arXiv subjects

Song Zhang

Publications and source records attributed to Song Zhang.

At least 73 records · Page 4Linked to original sources

arXiv2022

System dependence of away-side broadening and $α$-clustering light nuclei structure effect in dihadron azimuthal correlations

A collision system scan involving $α$-clustered $^{12}$C and $^{16}$O is studied by using a multiphase transport model for central collisions at $\sqrt{s_{NN}} = 6.37$ TeV. Background subtracted away-side dihadron azimuthal correlation is performed via the zero yield at minimum (ZYAM) method from raw signals, and the quantitative parameters, such as RMS width and Kurtosis, seem nicely follow the $A^{-1/3}$ law of the system size if the nucleus has the normal Woods-Saxon nucleon distribution. However, for $α$-clustering light nuclei, specifically for $^{12}$C and $^{16}$O, the RMS width and Kurtosis of away-side azimuthal correlation are deviated from the baseline of $A^{-1/3}$ law. In addition, the momentum dependence of away-side broadening parameters is also presented. The results show that there is a distinction in away-side broadening parameters of dihadron correlation function between the Woods-Saxon distribution and the $α$-clustered structures, which sheds light on that the collision system scan for dihadron azimuthal correlation as a potential probe to distinguish $α$-clustered nuclei.

nucl-th↗

arXiv2022

NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results

This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022. This manuscript focuses on the competition set-up, datasets, the proposed methods and their results. The challenge aims at estimating an HDR image from multiple respective low dynamic range (LDR) observations, which might suffer from under- or over-exposed regions and different sources of noise. The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i.e. solutions can not exceed a given number of operations). In Track 2, participants are asked to minimize the complexity of their solutions while imposing a constraint on fidelity scores (i.e. solutions are required to obtain a higher fidelity score than the prescribed baseline). Both tracks use the same data and metrics: Fidelity is measured by means of PSNR with respect to a ground-truth HDR image (computed both directly and with a canonical tonemapping operation), while complexity metrics include the number of Multiply-Accumulate (MAC) operations and runtime (in seconds).

cs.CV↗

arXiv2022

Azimuthal-sensitive three-dimensional HBT radius in Au-Au collisions at $E_{beam} = 1.23$$A$ GeV by the IQMD model

We used an Isospin dependent Quantum Molecular Dynamics (IQMD) model to simulate Au + Au collisions at beam energy $E_{beam}$ = 1.23$A$ GeV, which corresponds to center of mass energy $\sqrt{s_{NN}} = 2.4$ GeV. Firstly, we obtained reasonable rapidity and transverse mass spectra of $π^-$ and $π^+$ as well as "apparent" temperature parameters in comparison with the HADES data. Then by calculating three-dimensional Hanbury Brown and Twiss (HBT) radius of same charged pion-pairs, we obtained the square difference of outward radius and sideward radius, i.e. $R_{out}^{2}-R_{side}^{2}$, as well as the freeze-out volume ($V_{fo}$), which were basically consistent with the trend of HADES experimental results. The azimuthal dependence of the HBT radii was also calculated by a matrix method, and corrected by the rotation matrix. In addition, the eccentricities of the $xy$- and $zy$- planes of pion-pair emissions were also extracted for different pair transverse momentum and collision centrality, which show that the $xy$-eccentricity increases with pair transverse momentum as well as centrality but not for $zy$-eccentricity, indicating a more asymmetric transverse emission of particle-pairs with higher transverse momentum in off-central collisions.

