599 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 utilizes FDTD simulations to demonstrate that optimizing the incident angle of an injected wave is essential for efficient O-X mode conversion and Electron Bernstein Wave excitation in non-uniform magnetized plasmas, as deviations from this angle create evanescent regions that cause significant wave attenuation.
By employing a multi-hierarchy framework that couples MHD and particle-in-cell simulations to solve a two-dimensional Riemann problem, this study demonstrates that Petschek-like reconnection with switch-off slow shocks remains viable in collisionless-collisional systems like solar flares, as these shocks can form in the MHD domain even when suppressed in the PIC domain, subsequently promoting plasma isotropization.
This study provides the first experimental evidence that geometric anisotropy in finite dusty plasma crystals governs inhomogeneous melting by enabling confinement-controlled mode coupling with laser heating to trigger localized structural destabilization.
This paper presents a new AI-based platform developed at CEA Paris-Saclay to optimize superconducting magnet design for particle accelerators by leveraging machine learning and advanced techniques to manage complex datasets and address challenges in multiphysics modeling, topology optimization, and anomaly detection.
This paper introduces a novel approach using physics-informed neural networks to parametrize Fourier modes for computing three-dimensional magnetohydrodynamic equilibria, demonstrating that the method can achieve competitive computational costs and establish new lower bounds for force residuals compared to conventional solvers.
This paper introduces a novel numerical method using multilayer perceptrons within the DESC solver to generate a continuous distribution of stellarator equilibria with fixed boundaries and rotational transform by varying the pressure invariant, thereby overcoming the limitation of conventional approaches that yield only single stationary solutions.
This paper utilizes numerical simulations with the Spacecraft Plasma Interaction Software to model and validate how photo- and secondary electron emissions from the Solar Orbiter spacecraft contaminate low-energy electron measurements by the SWA-EAS instrument, revealing that such contamination extends well above the spacecraft potential threshold due to emissions from distant surfaces and highlighting a discrepancy between the simulated and observed spectral breaks that suggests a difference between the detector's actual and measured potentials.
This paper proposes a thermodynamic model of plasma boundary layers that explains the formation of transport barriers through bifurcation into a high-gradient state, contingent on both the heat flux exceeding a critical value and the edge temperature surpassing a specific threshold, with optimal confinement occurring at a particular temperature where incoming power is converted into coherent motions rather than diffusive processes.
This study utilizes fully kinetic particle-in-cell simulations to reveal a thickness-dependent transition in electron-scale current sheets, where wider layers evolve through a velocity-shear-driven Kelvin-Helmholtz instability before tearing, while thinner layers remain dominated by electron inertial tearing.
This paper presents new analytic continuation results for the dynamic structure factor of the uniform electron liquid across a broad temperature range by comparing traditional maximum entropy and sparse Gaussian kernel methods applied to *ab initio* path integral Monte Carlo data, with implications for x-ray Thomson scattering experiments and time-dependent density functional theory.