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Jie Zhao

Publications and source records attributed to Jie Zhao.

At least 181 records · Page 10Linked to original sources

Investigation of Experimental Observables in Search of the Chiral Magnetic Effect in Heavy-ion Collisions in the STAR experiment

The chiral magnetic effect (CME) is a novel transport phenomenon, arising from the interplay between quantum anomalies and strong magnetic fields in chiral systems. In high-energy nuclear collisions, the CME may survive the expansion of the quark-gluon plasma fireball and be detected in experiments. Over the past decade, the experimental searches for the CME have aroused extensive interest at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The main goal of this article is to investigate three pertinent experimental approaches: the $γ$ correlator, the $R$ correlator and the signed balance functions. We will exploit both simple Monte Carlo simulations and a realistic event generator (EBE-AVFD) to verify the equivalence in the kernel-component observables among these methods and to ascertain their sensitivities to the CME signal for the isobaric collisions at RHIC.

nucl-ex↗

Video Annotation for Visual Tracking via Selection and Refinement

Deep learning based visual trackers entail offline pre-training on large volumes of video datasets with accurate bounding box annotations that are labor-expensive to achieve. We present a new framework to facilitate bounding box annotations for video sequences, which investigates a selection-and-refinement strategy to automatically improve the preliminary annotations generated by tracking algorithms. A temporal assessment network (T-Assess Net) is proposed which is able to capture the temporal coherence of target locations and select reliable tracking results by measuring their quality. Meanwhile, a visual-geometry refinement network (VG-Refine Net) is also designed to further enhance the selected tracking results by considering both target appearance and temporal geometry constraints, allowing inaccurate tracking results to be corrected. The combination of the above two networks provides a principled approach to ensure the quality of automatic video annotation. Experiments on large scale tracking benchmarks demonstrate that our method can deliver highly accurate bounding box annotations and significantly reduce human labor by 94.0%, yielding an effective means to further boost tracking performance with augmented training data.

cs.CV↗

Revisit the Chiral Magnetic Effect Expectation in Isobaric Collisions at the Relativistic Heavy Ion Collider

Isobaric $^{96}_{44}$Ru+$^{96}_{44}$Ru and $^{96}_{40}$Zr+$^{96}_{40}$Zr collisions at $\sqrt{s_{_{NN}}}=200$ GeV have been conducted at the Relativistic Heavy Ion Collider to circumvent the large flow-induced background in searching for the chiral magnetic effect (CME), predicted by the topological feature of quantum chromodynamics (QCD). Considering that the background in isobar collisions is approximately twice that in Au+Au collisions (due to the smaller multiplicity) and the CME signal is approximately half (due to the weaker magnetic field), we caution that the CME may not be detectable with the collected isobar data statistics, within $\sim$2$σ$ significance, if the axial charge per entropy density ($n_5/s$) and the QCD vacuum transition probability are system independent. This expectation is generally verified by the Anomalous-Viscous Fluid Dynamics (AVFD) model. While our estimate provides an approximate "experimental" baseline, theoretical uncertainties on the CME remain large.

nucl-ex↗

Microscopic self-consistent description of induced fission: dynamical pairing degree of freedom

The role of dynamical pairing in induced fission dynamics is investigated using the time-dependent generator coordinate method in the Gaussian overlap approximation, based on the microscopic framework of nuclear energy density functionals. A calculation of fragment charge yields for induced fission of $^{228}$Th is performed in a three-dimensional space of collective coordinates that, in addition to the axial quadrupole and octupole intrinsic deformations of the nuclear density, also includes an isoscalar pairing degree of freedom. It is shown that the inclusion of dynamical pairing has a pronounced effect on the collective inertia, the collective flux through the scission hyper-surface, and the resulting fission yields, reducing the asymmetric peaks and enhancing the contribution of symmetric fission, in better agreement with the empirical trend.

nucl-th↗

Linear Dependence of Post-irradiation Input Bias Currents on Pre-irradiation Values in Silicon Bipolar Microcircuits