nucl-th↗

arXiv2022

Production of $ΩNN$ and $ΩΩN$ in ultra-relativistic heavy ion collisions

Even though lots of $Λ$-hypernuclei have been found and measured, multi-strangeness hypernuclei consisting of $Ω$ are not yet discovered. The studies of multi-strangeness hypernuclei help us further understand the interaction between hyperons and nucleons. Recently the $ΩN$ and $ΩΩ$ interactions as well as binding energies were calculated by the HAL-QCD's lattice Quantum Chromo-Dynamics (LQCD) simulations and production rates of $Ω$-dibaryon in Au + Au collisions at RHIC and Pb + Pb collisions at LHC energies were estimated by a coalescence model. The present work discusses the production of more exotic triple-baryons including $Ω$, namely $ΩNN$ and $ΩΩN$ as well as their decay channels. A variation method is used in calculations of bound states and binding energy of $ΩNN$ and $ΩΩN$ with the potentials from the HAL-QCD's results. The productions of $ΩNN$ and $ΩΩN$ are predicted by using a blast-wave model plus coalescence model in ultra-relativistic heavy-ion collisions at $\sqrt{s_{NN}} = 200$ GeV and $2.76$ TeV. Furthermore, plots for baryon number dependent yields of different baryons ($N$ and $Ω$), their dibaryons and hypernuclei are made and the production rate of a more exotic tetra-baryon ($ΩΩNN$) is extrapolated.

hep-ph↗

arXiv2022

Practical Adoption of Cloud Computing in Power Systems- Drivers, Challenges, Guidance, and Real-world Use Cases

Motivated by The Federal Energy Regulatory Commission's (FERC) recent direction and ever-growing interest in cloud adoption by power utilities, a Task Force was established to assist power system practitioners with secure, reliable and cost-effective adoption of cloud technology to meet various business needs. This paper summarizes the business drivers, challenges, guidance, and best practices for cloud adoption in power systems from the Task Force's perspective, after extensive review and deliberation by its members, including grid operators, utility companies, software vendors, and cloud providers. The paper begins by enumerating various business drivers for cloud adoption in the power industry. It follows with the discussion of the challenges and risks of migrating power grid utility workloads to the cloud. Next, for each corresponding challenge or risk, the paper provides appropriate guidance. Notably, the guidance is directed toward power industry professionals who are considering cloud solutions and are yet hesitant about the practical execution. Finally, to tie all the sections together, the paper documents various real-world use cases of cloud technology in the power system domain, which both the power industry practitioners and software vendors can look toward to design and select their own future cloud solutions. We hope that the information in this paper will serve as helpful guidance for the development of NERC guidelines and standards relevant to cloud adoption in the industry.

eess.SY↗

arXiv2021

Collision centrality and system size dependences of light nuclei production via dynamical coalescence mechanism

Light (anti-)nuclei in relativistic heavy-ion collisions are considered to be formed by the coalescence mechanism of (anti-)nucleons in the present work. Using a dynamical phase-space coalescence model coupled with a multi-phase transport (AMPT) model, we explore the formation of light clusters such as deuteron, triton and their anti-particles in different centralities for $^{197}$Au + $^{197}$Au collisions at $\sqrt{s_{NN}} = 39$ GeV. The calculated transverse momentum spectra of protons, deuterons, and tritons are comparable to those of experimental data from the RHIC-STAR collaboration. Both coalescence parameters $B_{2}$ for (anti-)deuteron and $B_{3}$ for triton increase with the transverse momentum as well as the collision centrality, and they are comparable with the measured values in experiments. The effect of system size on the production of light nuclei is also investigated by $^{10}$B + $^{10}$B, $^{16}$O + $^{16}$O, $^{40}$Ca + $^{40}$Ca, and $^{197}$Au + $^{197}$Au systems in central collisions. The results show that yields of light nuclei increase with system size, while the values of coalescence parameters present an opposite trend. It is interesting to see that the system size, as well as the centrality dependence of $B_A$ ($A$ = 2, 3), falls into the same group, which further demonstrates production probability of light nuclei is proportional to the size of the fireball. Furthermore, we compare our coalescence results with other models, such as the thermal model and analytic coalescence model, it seems that the description of light nuclei production is consistent with each other.

nucl-th↗

arXiv2021

System evolution of forward-backward multiplicity correlations in a multi-phase transport model

The initial geometry effect on forward-backward multiplicity correlations $C(N_{f},N_{b})$ is studied in relativistic collisions between light nuclei by using a multiphase transport model (AMPT). It is found that tetrahedron $^{16}$O + $^{16}$O gives a more uniform and symmetrical fireball which produces a more isotropic distribution of final particles after the expansion and evolution, and leads to a small $C(N_{f},N_{b})$. Forward-backward multiplicity correlation could be taken as a useful probe to distinguish the pattern of $α$-clustered $^{16}$O in experiments by comparing the neighboring colliding nuclear systems like $^{14}$N + $^{14}$N and $^{19}$F + $^{19}$F.

