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Qun Wang

Publications and source records attributed to Qun Wang.

At least 55 records · Page 3Linked to original sources
arXiv2024

A General-Purpose Device for Interaction with LLMs

This paper investigates integrating large language models (LLMs) with advanced hardware, focusing on developing a general-purpose device designed for enhanced interaction with LLMs. Initially, we analyze the current landscape, where virtual assistants and LLMs are reshaping human-technology interactions, highlighting pivotal advancements and setting the stage for a new era of intelligent hardware. Despite substantial progress in LLM technology, a significant gap exists in hardware development, particularly concerning scalability, efficiency, affordability, and multimodal capabilities. This disparity presents both challenges and opportunities, underscoring the need for hardware that is not only powerful but also versatile and capable of managing the sophisticated demands of modern computation. Our proposed device addresses these needs by emphasizing scalability, multimodal data processing, enhanced user interaction, and privacy considerations, offering a comprehensive platform for LLM integration in various applications.

cs.AR↗
arXiv2024

Light nuclei photoproduction in relativistic heavy ion ultraperipheral collisions

We have investigated light nuclei pair photoproduction in relativistic heavy ion ultraperipheral collisions. As a first attempt, we employ our previously developed quantum electrodynamics model, which incorporates a wave-packet description of initial nuclei, to compute the cross section for proton-antiproton pair photoproduction. The effective vertex for the photon and proton interaction is chosen based on studies of two-photon exchange effects in hadron physics. We present the transverse momentum, invariant mass, and azimuthal angle distributions of proton-antiproton pairs at $\sqrt{s_{NN}}=200$ GeV in Au+Au ultraperipheral collisions. We observe a $\cos(2ϕ)$ modulation and an almost negligible $\cos(4ϕ)$ modulation in the azimuthal angle distribution. Our studies helps us better understand the matter generated by light.

hep-ph↗
arXiv2024

Bell nonlocality and entanglement in $e^{+}e^{-} \rightarrow Y\bar{Y}$ at BESIII

The Bell nonlocality and entanglement are two kinds of quantum correlations in quantum systems. Due to the recent upgrade in Beijing Spectrometer III (BESIII) experiment, it is possible to explore the nonlocality and entanglement in hyperon-antihyperon systems produced in electron-positron annihilation with high precision data. We provide a systematic method for studying quantum correlations in spin-1/2 hyperon-antihyperon systems through the measures for the nonlocality and entanglement. We find that with nonvanishing polarizations of the hyperon and its antihyperon, the kinematic region of nonlocality in the hyperon-antihyperon system is more restricted than the $τ^{+}τ^{-}$ system in which polarizations of $τ$ leptons are vanishing. We also present an experimental proposal to probe the nonlocality and entanglement in hyperon-antihyperon systems at BSEIII.

hep-ph↗
arXiv2024

Hadronic energy-momentum tensor revisited

Everything gravitates and they do so through the energy-momentum tensor (EMT). However, there is no consensus on how to define the EMT of a hadron, e.g. the proton, the fundamental building blocks of the visible world. In this work, we show that the hadronic EMT can be cast into the form of relativistic continua with spin. The fluid-like form allows a clear identification of the proper hadronic energy density, pressure and shear. A spin tensor contribution is also identified without the reference to the total angular momentum operator, in alignment with the recent development in relativistic spin hydrodynamics. The hadronic EMT is related to the quantum expectation value of the EMT operator through the convolution with the hadronic wavepacket. To factorize out the hadronic EMT, different multipole expansion schemes are explored. We show that the popular Breit-frame densities and light-front densities emerge as the monopole momentum densities from different factorization schemes.

hep-ph↗
arXiv2024

Exploring Communication Technologies, Standards, and Challenges in Electrified Vehicle Charging