We find in experiments a linear dependence of ionization irradiation-induced degradations on pre-irradiation values of the input bias current in bipolar devices with simple input stages. The dependence is found to generally exist in all studied cases of different device types and different irradiation conditions. A unique behavior of the energy distribution of the interface states ($D_{it}$) under irradiation is suggested as the origin of the observed phenomenon: the generation of interface traps through the depassivation of Si-H bonds located near the pre-irradiation interface traps displays a $D_{it}$ as an enlarge of the initial $D_{it}$ and results in the general linear dependence. A more accurate damage prediction method by using the pre-irradiation values is proposed based on the observed phenomenon.

physics.space-ph↗

Two- and three-particle nonflow contributions to the chiral magnetic effect measurement by spectator and participant planes in relativistic heavy ion collisions

Correlation measurements with respect to the spectator and participant planes in relativistic heavy ion collisions were proposed to extract the chiral magnetic effect (CME) from background dominated azimuthal correlators. This paper investigates the effects of two- and three-particle nonflow correlations on the extracted CME signal fraction, $f_{\text{CME}}$. It is found, guided by a multiphase transport (AMPT) model and the heavy ion jet interaction generator (HIJING) together with experimental data, that the nonflow effects amount to approximately $(4\pm5)$% and $(-5\pm3)$% without and with pseudorapidity gaps, respectively, in 20-50% centrality Au+Au collisions at $\sqrt{s_{\text{NN}}}= 200 \text{ GeV}$.

nucl-ex↗

HIJING can describe the anisotropy-scaled charge-dependent correlations at the Relativistic Heavy Ion Collider

The experimentally measured charge-depdendent correlations in heavy ion collisions have been suggested as a signature of the chiral magenetic effect (CME). Early model studies could not reproduce the measurement. For example, the Hijing model yielded far smaller magnitude for the charge-dependent correlation than observed in data. This led to the conclusion that the CME had to be invoked to explain the observed correlations in heavy ion collisions. In this paper we show that this conclusion of the CME interpretation is premature. We show that the reason that Hijing predicts a far smaller correlation than data is because the elliptic anisotrpy ($v_{2}$) parameter in Hijing is too small. When properly scaled, the Hijing model can reproduce in entirety the measured correlations. We also employ the AMPT model, which has a large enough $v_2$, to demonstrate that the measured data can be easily accommodated by models without invoking the CME.

nucl-th↗

BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation

Blood vessel segmentation is crucial for many diagnostic and research applications. In recent years, CNN-based models have leaded to breakthroughs in the task of segmentation, however, such methods usually lose high-frequency information like object boundaries and subtle structures, which are vital to vessel segmentation. To tackle this issue, we propose Boundary Enhancement and Feature Denoising (BEFD) module to facilitate the network ability of extracting boundary information in semantic segmentation, which can be integrated into arbitrary encoder-decoder architecture in an end-to-end way. By introducing Sobel edge detector, the network is able to acquire additional edge prior, thus enhancing boundary in an unsupervised manner for medical image segmentation. In addition, we also utilize a denoising block to reduce the noise hidden in the low-level features. Experimental results on retinal vessel dataset and angiocarpy dataset demonstrate the superior performance of the new BEFD module.

eess.IV↗

Decipher the $R_{Ψ_{m}}$ correlator in search for the chiral magnetic effect in relativistic heavy ion collisions

Background: The chiral magnetic effect (CME) is extensively studied in heavy-ion collisions at RHIC and the LHC. An azimuthal correlator called $R_{Ψ_{m}}$ was proposed to measure the CME. By observing the same $R_{Ψ_{2}}$ and $R_{Ψ_{3}}$ (convex) distributions from A Multi-Phase Transport (AMPT) model, by contrasting data and model as well as large and small systems and by event shape engineering (ESE), a recent preprint (arXiv:2006.04251v1) from STAR suggests that the $R_{Ψ_{m}}$ observable is sensitive to the CME signal and relatively insensitive to backgrounds, and their Au+Au data are inconsistent with known background contributions. Purpose: We examine those claims by studying the robustness of the $R_{Ψ_{m}}$ observable using AMPT as well as toy model simulations. We compare $R_{Ψ_{m}}$ to the more widely used $Δγ$ azimuthal correlator to identify their commonalities and differences. Methods: We use AMPT to simulate Au+Au, p+Au, and d+Au collisions at $\sqrt{s_{NN}} = 200 \text{ GeV}$, and study the responses of $R_{Ψ_{m}}$ to anisotropic flow backgrounds in the model. We also use a toy model to simulate resonance flow background and input CME signal to investigate their effects in $R_{Ψ_{2}}$. Additionally we use the toy model to perform an ESE analysis to compare to STAR data as well as predict the degree of sensitivity of $R_{Ψ_{2}}$ to isobar collisions with the event statistics taken at RHIC. ...

