arXiv subjects

Shi Pu

Publications and source records attributed to Shi Pu.

At least 55 records · Page 3Linked to original sources

arXiv2024

Corrections from space-time dependent electromagnetic fields to Wigner functions and spin polarization

We have derived the Wigner equations at global equilibrium with constant vorticity but space-time dependent electromagnetic fields up to second order in semiclassical expansion. We obtain the new second-order contributions to the charge currents and energy-momentum tensor from the varying electromagnetic fields. We also compute the new corrections to the spin polarization pesudo-vector from both contant and varying electromagnetic fields. We also find that the space-time dependent electromagnetic field provides a tighter constraint on the solutions of Wigner functions in global equilibrium compared with constant electromagnetic field.

hep-ph↗

arXiv2024

Spin polarization of $Λ$ hyperons along beam direction in p+Pb collisions at $\sqrt{s_{NN}}=8.16$ TeV using hydrodynamic approaches

We have implemented the 3+1 dimensional CLVisc hydrodynamics model with TRENTO-3D initial conditions to investigate the spin polarization of $Λ$ hyperons along the beam direction in p+Pb collisions at $\sqrt{s_{NN}} = 8.16$ TeV. Following our previous theoretical framework based on quantum kinetic theory, we consider three different scenarios: $Λ$ equilibrium, $s$ quark equilibrium, and iso-thermal equilibrium scenarios. We have computed the second Fourier sine coefficients of spin polarization along the beam direction, denoted as $\left\langle P_{z} \sin 2(ϕ_{p} - Ψ_{2}) \right\rangle$, with $ϕ_{p} - Ψ_{2}$ being the azimuthal angle relative to the second-order event plane $Ψ_{2}$, as functions of multiplicity, transverse momentum and pseudo-rapidity in the three scenarios. Additionally, we have also computed the spin polarization along the beam direction, $P_{z}$, as a function of the azimuthal angle. We find that the spin polarization induced by thermal vorticity always provides an opposite contribution compared to the shear-induced polarization in p+Pb collisions. The total spin polarization computed by the current hydrodynamic model disagrees with the data measured by LHC-CMS experiments. Our findings imply that other non-flow effects may play a crucial role in p+Pb collisions.

hep-ph↗

arXiv2024

Thermodynamic stability in relativistic viscous and spin hydrodynamics

We have applied thermodynamic stability analysis to derive the stability and causality conditions for conventional relativistic viscous hydrodynamics and spin hydrodynamics. We obtain the thermodynamic stability conditions for second-order relativistic hydrodynamics with shear and bulk viscous tensors, finding them identical to those derived from linear mode analysis. We then derive the thermodynamic stability conditions for minimal causal extended second-order spin hydrodynamics in canonical form, both with and without viscous tensors. Without viscous tensors, the constraints from thermodynamic stability exactly match those from linear mode analysis. In the presence of viscous tensors, the thermodynamic stability imposes more stringent constraints than those obtained from linear mode analysis. Our results suggest that conditions derived from thermodynamic stability analysis can guarantee both causality and stability in linear mode analysis.

nucl-th↗

arXiv2024

Late-time asymptotic solutions, attractor, and focusing behavior of spin hydrodynamics

We have investigated the late-time asymptotic solutions, attractor, and focusing behavior of minimal causal spin hydrodynamics in Bjorken expansion. Using the method of dominant balance, we derive the late-time asymptotic solutions of the evolution equation for spin density and identify the specific conditions necessary for the spin density to exhibit a power-law decay. We then analyze both the late-time and early-time attractors for the decay rate of spin density. Additionally, we report the focusing behavior in spin hydrodynamics, which has not been found in conventional relativistic hydrodynamics in Bjorken expansion. Our findings suggest that spin density can be treated as a conventional hydrodynamic variable at late times under certain conditions.

hep-ph↗

arXiv2024

A Robust Compressed Push-Pull Method for Decentralized Nonconvex Optimization

In the modern paradigm of multi-agent networks, communication has become one of the main bottlenecks for decentralized optimization, where a large number of agents are involved in minimizing the average of the local cost functions. In this paper, we propose a robust compressed push-pull algorithm (RCPP) that combines gradient tracking with communication compression. In particular, RCPP is robust under a much more general class of compression operators that allow both relative and absolute compression errors, in contrast to the existing works which can handle either one of them or assume convex problems. We show that RCPP enjoys sublinear convergence rate for smooth and possibly nonconvex objective functions over general directed networks. Moreover, under the additional Polyak-Łojasiewicz condition, linear convergence rate can be achieved for RCPP. Numerical examples verify the theoretical findings and demonstrate the efficiency, flexibility, and robustness of the proposed algorithm.