As public awareness of environmental protection continues to grow, the trend of integrating more electric vehicles (EVs) into the transportation sector is rising. Unlike conventional internal combustion engine (ICE) vehicles, EVs can minimize carbon emissions and potentially achieve autonomous driving. However, several obstacles hinder the widespread adoption of EVs, such as their constrained driving range and the extended time required for charging. One alternative solution to address these challenges is implementing dynamic wireless power transfer (DWPT), charging EVs in motion on the road. Moreover, charging stations with static wireless power transfer (SWPT) infrastructure can replace existing gas stations, enabling users to charge EVs in parking lots or at home. This paper surveys the communication infrastructure for static and dynamic wireless charging in electric vehicles. It encompasses all communication aspects involved in the wireless charging process. The architecture and communication requirements for static and dynamic wireless charging are presented separately. Additionally, a comprehensive comparison of existing communication standards is provided. The communication with the grid is also explored in detail. The survey gives attention to security and privacy issues arising during communications. In summary, the paper addresses the challenges and outlines upcoming trends in communication for EV wireless charging.

cs.NI↗
arXiv2024

Linear response theory for spin alignment of vector mesons in thermal media

We present a calculation of the spin alignment for unflavored vector mesons in thermalized quark-gluon plasma based on the Kubo formula in linear response theory. This is achieved by expanding the system to the first order of the coupling constant and the spatial gradient. The effect strongly relies on the vector meson's spectral functions which are determined by the interaction and medium properties. The spectral functions are calculated for the one-quark-loop self-energy with meson-quark interaction. The numerical results show that the correction to the spin alignment from the thermal shear tensor is of the order $10^{-4}\sim10^{-5}$ for the chosen values of quark-meson coupling constant, if the magnitude of thermal shear tensor is $10^{-2}$.

hep-ph↗
arXiv2024

Generalized quantum measurement in spin-correlated hyperon-antihyperon decays

The rapid developments of Quantum Information Science (QIS) have opened up new avenues for exploring fundamental physics. Quantum nonlocality, a key aspect for distinguishing quantum information from classical one, has undergone extensive examinations in particles' decays through the violation of Bell-type inequalities. Despite these advancements, a comprehensive framework based on quantum information theory for particle interaction is still lacking. Trying to close this gap, we introduce a generalized quantum measurement description for decay processes of spin-1/2 hyperons. We validate this approach by aligning it with established theoretical calculations and apply it to the joint decay of correlated $Λ\barΛ$ pairs. We employ quantum simulation to observe the violation of CHSH inequalities in hyperon decays. Our generalized measurement description is adaptable and can be extended to a variety of high energy processes, including decays of vector mesons, $J/ψ,ψ(2S)\rightarrowΛ\barΛ$, in the Beijing Spectrometer III (BESIII) experiment at the Beijing Electron Positron Collider (BEPC). The methodology developed in this study can be applied to quantum correlation and information processing in fundamental interactions.

hep-ph↗
arXiv2024

Global quark spin correlations in relativistic heavy ion collisions

The observation of the vector meson's global spin alignment by the STAR Collaboration reveals that strong spin correlations may exist for quarks and antiquarks in relativistic heavy-ion collisions in the normal direction of the reaction plane. We propose a systematic method to describe such correlations in the quark matter. The correlations can be classified as local and long range types. We show in particular that the effective quark spin correlations contain the genuine spin correlations originated directly from the dynamical process as well as those induced by averaging over other degrees of freedom. We also show that such correlations can be studied by measuring the vector meson's spin density matrix and hyperon-hyperon and hyperon-anti-hyperon spin correlations. We present the relationships between these measurable quantities and spin correlations of quarks and antiquarks.

hep-ph↗
arXiv2024

Spin polarization in relativistic heavy-ion collisions

Polarization has opened a new physics chapter in relativistic heavy-ion collisions. Since the first prediction and experimental observation of global spin polarization, a lot of progress has been made in understanding its features, both at experimental and theoretical level. In this paper, we give an overview on the recent advances in this field. The covered topics include a review of measurements of global and local spin polarization of hyperons and the global spin alignment of vector mesons. We account for the basic theoretical framework to describe spin polarization in a relativistic fluid such as the Quark Gluon Plasma, including statistical quantum field theory and local thermodynamic equilibrium, spin hydrodynamics, relativistic kinetic theory with spin and coalescence models.

