arXiv subjects

Naixin Liang

Publications and source records attributed to Naixin Liang.

6 recordsLinked to original sources

arXiv2026

Beyond the Diffusion Coefficient: Propagators and Memory in Cosmic Ray Transport

Cosmic ray (CR) transport is usually modeled with a single diffusion coefficient, but this description captures only the growth of the variance and not the full transport process. Distinct transport mechanisms can share the same effective diffusion coefficient while producing different particle distributions and approaches to the diffusive limit. This limitation is especially relevant in realistic multiphase, structured, and time-dependent media, and is also reflected in observed environmental variations in CR transport near pulsar wind nebulae, supernova remnants, and molecular clouds. Particle-tracing studies also show clear departures from standard diffusion, including both superdiffusion and subdiffusion. We therefore develop a propagator-based framework centered on $P(x,t)$, the probability distribution of particle positions, or equivalently its Fourier-Laplace transform $P(k,s)$. This object is compact and statistically complete, and naturally exposes memory: the CR flux can depend on earlier gradients when unresolved trapping or phase changes are coarse-grained away. Using the Montroll-Weiss formalism, we show how to measure $P(k,s)$ directly from trajectories, how to recover the associated memory kernel, and how to represent broad kernels efficiently with a Prony expansion. Applied to a multiphase medium, the framework shows that slow regions can regulate escape without dominating the total residence-time budget. We also introduce an accelerated Monte Carlo method for coarse-grained transport, and show that if trapping structures evolve while particles are still sampling them, the static long-time limit need not be reached. This paper provides the foundation for future observational applications, particle-tracing measurements, and CR-MHD closures.

astro-ph.HE↗

arXiv2026

Hybrid Simulations of Supersonic Shear Flows: II) Cosmic Ray Viscosity

In this second paper in a series dedicated to characterizing shear layers via 2D hybrid (kinetic ions -- fluid electrons) simulations, we study the dynamical role of nonthermal particles (cosmic rays, CRs), either spontaneously generated or pre-existing. We initialize Kolmogorov-type sinusoidal velocity shear flows unstable to the Kelvin--Helmholtz instability, which evolve nonlinearly into turbulence. Particles with large gyroradii act as long-range messengers that promote momentum exchange between layers, hence introducing a form of CR viscosity. Even when not energetically dominant, increasing the CR energy density generally enhances momentum transfer, provided that their gyroradii are smaller than the shear lengthscale. We consider flows ranging from subsonic to supersonic and assess the rate of shear dissipation, the partition of the initial kinetic energy among heating, thermal ion acceleration, CR reacceleration, and magnetic-field amplification, and the maximum energy attained by accelerated particles.

astro-ph.HE↗

arXiv2025

Particle Acceleration in Magnetized Shear-Driven Turbulence

Shear flows, ubiquitous in space and astrophysical plasmas, can accelerate particles through turbulence excited by the Kelvin-Helmholtz instability. We present the first numerical study of particle acceleration in sustained, subsonic, non-relativistic, and magnetized turbulence driven purely by velocity shear, including full particle backreaction. Using two-dimensional MHD-PIC simulations with an initially uniform flow-aligned magnetic field and external stirring force, we demonstrate that, in this subsonic regime, sustained particle acceleration requires continuously driven turbulence, whereas freely decaying turbulence rapidly depletes its energy reservoirs and halts the acceleration. The acceleration mechanism operates through the systematic distortion of gyro-orbits by turbulent electric fields: acceleration phases extend the particle trajectory along the electric force, increasing the energy gain, while deceleration phases shorten the trajectory, reducing the energy loss. This asymmetry produces net energy gain despite stochastic fluctuations, with the mean energy change scaling quadratically with shear velocity, characteristic of second-order Fermi acceleration. Initially monoenergetic particles develop substantial non-thermal tails after the turbulence onset. The energization of particles that repeatedly cross shear layers follows geometric Brownian motion, yielding a log-normal distribution. High-energy particles exhibit pitch-angle anisotropy, becoming preferentially perpendicular to the flow-aligned magnetic field as their gyroradii exceed the turbulent layer width. These results establish shear-driven turbulence as a viable particle acceleration mechanism, providing a general model for particle energization in shear flows.

