7937 20260211173550.0 10.1063/5.0300009 DOI SCART-2026-0099 Miloshevich, George Electron neural closure for turbulent magnetosheath simulations: Energy channels 2026 In this work, we introduce a non-local five-moment electron pressure tensor closure parametrized by a fully convolutional neural network (FCNN). Electron pressure plays an important role in generalized Ohm's law, competing with electron inertia. This model is used in the development of a surrogate model for a fully kinetic energy-conserving semi-implicit particle-in-cell simulation of decaying magnetosheath turbulence. We achieve this by training FCNN on a representative set of simulations with a smaller number of particles per cell and showing that our results generalize to a simulation with a large number of particles per cell. We evaluate the statistical properties of the learned equation of state, with a focus on pressure-strain interaction, which is crucial for understanding energy channels in turbulent plasmas. The resulting equation of state learned via FCNN significantly outperforms local closures, such as those learned by multi-layer perceptron (MLP) or double adiabatic expressions. We report that the overall spatial distribution of pressure-strain and its conditional averages are reconstructed well. However, some small-scale features are missed, especially for the off-diagonal components of the pressure tensor. Nevertheless, the results are substantially improved with more training data, indicating favorable scaling and potential for improvement, which will be addressed in future work. NO Vranckx, Luka de Oliveira Lopes, Felipe Nathan Dazzi, Pietro Arrò, Giuseppe Lapenta, Giovanni Physics of Plasmas 33 2026 1 luka.vranckx@ksb-orb.be https://pubs.aip.org/aip/pop/article/33/1/012901/3377334/Electron-neural-closure-for-turbulent 11346045 http://publi2-as.oma.be/record/7937/files/Miloshevich et al. 2026 - Electron neural closure for turbulent magnetosheath simulations Energy channels.pdf 11397 http://publi2-as.oma.be/record/7937/files/Miloshevich et al. 2026 - Electron neural closure for turbulent magnetosheath simulations Energy channels.gif?subformat=icon icon 12848 http://publi2-as.oma.be/record/7937/files/Miloshevich et al. 2026 - Electron neural closure for turbulent magnetosheath simulations Energy channels.jpg?subformat=icon-180 icon-180 published in REFERD