nucl-th↗
arXiv2024

The spin alignment of rho mesons in a pion gas

We study the spin alignment of neutral rho mesons in a pion gas using spin kinetic or Boltzmann equations. The $ρππ$ coupling is given by the chiral effective theory. The collision terms at the leading and next-to-leading order in spin Boltzmann equations are derived. The evolution of the spin density matrix of the neutral rho meson is simulated with different initial conditions. The numerical results show that the interaction of pions and neutral rho mesons creates very small spin alignment in the central rapidity region if there is no rho meson in the system at the initial time. Such a small spin alignment in the central rapidity region will decay rapidly toward zero in later time. If there are rho mesons with a sizable spin alignment at the initial time the spin alignment will also decrease rapidly. We also considered the effect on $ρ_{00}$ from the elliptic flow of pions in the blast wave model. With vanishing spin alignment at the initial time, the deviation of $ρ_{00}$ from 1/3 is positive but very small.

nucl-th↗
arXiv2024

Physics-Augmented Data-EnablEd Predictive Control for Eco-driving of Mixed Traffic Considering Diverse Human Behaviors

Data-driven cooperative control of connected and automated vehicles (CAVs) has gained extensive research interest as it can utilize collected data to generate control actions without relying on parametric system models that are generally challenging to obtain. Existing methods mainly focused on improving traffic safety and stability, while less emphasis has been placed on energy efficiency in the presence of uncertainties and diversities of human-driven vehicles (HDVs). In this paper, we employ a data-enabled predictive control (DeePC) scheme to address the eco-driving of mixed traffic flows with diverse behaviors of human drivers. Specifically, by incorporating the physical relationship of the studied system and the Hankel matrix update from the generalized behavior representation to a particular one, we develop a new Physics-Augmented Data-EnablEd Predictive Control (PA-DeePC) approach to handle human driver diversities. In particular, a power consumption term is added to the DeePC cost function to reduce the holistic energy consumption of both CAVs and HDVs. Simulation results demonstrate the effectiveness of our approach in accurately capturing random human driver behaviors and addressing the complex dynamics of mixed traffic flows, while ensuring driving safety and traffic efficiency. Furthermore, the proposed optimization framework achieves substantial reductions in energy consumption, i.e., average reductions of 4.83% and 9.16% when compared to the benchmark algorithms.

eess.SY↗
arXiv2024

Safe Reinforcement Learning-Based Eco-Driving Control for Mixed Traffic Flows With Disturbances

This paper presents a safe learning-based eco-driving framework tailored for mixed traffic flows, which aims to optimize energy efficiency while guaranteeing safety during real-system operations. Even though reinforcement learning (RL) is capable of optimizing energy efficiency in intricate environments, it is challenged by safety requirements during the training process. The lack of safety guarantees is the other concern when deploying a trained policy in real-world application. Compared with RL, model predicted control (MPC) can handle constrained dynamics systems, ensuring safe driving. However, the major challenges lie in complicated eco-driving tasks and the presence of disturbances, which respectively challenge the MPC design and the satisfaction of constraints. To address these limitations, the proposed framework incorporates the tube-based enhanced MPC (RMPC) to ensure the safe execution of the RL policy under disturbances, thereby improving the control robustness. RL not only optimizes the energy efficiency of the connected and automated vehicle in mixed traffic but also handles more uncertain scenarios, in which the energy consumption of the human-driven vehicle and its diverse and stochastic driving behaviors are considered in the optimization framework. Simulation results demonstrate that the proposed algorithm, compared with RMPC technique, shows an average improvement of 10.88% in holistic energy efficiency, while compared with RL algorithm, it effectively prevents inter-vehicle collisions.