hep-ph↗

arXiv2021

Machine-learning-based identification for initial clustering structure in relativistic heavy-ion collisions

$α$-clustering structure is a significant topic in light nuclei. A Bayesian convolutional neural network (BCNN) is applied to classify initial non-clustered and clustered configurations, namely Woods-Saxon distribution and three-$α$ triangular (four-$α$ tetrahedral) structure for $^{12}$C ($^{16}$O), from heavy-ion collision events generated within a multi-phase transport (AMPT) model. Azimuthal angle and transverse momentum distributions of charged pions are taken as inputs to train the classifier. On multiple-event basis, the overall classification accuracy can reach $95\%$ for $^{12}$C/$^{16}$O + $^{197}$Au events at $\sqrt{S_{NN}} =$ 200 GeV. With proper constructions of samples, the predicted deviations on mixed samples with different proportions of both configurations could be within $5\%$. In addition, setting a simple confidence threshold can further improve the predictions on the mixed dataset. Our results indicate promising and extensive possibilities of application of machine-learning-based techniques to real data and some other problems in physics of heavy-ion collisions.

hep-ph↗

arXiv2021

Interpreting the charge-dependent flow and constraining the chiral magnetic wave with event shape engineering

The charge asymmetry (Ach) dependence of anisotropic flow serves as an important tool to search for the chiral magnetic wave (CMW) in heavy-ion collisions. However, the background effect, such as the local charge conservation (LCC) entwined with collective flow, has not yet been unambiguously eliminated in the measurement. With the help of two models, the AMPT with initial quadrupole moment and the blast wave (BW) incorporating LCC, we discuss the features of the LCC-induced and the CMW-induced correlations between Ach and the flow. More importantly, we first propose to use the Event Shape Engineering (ESE) technique to distinguish the background and the signal for the CMW study. This method would be highly desirable in the experimental search for the CMW and provides more insights for understanding the charge-dependent collective motion of the quark-gluon plasma.

nucl-th↗

arXiv2021

Thermal photons as a sensitive probe of $α$-cluster in C+Au collisions at the BNL Relativistic Heavy Ion Collider

Different orientations of $α$-clustered carbon nuclei colliding with heavy ions can result in a large variation in the value of anisotropic flow. Thus, photon flow observables from clustered ${\rm^{12}C}$ and ${\rm^{197}Au}$ collisions could be a potential probe to study the `direct photon puzzle'. We calculate the transverse momentum spectra and anisotropic flow coefficients ($v_n$) of thermal photons from collisions of triangular $α$-clustered carbon and gold at $\sqrt{s_{\rm NN}}=200$ GeV at RHIC using a hydrodynamic model framework and compare the results with those obtained from unclustered carbon and gold collisions. The slope of the thermal photon spectra is found to vary moderately for different orientations of collisions. However, we find that the elliptic ($v_2$) and triangular flow ($v_3$) coefficients of direct photons for specific configurations are significantly larger and predominantly formed by the QGP radiation. A strong anti-correlation between initial spatial ellipticity and triangularity is observed in an event-by-event framework of $α$-clustered ${\rm C+Au}$ collisions. These special features provide us an opportunity to detect the exotic nature of cluster structure inside carbon nucleus using the photon probe in the future experiments.

nucl-th↗

arXiv2020

Searching for $^4\overline{L}i$ by momentum correlation function of $\overline{p}-^3\overline{H}e$

