627 papers
Plasma physics explores the behavior of the fourth state of matter, a superheated soup of charged particles that makes up most of the visible universe. From the fusion power we hope to harness on Earth to the glowing auroras and distant stars above, this field investigates how these energetic gases interact with magnetic fields and light. It is a dynamic area where extreme conditions reveal fundamental laws of nature in ways solid matter never can.
At Gist.Science, we bridge the gap between these complex discoveries and curious minds by processing every new preprint from arXiv in this category. We transform dense, technical research into clear, plain-language explanations alongside detailed summaries, ensuring that breakthroughs in plasma dynamics and fusion energy are accessible to everyone. Below are the latest papers in plasma physics, curated and simplified for your reading.
This study demonstrates that beating two co-propagating laser pulses on a smooth cylindrical plasma-vacuum interface can resonantly excite high-amplitude surface plasmon wakefields, offering a pathway toward portable laser-driven plasma accelerators using state-of-the-art fiber lasers.
This paper presents quantitative 3D non-linear JOREK simulations of shattered pellet injection in ASDEX Upgrade, demonstrating that incorporating a simplified parallel heat-flux limiting treatment resolves previous discrepancies with experimental data to enable reliable predictions of thermal quench duration and radiation fraction for ITER disruption mitigation.
This paper presents a novel structure-preserving framework for the Vlasov-Poisson-Landau system that combines particle-in-cell discretization with discrete gradient time integrators to guarantee the conservation of mass, momentum, and energy while preserving entropy production monotonicity in both continuous and discrete settings.
This paper introduces a novel numerical method for kinetic plasma simulation that combines Strang splitting with fully spectral Vlasov-Poisson solvers by representing the phase-space distribution function and operators as adaptive low-rank tensor networks, thereby enabling efficient time stepping and self-consistent field calculations directly in compressed form without reconstructing the full phase-space grid.
This paper introduces a method for deriving exact moment models and particle simulations for conservation laws in phase space by parameterizing the distribution function with centered moments, ensuring the parameterized function exactly solves the underlying hyperbolic equations, and demonstrates its application to non-relativistic and relativistic Vlasov–Maxwell systems.
This paper rigorously interprets surface helicity as a measure of field line linking and proves its dependence on surface topology, then applies these findings to toroidal surfaces in plasma physics to connect helicity with rotational transform, optimize coil designs for fusion devices, and identify symmetric toroidal surfaces as global minimizers of helicity.
This paper provides a mathematically rigorous derivation of the zero-order approximation for charged particle motion in strong magnetic fields to establish a displacement formula for plasma pressure and offer a qualitative estimate of confinement time for optimized equilibria, thereby advancing the theoretical understanding of plasma fusion confinement.
This paper introduces a refactored, object-oriented version of the GMGPolar geometric multigrid solver that utilizes matrix-free implementations, the Sherman-Morrison formula, and cache-optimized reordering to achieve significant speedups (up to 37x) and reduced memory usage for solving 2D gyrokinetic Poisson equations in tokamak fusion plasma simulations.
This paper investigates relativistic modulational instability in magnetized plasma driven by strong laser pulses, deriving a nonlinear Schrödinger equation to analyze the maximum growth rate and dynamics of wave dispersion, intensity dependence, and damping effects using perturbation techniques.
This paper introduces TokaMark, a comprehensive, open-source benchmark designed to overcome data fragmentation in fusion research by providing standardized tools, curated multi-modal datasets from the MAST tokamak, and a unified evaluation framework for advancing AI-driven plasma modeling.