nucl-th↗

Efficient Client Contribution Evaluation for Horizontal Federated Learning

In federated learning (FL), fair and accurate measurement of the contribution of each federated participant is of great significance. The level of contribution not only provides a rational metric for distributing financial benefits among federated participants, but also helps to discover malicious participants that try to poison the FL framework. Previous methods for contribution measurement were based on enumeration over possible combination of federated participants. Their computation costs increase drastically with the number of participants or feature dimensions, making them inapplicable in practical situations. In this paper an efficient method is proposed to evaluate the contributions of federated participants. This paper focuses on the horizontal FL framework, where client servers calculate parameter gradients over their local data, and upload the gradients to the central server. Before aggregating the client gradients, the central server train a data value estimator of the gradients using reinforcement learning techniques. As shown by experimental results, the proposed method consistently outperforms the conventional leave-one-out method in terms of valuation authenticity as well as time complexity.

cs.LG↗

Phase-controlled pathway interferences and switchable fast-slow light in a cavity-magnon polariton system

We study the phase controlled transmission properties in a compound system consisting of a 3D copper cavity and an yttrium iron garnet (YIG) sphere. By tuning the relative phase of the magnon pumping and cavity probe tones, constructive and destructive interferences occur periodically, which strongly modify both the cavity field transmission spectra and the group delay of light. Moreover, the tunable amplitude ratio between pump-probe tones allows us to further improve the signal absorption or amplification, accompanied by either significantly enhanced optical advance or delay. Both the phase and amplitude-ratio can be used to realize in-situ tunable and switchable fast-slow light. The tunable phase and amplitude-ratio lead to the zero reflection of the transmitted light and an abrupt fast-slow light transition. Our results confirm that direct magnon pumping through the coupling loops provides a versatile route to achieve controllable signal transmission, storage, and communication, which can be further expanded to the quantum regime, realizing coherent-state processing or quantum-limited precise measurements.

quant-ph↗

Finite Volume Element Methods for Two-Dimensional Time Fractional Reaction-Diffusion Equations on Triangular Grids

In this paper, the time fractional reaction-diffusion equations with the Caputo fractional derivative are solved by using the classical $L1$-formula and the finite volume element (FVE) methods on triangular grids. The existence and uniqueness for the fully discrete FVE scheme are given. The stability result and optimal \textit{a priori} error estimate in $L^2(Ω)$-norm are derived, but it is difficult to obtain the corresponding results in $H^1(Ω)$-norm, so another analysis technique is introduced and used to achieve our goal. Finally, two numerical examples in different spatial dimensions are given to verify the feasibility and effectiveness.

math.NA↗

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↗

Skin disease diagnosis with deep learning: a review

Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin cancer correctly is challenging. Recently, deep learning algorithms have emerged to achieve excellent performance on various tasks. Particularly, they have been applied to the skin disease diagnosis tasks. In this paper, we present a review on deep learning methods and their applications in skin disease diagnosis. We first present a brief introduction to skin diseases and image acquisition methods in dermatology, and list several publicly available skin datasets for training and testing algorithms. Then, we introduce the conception of deep learning and review popular deep learning architectures. Thereafter, popular deep learning frameworks facilitating the implementation of deep learning algorithms and performance evaluation metrics are presented. As an important part of this article, we then review the literature involving deep learning methods for skin disease diagnosis from several aspects according to the specific tasks. Additionally, we discuss the challenges faced in the area and suggest possible future research directions. The major purpose of this article is to provide a conceptual and systematically review of the recent works on skin disease diagnosis with deep learning. Given the popularity of deep learning, there remains great challenges in the area, as well as opportunities that we can explore in the future.