astro-ph.HE↗

arXiv2025

Hybrid Simulations of Supersonic Shear Flows: I) Particle Acceleration

Supersonic flows are ubiquitous in warm and cool media; their dissipation leads to heating, generation of nonthermal particles, and amplification of background magnetic fields. We present 2D hybrid (kinetic ions - fluid electrons) simulations of decaying shear flows across the subsonic-to-supersonic transition, finding that the canonical Kelvin-Helmholtz instability in subsonic cases gives way to the formation of shocklets in supersonic shears, where dissipation is faster and nonthermal particles are produced. We discuss the dependence on the flow Mach number of particle acceleration, the viscosity induced by kinetic effects, and the production of magnetic turbulence. We outline the potential impact of these findings for turbulence in the warm interstellar medium, for molecular clouds, and for accretion disks, leaving to a companion paper the discussion of the effects on the shear of self-generated and pre-existing energetic particles.

astro-ph.HE↗

arXiv2025

A Novel Evaluation Benchmark for Medical LLMs: Illuminating Safety and Effectiveness in Clinical Domains

Large language models (LLMs) hold promise in clinical decision support but face major challenges in safety evaluation and effectiveness validation. We developed the Clinical Safety-Effectiveness Dual-Track Benchmark (CSEDB), a multidimensional framework built on clinical expert consensus, encompassing 30 criteria covering critical areas like critical illness recognition, guideline adherence, and medication safety, with weighted consequence measures. Thirty-two specialist physicians developed and reviewed 2,069 open-ended Q&A items aligned with these criteria, spanning 26 clinical departments to simulate real-world scenarios. Benchmark testing of six LLMs revealed moderate overall performance (average total score 57.2%, safety 54.7%, effectiveness 62.3%), with a significant 13.3% performance drop in high-risk scenarios (p < 0.0001). Domain-specific medical LLMs showed consistent performance advantages over general-purpose models, with relatively higher top scores in safety (0.912) and effectiveness (0.861). The findings of this study not only provide a standardized metric for evaluating the clinical application of medical LLMs, facilitating comparative analyses, risk exposure identification, and improvement directions across different scenarios, but also hold the potential to promote safer and more effective deployment of large language models in healthcare environments.

cs.CL↗

arXiv2025

Lévy Flights and Leaky Boxes: Anomalous Diffusion of Cosmic Rays

In classical diffusion, particle step-sizes have a Gaussian distribution. However, in superdiffusion, they have power-law tails, with transport dominated by rare, long Lévy flights. Similarly, if the time interval between scattering events has power-law tails, subdiffusion occurs. Both forms of anomalous diffusion are seen in cosmic ray (CR) particle tracking simulations in turbulent magnetic fields. They also likely occur if CRs are scattered by discrete intermittent structures. Anomalous diffusion mimics a scale-dependent diffusion coefficient, with potentially wide-ranging consequences. However, the finite size of galaxies implies an upper bound on step-sizes before CRs escape. This truncation results in eventual convergence to Gaussian statistics by the central limit theorem. Using Monte-Carlo simulations, we show that this occurs in both standard finite-thickness halo models, or when CR diffusion transitions to advection or streaming-dominated regimes. While optically thick intermittent structures produce power-law trapping times and thus subdiffusion, gaussianization also eventually occurs on timescales longer than the maximum trapping time. Anomalous diffusion is a transient, and converges to standard diffusion on the (usually short) timescale of particle escape, either from confining structures (subdiffusion), or the system as a whole (superdiffusion). Thus, standard assumptions of classical diffusion are physically justified in most applications, despite growing simulation evidence for anomalous diffusion. However, if escape times are long, this is no longer true. For instance, anomalous diffusion in the CGM or ICM would change CR pressure profiles. Finally, we show the standard diagnostic for anomalous diffusion, $\langle d^2 \rangle \propto t^α$ with $α\neq 1$, is not justified for truncated Lévy flights, and propose an alternative robust measure.

astro-ph.HE↗