Time-embedded convolutional neural networks for modeling plasma heat transport
Physical Review E American Physical Society (APS) 113:3 (2026) 035303
Abstract:
We introduce a time-embedded convolutional neural network (TCNN) for modeling spatiotemporal heat transport in plasmas, particularly under strongly nonlocal conditions. In our earlier work, the Luciani-Mora-Virmont (LMV) Informed Neural Network (LINN) (Luo , ) combined prior knowledge from the LMV model with kinetic Particle-in-Cell (PIC) data to improve kernel-based heat-flux predictions. While effective under moderately nonlocal conditions, LINN produced physically inconsistent kernels in strongly time-dependent regimes due to its reliance on the quasistationary LMV formulation. To overcome this limitation, TCNN is designed to capture the coupled evolution of both the normalized heat flux and the characteristic nonlocality parameter using a unified neural architecture informed by underlying physical principles. Trained on fully kinetic PIC simulations, TCNN accurately reproduces nonlocal dynamics across a broad range of collisionalities. Our results demonstrate that the combination of time modulation, coupled prediction, and convolutional depth significantly enhances predictive performance, offering a data-driven yet physically consistent framework for multiscale plasma transport problems.Suppression of pair beam instabilities in a laboratory analogue of blazar pair cascades
Proceedings of the National Academy of Sciences National Academy of Sciences 122:45 (2025) e2513365122
Abstract:
The generation of dense electron-positron pair beams in the laboratory can enable direct tests of theoretical models of γ-ray bursts and active galactic nuclei. We have successfully achieved this using ultrarelativistic protons accelerated by the Super Proton Synchrotron at (CERN). In the first application of this experimental platform, the stability of the pair beam is studied as it propagates through a meter-length plasma, analogous to TeV γ-ray-induced pair cascades in the intergalactic medium. It has been argued that pair beam instabilities disrupt the cascade, thus accounting for the observed lack of reprocessed GeV emission from TeV blazars. If true, this would remove the need for a moderate strength intergalactic magnetic field to explain the observations. We find that the pair beam instability is suppressed if the beam is not perfectly collimated or monochromatic, hence the lower limit to the intergalactic magnetic field inferred from γ-ray observations of blazars is robust.Learning heat transport kernels using a nonlocal heat transport theory-informed neural network
Physical Review Research American Physical Society (APS) 7:4 (2025) L042017
Abstract:
<jats:p>We present a data-driven framework for the modeling of nonlocal heat transport in plasmas using a nonlocal theory-informed neural network trained on kinetic particle-in-cell simulations that span both local and nonlocal regimes. The model learns spatio-temporal heat flux kernels directly from simulation data, capturing dynamic transport behaviors beyond the reach of classical formulations. Unlike time-independent kernel models such as Luciani-Mora-Virmont and Schurtz-Nicolaï-Busquet models, our approach yields physically grounded, time-evolving kernels that adapt to varying plasma conditions. The resulting predictions show strong agreement with kinetic benchmarks across regimes. This offers a promising direction for data-driven modeling of nonlocal heat transport and contributes to a deeper understanding of plasma dynamics.</jats:p>Numerical simulations of laser-driven experiments of ion acceleration in stochastic magnetic fields
Physics of Plasmas American Institute of Physics 31:12 (2024) 122105
Abstract:
We present numerical simulations used to interpret laser-driven plasma experiments at the GSI Helmholtz Centre for Heavy Ion Research. The mechanisms by which non-thermal particles are accelerated, in astrophysical environments e.g., the solar wind, supernova remnants, and gamma ray bursts, is a topic of intense study. When shocks are present the primary acceleration mechanism is believed to be first-order Fermi, which accelerates particles as they cross a shock. Second-order Fermi acceleration can also contribute, utilizing magnetic mirrors for particle energization. Despite this mechanism being less efficient, the ubiquity of magnetized turbulence in the universe necessitates its consideration. Another acceleration mechanism is the lower-hybrid drift instability, arising from gradients of both density and magnetic field, which produce lower-hybrid waves with an electric field which energizes particles as they cross these waves. With the combination of high-powered laser systems and particle accelerators it is possible to study the mechanisms behind cosmic-ray acceleration in the laboratory. In this work, we combine experimental results and high-fidelity threedimensional simulations to estimate the efficiency of ion acceleration in a weakly magnetized interaction region. We validate the FLASH MHD code with experimental results and use OSIRIS particle-in-cell (PIC) code to verify the initial formation of the interaction region, showing good agreement between codes and experimental results. We find that the plasma conditions in the experiment are conducive to the lower-hybrid drift instability, yielding an increase in energy ∆E of ∼ 264 keV for 242 MeV calcium ions.Laboratory realization of relativistic pair-plasma beams
Nature Communications Springer Nature 15:1 (2024) 5029