727 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 paper systematically compares VMEC and HINT equilibrium calculations for Large Helical Device plasmas, revealing that while both codes agree at low beta, they diverge at higher beta values as HINT captures edge stochasticity and flux surface breaking that the nested-flux-surface assumption of VMEC cannot represent.
This paper presents a real-time safe multi-threading library developed for the DIII-D plasma control system that successfully optimizes the execution of the TORBEAM and STRIDE physics codes to under 20 ms and 100 ms, respectively, enabling crucial electron cyclotron wave propagation and stability limit calculations for future fusion power plants.
This study uses one-dimensional kinetic simulations to demonstrate that while the linear growth of the Bell instability is governed solely by cosmic ray current regardless of distribution, its saturation is strongly dependent on the momentum spectrum, with power-law distributions showing distinct relaxation behaviors that lead to a modified saturation prescription and a proposed layered confinement scenario upstream of astrophysical shocks.
This study presents the first in vivo investigation demonstrating that laser-driven ultra-high dose rate protons reduce normal tissue swelling compared to conventional X-rays, while inducing distinct immune and epidermal gene expression changes, thereby providing initial evidence for the FLASH effect using this novel acceleration method.
This study utilizes superposed epoch analysis of over 1600 CMEs from 0.2 to 2.2 au to reveal that CMEs during the solar active phase are faster and magnetically stronger than those in the quiet phase due to intrinsic eruption differences, while also demonstrating that CME magnetic ejecta expand uniformly in toroidal and poloidal dimensions and exhibit increasing magnetic field asymmetry with heliocentric distance.
This paper reports the first direct experimental measurement of ion properties in a Capacitively Coupled Plasma using Laser Induced Fluorescence, revealing that ions exhibit faster directional flow and higher temperatures than previously assumed, with flow reductions observed in the presence of dust particles.
This paper proposes that Fast Radio Bursts originate from the rapid collapse and breaking of macroscopic X-mode waves in highly magnetized pair plasma near neutron stars, a process that concentrates electromagnetic energy into short, bright pulses while generating a red spectrum and exceptionally hard particle distributions.
This paper utilizes the ORB5 gyrokinetic code to demonstrate that the nonlinear amplitude oscillations of energetic-particle induced geodesic acoustic modes (EGAMs) in tokamak plasmas share the same physical mechanisms and scaling laws as the beam-plasma instability, leading to the proposal of a novel diagnostic for evaluating EGAM intensity.
This paper presents a machine learning-driven, physics-guided reduced model for predicting Electron Temperature Gradient (ETG) turbulence heat flux in the Wendelstein 7-X stellarator, which achieves high accuracy through active learning and radial interpolation but reveals that a single radius-independent formulation is insufficient to capture the device's geometry-dependent transport physics.
The paper introduces TokaMind, the first open-source multi-modal transformer foundation model pretrained on heterogeneous MAST tokamak data, which demonstrates superior performance across 14 diverse plasma dynamics tasks compared to state-of-the-art baselines.