by simulations of the field in the vacuum, the chiral magnetic effect will be largely suppressed. However, the lifetime of the magnetic field will become longer when the QGP medium response is considered. We give an estimate of the effect, especially considering the magnetic field response of the QGP medium, and compare it with the experimental results of background-subtracted correlator $H$ at RHIC and LHC energies. The results show that our method explains better for the experimental results at the top RHIC energy than that of the LHC energy.

nucl-th↗

arXiv2016

Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild

Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavourable conditions. Given the success of Convolutional Neural Network (CNN) in image classification, the high-level CNN feature, as an intuitive and reasonable choice, has been widely utilized for this problem. In this paper, however, we consider the mid-level CNN features as an alternative to the high-level ones for attribute prediction. This is based on the observation that face attributes are different: some of them are locally oriented while others are globally defined. Our investigations reveal that the mid-level deep representations outperform the prediction accuracy achieved by the (fine-tuned) high-level abstractions. We empirically demonstrate that the midlevel representations achieve state-of-the-art prediction performance on CelebA and LFWA datasets. Our investigations also show that by utilizing the mid-level representations one can employ a single deep network to achieve both face recognition and attribute prediction.

cs.CV↗

arXiv2016

Face Attribute Prediction Using Off-the-Shelf CNN Features

Predicting attributes from face images in the wild is a challenging computer vision problem. To automatically describe face attributes from face containing images, traditionally one needs to cascade three technical blocks --- face localization, facial descriptor construction, and attribute classification --- in a pipeline. As a typical classification problem, face attribute prediction has been addressed using deep learning. Current state-of-the-art performance was achieved by using two cascaded Convolutional Neural Networks (CNNs), which were specifically trained to learn face localization and attribute description. In this paper, we experiment with an alternative way of employing the power of deep representations from CNNs. Combining with conventional face localization techniques, we use off-the-shelf architectures trained for face recognition to build facial descriptors. Recognizing that the describable face attributes are diverse, our face descriptors are constructed from different levels of the CNNs for different attributes to best facilitate face attribute prediction. Experiments on two large datasets, LFWA and CelebA, show that our approach is entirely comparable to the state-of-the-art. Our findings not only demonstrate an efficient face attribute prediction approach, but also raise an important question: how to leverage the power of off-the-shelf CNN representations for novel tasks.

cs.CV↗

arXiv2016

Chiral electric field in relativistic heavy-ion collisions at energies available at the BNL Relativistic Heavy Ion Collider and at the CERN Large Hadron Collider

It was proposed that the electric fields may lead to chiral separation in QGP, which is called the chiral electric separation effect. The strong electromagnetic field and the QCD vacuum can both completely be produced in the off-central nuclear-nuclear collision. We used the Wood-Saxon nucleon distribution to calculate the electric field distributions of the off-central collisions. The chiral electro field spatial distribution at Relativistic Heavy-Ion Collider (RHIC) and Large Hadron Collider (LHC) energy regions are systematically studied in this paper. Compared with magnetic field spatial distribution, electric field shows some different features in relativistic heavy-ion collisions. The dependence of the electric field produced by the thermal quark in the central position with different impact parameters on the proper time with different collision energies in the RHIC and LHC energy region are studied in this paper.

hep-ph↗

arXiv2015

Leveraging the Power of Gabor Phase for Face Identification: A Block Matching Approach

Different from face verification, face identification is much more demanding. To reach comparable performance, an identifier needs to be roughly N times better than a verifier. To expect a breakthrough in face identification, we need a fresh look at the fundamental building blocks of face recognition. In this paper we focus on the selection of a suitable signal representation and better matching strategy for face identification. We demonstrate how Gabor phase could be leveraged to improve the performance of face identification by using the Block Matching method. Compared to the existing approaches, the proposed method features much lower algorithmic complexity: face images are only filtered by a single-scale Gabor filter pair and the matching is performed between any pairs of face images at hand without involving any training process. Benchmark evaluations show that the proposed approach is totally comparable to and even better than state-of-the-art algorithms, which are typically based on more features extracted from a large set of Gabor faces and/or rely on heavy training processes.