The observed heaviest anti-nucleus so far is $^4\overline{H}e$ which is found in relativistic heavy ion collider in 2011. The yield of $^4\overline{L}i$ is four times bigger than that of $^4\overline{H}e$ according to the thermal model. From previous scattering experiment, we know that the $^4Li$ has a very short life time about $1.197\times10^{-22}s$. It decays into $^3{H}e$ and ${p}$. In experiment, the correlation function of $\overline{p}-^3\overline{H}e$ will offer us a method to observe $^4\overline{L}i$ by CPT symmetry. In this paper, we use the blast-wave model and Lednicky-Lyuboshitz analytical model to obtain a prediction of the correlation function of $\overline{p}-{}^3\overline{H}e$ with/without $^4\overline{L}i$ decay in Au + Au collisions at $\sqrt{S_{NN}}$ = 200 GeV. The correlation function with $^4\overline{L}i$ decay is found to exhibit a peak at $k^* \approx$ 0.073GeV/$c$. The results offer a guide for the experimental search for $^4\overline{L}i$ in relativistic heavy ion collision.

nucl-th↗

arXiv2020

Signatures of $α$ clustering in $^{16}$O by using a multiphase transport model

$α$-clustered structures in light nuclei could be studied through "snapshots" taken by relativistic heavy-ion collisions. A multiphase transport (AMPT) model is employed to simulate the initial structure of collision nuclei and the proceeding collisions at center of mass energy $\sqrt{s_{NN}}$ = 6.37 TeV. This initial structure can finally be reflected in the subsequent observations, such as elliptic flow ($v_{2}$), triangular flow ($v_{3}$) and quadrangular flow ($v_4$). Three sets of the collision systems are chosen to illustrate system scan is a good way to identify the exotic $α$-clustered nuclear structure, case I: $\mathrm{^{16}O}$ nucleus (with or without $α$-cluster) + ordinary nuclei (always in Woods-Saxon distribution) in most central collisions, case II: $\mathrm{^{16}O}$ nucleus (with or without $α$-cluster) + $\mathrm{^{197}Au}$ nucleus collisions for centrality dependence, and case III: symmetric collision systems (namely, $^{10}$B + $^{10}$B, $^{12}$C + $^{12}$C, $^{16}$O + $^{16}$O (with or without $α$-cluster), $^{20}$Ne + $^{20}$Ne, and $^{40}$Ca + $^{40}$Ca) in most central collisions. Our calculations propose that relativistic heavy-ion collision experiments at $\sqrt{s_{NN}}$ = 6.37 TeV are promised to distinguish the tetrahedron structure of $\mathrm{^{16}O}$ from the Woods-Saxon one and shed lights on the system scan projects in experiments.

hep-ph↗

arXiv2020

Self-Supervised Learning Aided Class-Incremental Lifelong Learning

Lifelong or continual learning remains to be a challenge for artificial neural network, as it is required to be both stable for preservation of old knowledge and plastic for acquisition of new knowledge. It is common to see previous experience get overwritten, which leads to the well-known issue of catastrophic forgetting, especially in the scenario of class-incremental learning (Class-IL). Recently, many lifelong learning methods have been proposed to avoid catastrophic forgetting. However, models which learn without replay of the input data, would encounter another problem which has been ignored, and we refer to it as prior information loss (PIL). In training procedure of Class-IL, as the model has no knowledge about following tasks, it would only extract features necessary for tasks learned so far, whose information is insufficient for joint classification. In this paper, our empirical results on several image datasets show that PIL limits the performance of current state-of-the-art method for Class-IL, the orthogonal weights modification (OWM) algorithm. Furthermore, we propose to combine self-supervised learning, which can provide effective representations without requiring labels, with Class-IL to partly get around this problem. Experiments show superiority of proposed method to OWM, as well as other strong baselines.

cs.LG↗

arXiv2020

Locally optimal measurement-based quantum feedback with application to multi-qubit entanglement generation

We present a general approach to measurement-based quantum feedback that employs proportional and quantum state-based (PaQS) feedback components to obtain locally optimal protocols. To demonstrate the power of the method, we first show that it reproduces many known feedback protocols, and then apply it to generation of multipartite entanglement with an emphasis on remote entanglement, which requires spatially local feedback Hamiltonians. The symmetry of both measurement and feedback operators is found to be essential for construction of effective protocols. We show that under perfect measurement efficiency, entangled states can be reached with fidelity approaching unity under non-Markovian feedback control protocols, while Markovian protocols resulting from optimizing the feedback unitaries on ensemble averaged states still yield fidelities above 94%. Application of the PaQS approach to generation of N-qubit W, general Dicke and GHZ states shows that such entangled states can be efficiently generated with high fidelity, for up to N = 100 in some cases.