math.OC↗

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

HARE: HumAn pRiors, a key to small language model Efficiency

Human priors play a crucial role in efficiently utilizing data in deep learning. However, with the development of large language models (LLMs), there is an increasing emphasis on scaling both model size and data volume, which often diminishes the importance of human priors in data construction. Influenced by these trends, existing Small Language Models (SLMs) mainly rely on web-scraped large-scale training data, neglecting the proper incorporation of human priors. This oversight limits the training efficiency of language models in resource-constrained settings. In this paper, we propose a principle to leverage human priors for data construction. This principle emphasizes achieving high-performance SLMs by training on a concise dataset that accommodates both semantic diversity and data quality consistency, while avoiding benchmark data leakage. Following this principle, we train an SLM named HARE-1.1B. Extensive experiments on large-scale benchmark datasets demonstrate that HARE-1.1B performs favorably against state-of-the-art SLMs, validating the effectiveness of the proposed principle. Additionally, this provides new insights into efficient language model training in resource-constrained environments from the view of human priors.

cs.CL↗

arXiv2024

Optimal Gradient Tracking for Decentralized Optimization

In this paper, we focus on solving the decentralized optimization problem of minimizing the sum of $n$ objective functions over a multi-agent network. The agents are embedded in an undirected graph where they can only send/receive information directly to/from their immediate neighbors. Assuming smooth and strongly convex objective functions, we propose an Optimal Gradient Tracking (OGT) method that achieves the optimal gradient computation complexity $O\left(\sqrtκ\log\frac{1}ε\right)$ and the optimal communication complexity $O\left(\sqrt{\fracκθ}\log\frac{1}ε\right)$ simultaneously, where $κ$ and $\frac{1}θ$ denote the condition numbers related to the objective functions and the communication graph, respectively. To our knowledge, OGT is the first single-loop decentralized gradient-type method that is optimal in both gradient computation and communication complexities. The development of OGT involves two building blocks which are also of independent interest. The first one is another new decentralized gradient tracking method termed "Snapshot" Gradient Tracking (SS-GT), which achieves the gradient computation and communication complexities of $O\left(\sqrtκ\log\frac{1}ε\right)$ and $O\left(\frac{\sqrtκ}θ\log\frac{1}ε\right)$, respectively. SS-GT can be potentially extended to more general settings compared to OGT. The second one is a technique termed Loopless Chebyshev Acceleration (LCA) which can be implemented "looplessly" but achieve similar effect with adding multiple inner loops of Chebyshev acceleration in the algorithms. In addition to SS-GT, this LCA technique can accelerate many other gradient tracking based methods with respect to the graph condition number $\frac{1}θ$.

math.OC↗

arXiv2024

Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks

In this paper, we propose two communication efficient decentralized optimization algorithms over a general directed multi-agent network. The first algorithm, termed Compressed Push-Pull (CPP), combines the gradient tracking Push-Pull method with communication compression. We show that CPP is applicable to a general class of unbiased compression operators and achieves linear convergence rate for strongly convex and smooth objective functions. The second algorithm is a broadcast-like version of CPP (B-CPP), and it also achieves linear convergence rate under the same conditions on the objective functions. B-CPP can be applied in an asynchronous broadcast setting and further reduce communication costs compared to CPP. Numerical experiments complement the theoretical analysis and confirm the effectiveness of the proposed methods.

math.OC↗

arXiv2024

Spin polarization and spin alignment from quantum kinetic theory with self-energy corrections

We derive the quantum kinetic theory for massive fermions with collision terms and self-energy corrections based on quantum field theory. We adopt an effective power counting scheme with $\hbar$ expansion to obtain the leading-order perturbative solutions of the vector and axial Wigner functions and the corresponding kinetic equations. We observe that both the onshell relation and the structure of Wigner functions, along with the kinetic equations, are modified due to the presence of self-energies and their space-time gradients. We further apply our formalism to investigate the spin polarization phenomena in relativistic heavy ion collisions and derive the modification to the spin polarization spectrum of massive quarks. We find that the gradient of vector self-energy plays a similar role to the background electromagnetic fields, which induces a more dominant contribution than the collisional effects by a naive power counting in the gradient expansion and weak coupling. Our findings could further modify the spin polarization of strange quarks and spin alignment of $ϕ$ mesons beyond local thermal equilibrium.

hep-ph↗

arXiv2024

Stability and causality criteria in linear mode analysis: stability means causality

Causality and stability are fundamental requirements for the differential equations describing predictable relativistic many-body systems. In this work, we investigate the stability and causality criteria in linear mode analysis. We discuss the updated stability criterion in 3+1 dimensional systems and introduce the improved sufficient criterion for causality. Our findings clearly demonstrate that stability implies causality in linear mode analysis. Furthermore, based on the theorems present in this work, we conclude that if updated stability criterion and improved causality criterion are fulfilled in one inertial frame of reference (IFR), they hold for all IFR.