eess.SY↗
arXiv2023

ACT-Net: Anchor-context Action Detection in Surgery Videos

Recognition and localization of surgical detailed actions is an essential component of developing a context-aware decision support system. However, most existing detection algorithms fail to provide high-accuracy action classes even having their locations, as they do not consider the surgery procedure's regularity in the whole video. This limitation hinders their application. Moreover, implementing the predictions in clinical applications seriously needs to convey model confidence to earn entrustment, which is unexplored in surgical action prediction. In this paper, to accurately detect fine-grained actions that happen at every moment, we propose an anchor-context action detection network (ACTNet), including an anchor-context detection (ACD) module and a class conditional diffusion (CCD) module, to answer the following questions: 1) where the actions happen; 2) what actions are; 3) how confidence predictions are. Specifically, the proposed ACD module spatially and temporally highlights the regions interacting with the extracted anchor in surgery video, which outputs action location and its class distribution based on anchor-context interactions. Considering the full distribution of action classes in videos, the CCD module adopts a denoising diffusion-based generative model conditioned on our ACD estimator to further reconstruct accurately the action predictions. Moreover, we utilize the stochastic nature of the diffusion model outputs to access model confidence for each prediction. Our method reports the state-of-the-art performance, with improvements of 4.0% mAP against baseline on the surgical video dataset.

cs.CV↗
arXiv2023

Momentum dependence of $ϕ$ meson's spin alignment

We study the rapidity and azimuthal angle dependences of the global spin alignment $ρ_{00}$ for $ϕ$ mesons with respect to the reaction plane in Au+Au collisions at RHIC by the relativistic coalescence model in the spin transport theory. The global spin alignment of $ϕ$ mesons arises from local fluctuations of strong force fields whose values are extracted from the STAR's data. The calculated results show that $ρ_{00}<1/3$ at the rapidity $Y=0$, and then it increases with rapidity and becomes $ρ_{00}>1/3$ at $Y=1$. Such a rapidity dependence is dominated by the relative motion of the $ϕ$ meson in the bulk matter. We also give prediction for the azimuthal angle dependence of $ρ_{00}$ at different rapidities.

nucl-th↗
arXiv2023

RBG-Maxwell Framework: Simulation of Collisional Plasma Systems via Coupled Boltzmann-Maxwell equations on GPU

This paper presents the RBG-Maxwell framework, a relativistic collisional plasma simulator on GPUs. We provide detailed discussions on the fundamental equations, numerical algorithms, implementation specifics, and key testing outcomes. The RBG-Maxwell framework is a robust numerical code designed for simulating the evolution of plasma systems through a kinetic approach on large-scale GPUs. It offers easy adaptability to a wide range of physical systems. Given the appropriate initial distributions, particle masses, charges, differential cross-sections, and external forces (which are not confined to electromagnetic forces), the RBG-Maxwell framework can direct the evolution of a particle system from a non-equilibrium state to a thermal state.

physics.plasm-ph↗
arXiv2023

CSMAAFL: Client Scheduling and Model Aggregation in Asynchronous Federated Learning

Asynchronous federated learning aims to solve the straggler problem in heterogeneous environments, i.e., clients have small computational capacities that could cause aggregation delay. The principle of asynchronous federated learning is to allow the server to aggregate the model once it receives an update from any client rather than waiting for updates from multiple clients or waiting a specified amount of time in the synchronous mode. Due to the asynchronous setting, the stale model problem could occur, where the slow clients could utilize an outdated local model for their local data training. Consequently, when these locally trained models are uploaded to the server, they may impede the convergence of the global training. Therefore, effective model aggregation strategies play a significant role in updating the global model. Besides, client scheduling is also critical when heterogeneous clients with diversified computing capacities are participating in the federated learning process. This work first investigates the impact of the convergence of asynchronous federated learning mode when adopting the aggregation coefficient in synchronous mode. The effective aggregation solutions that can achieve the same convergence result as in the synchronous mode are then proposed, followed by an improved aggregation method with client scheduling. The simulation results in various scenarios demonstrate that the proposed algorithm converges with a similar level of accuracy as the classical synchronous federated learning algorithm but effectively accelerates the learning process, especially in its early stage.

cs.DC↗