cs.CV↗

arXiv2015

The spatial distributions of chiral magnetic field in the RHIC and LHC energy regions

Relativistic heavy-ion collisions can produce extremely strong magnetic field in the collision regions. The spatial variation features of the magnetic fields are analyzed in detail for non-central Pb - Pb collisions at LHC $\sqrt{s_{NN}}$= 900, 2760 and 7000 GeV and Au-Au collisions at RHIC $\sqrt{s_{NN}}$ = 62.4, 130 and 200 GeV. The dependencies of magnetic field on proper time, collision energies and impact parameters are investigated in this paper. It is shown that a enormous with highly inhomogeneous spatial distribution magnetic field can indeed be created in off-central relativistic heavy-ion collisions in RHIC and LHC energy regions. The enormous magnetic field is quite large, especially just after the collision, and then decreases rapidly with time. We are surprised to find that the magnetic effect decreases with increasing energy from RHIC to LHC energy region. It is found that the magnitude of magnetic field in the LHC energy region is far less than that of magnetic field in the RHIC energy region.

hep-ph↗

arXiv2014

A systematic study of magnetic field in Relativistic Heavy-ion Collisions in the RHIC and LHC energy regions

The features of magnetic field in relativistic heavy-ion collisions are systematically studied by using a modified magnetic field model in this paper. The features of magnetic field distributions in the central point are studied in the RHIC and LHC energy regions. We also predict the feature of magnetic fields at LHC $\sqrt{s_{NN}}$= 900, 2760 and 7000 GeV based on the detailed study at RHIC $\sqrt{s_{NN}}$ = 62.4, 130 and 200 GeV. The dependencies of the features of magnetic fields on the collision energies, centralities and collision time are systematically investigated, respectively.

hep-ph↗

arXiv2012

Baryon productions and collective flow of relativistic heavy-ion collisions in the AGS, SPS, RHIC and LHC energy regions($\sqrt{s_{NN}}\leq5$GeV to 5.5 TeV)

The features of net baryon productions and collective flow in relativistic heavy-ion collisions at energies reached at the CERN Large Hadron Collider (LHC), BNL Relativistic Heavy Ion Collider (RHIC), CERN Super Proton Synchrotron (SPS) and BNL Alternating Gradient Synchrotron (AGS) with the model of Non-Uniform Flow Model(NUFM) are systematically studied in this paper. Especially we predict the feature of net baryon productions and collective flow at LHC $\sqrt{s_{NN}}$=5500 GeV basing on the detailed study of that at RHIC $\sqrt{s_{NN}}$=62.4 and 200GeV. The dependencies of the features of baryon stopping and collective flow on the collision energies and centralities are investigated.

hep-ph↗

arXiv2011

The role of vegetables trade network in global epidemics

The outbreak of enterohemorrhagic Escherichia coli (EHEC) in May 2011 warns the potential threats of the world vegetables trade network (VTN) in spreading fatal infectious diseases. The heterogeneous weight distribution and multi-scale activity of intermediary networks affects the diffusion, proliferation and extinction of epidemics. Here, we constructed a dual-weighted VTN with 118 major countries and territories from FAO 2008 statistic data about global vegetation production and trade, and develop a reaction-diffusion model to simulate the epidemic behaviors in through VTN. We found an emerged asymmetric threshold of epidemic on VTN, in which local proliferation within nodes plays a more critical role than global diffusion in spreading of EHEC-like diseases, i.e. sufficient local proliferation is the precondition for global diffusion. We also found that a strong modularity on VTN structure, which restricts the spreading of EHEC-like diseases; however, within the communities, the diffusion is quick and easy. There is, moreover, a critical "epidemic stem", in which a serial of positive feedback loop for amplifying the proliferation and diffusion pathogens has been identified from entire VTN. Surprisingly, statistical analysis shows a well consistency between theoretical composition of stem and actual pattern of EHEC. The results provide a chance to design gradient control strategies for controlling disease global diffusion. Our analysis provided the first inspect of global epidemics mediated by trade networks for improved control and immunity strategies in the future.

q-bio.PE↗