eess.IV↗

Probing the neutron skin with ultrarelativistic isobaric collisions

Particle production in ultrarelativistic heavy ion collisions depends on the details of the nucleon density distributions in the colliding nuclei. We demonstrate that the charged hadron multiplicity distributions in isobaric collisions at ultrarelativistic energies provide a novel approach to determine the poorly known neutron density distributions and thus the neutron skin thickness in finite nuclei, which can in turn put stringent constraints on the nuclear symmetry energy.

nucl-th↗

A practical approach of high precision U and Th concentration measurement in acrylic

The Jiangmen Underground Neutrino Observatory will build the world's largest liquid scintillator detector to study neutrinos from various sources. The 20 kt liquid scintillator will be stored in a $\sim$600 t acrylic sphere with 35.4 m diameter due to the good light transparency, chemical compatibility and low radioactivity of acrylic. The concentration of U/Th in acrylic is required to be less than 1 ppt (10$^{-12}$ g/g) to achieve a low radioactive background in the fiducial volume of the JUNO detector. The mass production of acrylic has started, and the quality control requires a fast and reliable radioassay on U/Th in acrylic. We have developed a practical method of measuring U/Th in acrylic to sub-ppt level using the Inductively Coupled Plasma Mass Spectrometer (ICP-MS). The U/Th in acrylic can be concentrated by vaporizing acrylic in a class 100 environment, and the residue will be collected and sent to ICP-MS for measuring U/Th. All the other chemical operation is done in a class 100 clean room, and the ICP-MS measurement is done in a class 1000 clean room. The recovery efficiency is studied by adding the natural nonexistent nuclei $^{229}$Th and $^{233}$U as the tracers. The resulting method detection limit (MDL) with 99% confidence can reach 0.02/0.06 pg $^{238}$U/$^{232}$Th /g acrylic with $\sim$75% recovery efficiency. This equipment and method can not only be used for the quality control of JUNO acrylic, but also be further optimized for the radioassay on other materials with extremely low radioactivity, such as ultra-pure water and liquid scintillator.

physics.ins-det↗

Adversarial Training for Code Retrieval with Question-Description Relevance Regularization

Code retrieval is a key task aiming to match natural and programming languages. In this work, we propose adversarial learning for code retrieval, that is regularized by question-description relevance. First, we adapt a simple adversarial learning technique to generate difficult code snippets given the input question, which can help the learning of code retrieval that faces bi-modal and data-scarce challenges. Second, we propose to leverage question-description relevance to regularize adversarial learning, such that a generated code snippet should contribute more to the code retrieval training loss, only if its paired natural language description is predicted to be less relevant to the user given question. Experiments on large-scale code retrieval datasets of two programming languages show that our adversarial learning method is able to improve the performance of state-of-the-art models. Moreover, using an additional duplicate question prediction model to regularize adversarial learning further improves the performance, and this is more effective than using the duplicated questions in strong multi-task learning baselines

cs.CL↗

Microscopic model for the collective enhancement of nuclear level densities

A microscopic method for calculating nuclear level densities (NLD) is developed, based on the framework of energy density functionals. Intrinsic level densities are computed from single-quasiparticle spectra obtained in a finite-temperature self-consistent mean-field (SCMF) calculation that takes into account nuclear deformation, and is specified by the choice of the energy density functional (EDF) and pairing interaction. The total level density is calculated by convoluting the intrinsic density with the corresponding collective level density, determined by the eigenstates of a five-dimensional quadrupole or quadrupole plus octupole collective Hamiltonian. The parameters of the Hamiltonian (inertia parameters, collective potential) are consistently determined by deformation-constrained SCMF calculations using the same EDF and pairing interaction. The model is applied in the calculation of NLD of $^{94,96,98}$Mo, $^{106,108}$Pd, $^{106,112}$Cd, $^{160,162,164}$Dy, $^{166}$Er, and $^{170,172}$Yb, in comparison with available data. It is shown that the collective enhancement of the intrinsic level density, consistently computed from the eigenstates of the corresponding collective Hamiltonian, leads to total NLDs that are in excellent agreement with data over the whole energy range of measured values.

nucl-th↗