quant-ph↗

arXiv2020

Sample Size Calculation for Cluster Randomized Trials with Zero-inflated Count Outcomes

Cluster randomized trails (CRT) have been widely employed in medical and public health research. Many clinical count outcomes, such as the number of falls in nursing homes, exhibit excessive zero values. In the presence of zero inflation, traditional power analysis methods for count data based on Poisson or negative binomial distribution may be inadequate. In this study, we present a sample size method for CRTs with zero-inflated count outcomes. It is developed based on GEE regression directly modeling the marginal mean of a ZIP outcome, which avoids the challenge of testing two intervention effects under traditional modeling approaches. A closed-form sample size formula is derived which properly accounts for zero inflation, ICCs due to clustering, unbalanced randomization, and variability in cluster size. Robust approaches, including t-distribution-based approximation and Jackknife re-sampling variance estimator, are employed to enhance trial properties under small sample sizes. Extensive simulations are conducted to evaluate the performance of the proposed method. An application example is presented in a real clinical trial setting.

stat.AP↗

arXiv2020

Generative Feature Replay with Orthogonal Weight Modification for Continual Learning

The ability of intelligent agents to learn and remember multiple tasks sequentially is crucial to achieving artificial general intelligence. Many continual learning (CL) methods have been proposed to overcome catastrophic forgetting which results from non i.i.d data in the sequential learning of neural networks. In this paper we focus on class incremental learning, a challenging CL scenario. For this scenario, generative replay is a promising strategy which generates and replays pseudo data for previous tasks to alleviate catastrophic forgetting. However, it is hard to train a generative model continually for relatively complex data. Based on recently proposed orthogonal weight modification (OWM) algorithm which can approximately keep previously learned feature invariant when learning new tasks, we propose to 1) replay penultimate layer feature with a generative model; 2) leverage a self-supervised auxiliary task to further enhance the stability of feature. Empirical results on several datasets show our method always achieves substantial improvement over powerful OWM while conventional generative replay always results in a negative effect. Meanwhile our method beats several strong baselines including one based on real data storage. In addition, we conduct experiments to study why our method is effective.

cs.LG↗

arXiv2020

Serverless computing for cloud-based power grid emergency generation dispatch

Operating a modern power grid reliably in case of SCADA/EMS failure or amid difficult times like COVID-19 pandemic is a challenging task for grid operators. In [11], a PMU-based emergency generation dispatch scheme has been proposed to help the system operators with the supply and demand balancing; however, its realization highly relies on the control center infrastructure for computing and communication. This work, rather than using the on-premises server and dispatch communication system, proposes and implements a cloud-centric serverless architecture to ensure the operation continuity regardless of local infrastructure's availability and accessibility. Through its prototype implementation and evaluation at ISO New England, the solution has demonstrated two major advantages. Firstly, the cloud infrastructure is independent and fault-tolerant, providing grid monitoring and control capability even when EMS loses the corresponding functionality or when operators need to work remotely away from the control center. Secondly, the overall design is event-driven using serverless cloud services in response to the SCADA/EMS failure event. Thanks to "serverless", the burden of the server provisioning and maintenance can be avoided from the user side. The cost of using public cloud services for this solution is extremely low since it is architected and implemented based on the event-driven Function-as-a-Service (FaaS) model. This work also develops a comprehensive cyber security mechanism to comply with critical infrastructure requirements for the power grid, which can serve as an exemplary framework for other grid operators to secure their cloud services.

physics.soc-ph↗

arXiv2020

Vorticity in low-energy heavy-ion collisions

We study the kinematic and thermal vorticities in low-energy heavy-ion collisions by using the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) model. We explore their time evolution and spatial distribution. We find that the initial vorticities have a non-monotonic dependence on the collision energy $\sqrt{s_{\rm NN}}$: as $\sqrt{s_{\rm NN}}$ grows the vorticities first increase steeply and then decrease with the turning point around $\sqrt{s_{\rm NN}}\sim 3-5$ GeV depending on the centrality.

nucl-th↗