hep-th↗

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↗

arXiv2023

Distributed Stochastic Optimization under a General Variance Condition

Distributed stochastic optimization has drawn great attention recently due to its effectiveness in solving large-scale machine learning problems. Though numerous algorithms have been proposed and successfully applied to general practical problems, their theoretical guarantees mainly rely on certain boundedness conditions on the stochastic gradients, varying from uniform boundedness to the relaxed growth condition. In addition, how to characterize the data heterogeneity among the agents and its impacts on the algorithmic performance remains challenging. In light of such motivations, we revisit the classical Federated Averaging (FedAvg) algorithm (McMahan et al., 2017) as well as the more recent SCAFFOLD method (Karimireddy et al., 2020) for solving the distributed stochastic optimization problem and establish the convergence results under only a mild variance condition on the stochastic gradients for smooth nonconvex objective functions. Almost sure convergence to a stationary point is also established under the condition. Moreover, we discuss a more informative measurement for data heterogeneity as well as its implications.

math.OC↗

arXiv2023

Global and local polarization of $Λ$ hyperons across RHIC-BES energies

We report our recent study on the global and local polarization of $Λ$ hyperons in Au+Au collisions at RHIC-BES energies within the (3+1)-dimensional CLVisc hydrodynamics framework. We present our numerical results for the global polarization as the function of collision energies and the local polarization along the beam direction as functions of azimuthal angle in $20-50$% centrality at $\sqrt{s_{NN}}$=7.7 GeV Au+Au collision energy. We have discussed the effects of initial conditions, Spin Hall effect and baryon diffusion.

nucl-th↗

arXiv2023

Provably Accelerated Decentralized Gradient Method Over Unbalanced Directed Graphs

We consider the decentralized optimization problem, where a network of $n$ agents aims to collaboratively minimize the average of their individual smooth and convex objective functions through peer-to-peer communication in a directed graph. To tackle this problem, we propose two accelerated gradient tracking methods, namely APD and APD-SC, for non-strongly convex and strongly convex objective functions, respectively. We show that APD and APD-SC converge at the rates $O\left(\frac{1}{k^2}\right)$ and $O\left(\left(1 - C\sqrt{\fracμ{L}}\right)^k\right)$, respectively, up to constant factors depending only on the mixing matrix. APD and APD-SC are the first decentralized methods over unbalanced directed graphs that achieve the same provable acceleration as centralized methods. Numerical experiments demonstrate the effectiveness of both methods.

math.OC↗

arXiv2023

Causality and stability analysis for the minimal causal spin hydrodynamics

We perform the linear analysis of causality and stability for a minimal extended spin hydrodynamics up to second order of the gradient expansion. The first order spin hydrodynamics, with a rank-3 spin tensor being antisymmetric for only the last two indices, are proved to be acausal and unstable. We then consider the minimal causal spin hydrodynamics up to second order of the gradient expansion. We derive the necessary causality and stability conditions for this minimal causal spin hydrodynamics. Interestingly, the satisfaction of the stability conditions relies on the equations of state for the spin density and chemical potentials. Moreover, different with the conventional relativistic dissipative hydrodynamics, the stability of the theory seems to be broken at the finite wave-vector when the stability conditions are fulfilled at small and large wave-vector limits. It implies that the behavior in small and large wave-vector limits may be insufficient to determine the stability conditions for spin hydrodynamics in linear mode analysis.

hep-ph↗

arXiv2023

Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning

With the help of conditioning mechanisms, the state-of-the-art diffusion models have achieved tremendous success in guided image generation, particularly in text-to-image synthesis. To gain a better understanding of the training process and potential risks of text-to-image synthesis, we perform a systematic investigation of backdoor attack on text-to-image diffusion models and propose BadT2I, a general multimodal backdoor attack framework that tampers with image synthesis in diverse semantic levels. Specifically, we perform backdoor attacks on three levels of the vision semantics: Pixel-Backdoor, Object-Backdoor and Style-Backdoor. By utilizing a regularization loss, our methods efficiently inject backdoors into a large-scale text-to-image diffusion model while preserving its utility with benign inputs. We conduct empirical experiments on Stable Diffusion, the widely-used text-to-image diffusion model, demonstrating that the large-scale diffusion model can be easily backdoored within a few fine-tuning steps. We conduct additional experiments to explore the impact of different types of textual triggers, as well as the backdoor persistence during further training, providing insights for the development of backdoor defense methods. Besides, our investigation may contribute to the copyright protection of text-to-image models in the future.

cs.CR↗