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A First-Principles Model Based on Saturation of the Electron Cyclotron Drift Instability for Electron Transport in Hydrodynamics Simulations of Hall Thruster Plasmas

We present a computational model based on the hypothesis that the higher-than-expected electron mobility across magnetic field lines observed in Hall thrusters is due to the growth and eventual saturation of the electron cyclotron drift instability. The key improvement of this model with respect to previous work is that it decouples the saturation of the instability from the correlation that exists between mobility and magnitude of the wave perturbations in linear theory, thereby enabling first-principles simulations. The model has been incorporated in the 2-D (r-z) multi-fluids code Hall2De and simulations of the H6 thruster at 300 V, 20 A are numerically stable and achieve a steady-state solution at a computational cost that is not significantly higher than previous Hall2De simulations. The computed location of the acceleration region is found to be within 10% of the length of the acceleration channel compared to that inferred by experiments. The simulations also capture well the plasma gradients along the channel centerline of this thruster. To further establish the validity of this model, we plan to conduct simulations of other thrusters and/or operating conditions.

Lopez Ortega, Alejandro

Towards Surrogate Modeling of Subgrid Turbulent Transport for 3D Radiative Hydrodynamic Simulations of the Quiet Sun

In this work, we investigate the use of deep learn-ing techniques as surrogate models, to enhance the estimationof effects of subgrid turbulent transport for 3D radiatuve hy-drodynamic simulations of the quiet Sun. We develop two dis-tinct 3D Convolutional Neural Networks (3DCNNs) to capturespatio-temporal dependencies in 3D velocity fields, leveragingdifferent activation functions and architectural designs. Thesemodels integrate both averaged velocity vector components andscalar features such as plasma density to enhance predictionaccuracy. Additionally, a Multilayer Perceptron (MLP) modelis employed to approximate complex nonlinear relationships,offering a comparison in performance between convolutionaland fully connected architectures. Logarithmic transformationis applied to the targets to handle heavily skewed data, im-proving model performance. All models are compared againsta physics-based Gradient Model. Results show that the 3DCNNmodels excel at approximating Reynolds stress tensors, makingthem a candidate for assisting in producing reduced resolutionsimulations, and thereby reducing computational overheadwhile maintaining higher accuracy than the baseline. Thesefindings demonstrate the potential of deep learning, particu-larly CNNs, to advance scalable and accurate simulations ofsolar dynamics, offering a promising alternative to traditionalturbulence models.

Heliophysics

Surrogate Modeling of Subgrid Turbulent Transport Based on 3D Radiative Hydrodynamic Simulations of the Quiet Sun

Turbulent Transport: Plays a critical role in astrophysical plasmas, such as the solar interior, spanning multiple scales and challenging traditional modeling approaches. Objective: Develop machine learning (ML) models—MLP and CNN—to predict subgrid Reynolds stress tensors from StellarBox 3D simulations of the solar atmosphere. Benchmarking: Compare ML-driven models against physics-based Gradient and Smagorinsky approaches.

SMD

The Role of a Neutron Component in the Photospheric Emission of Long Duration Gamma-Ray Burst Jets

Long-duration gamma-ray bursts (LGRBs), thought to be produced during core-collapse supernovæ, may have a prominent neutron component in the outflow material. If present, neutrons can change how photons scatter in the outflow by reducing its opacity, thereby allowing the photons to decouple sooner than if there were no neutrons present. Understanding the details of this process could therefore allow us to probe the central engine of LGRBs, which is otherwise hidden. Here, we present results of the photospheric emission from an LGRB jet, using a combination of relativistic hydrodynamic simulations and radiative transfer post-processing using the Monte Carlo Radiation Transfer (MCRaT) code. We control the size of the neutron component in the jet material by varying the equilibrium electron fraction Y e , and we find that the presence of neutrons in the GRB fireball affects the Band parameters α and E 0 , while the picture with the β parameter is less clear. In particular, the break energy E 0 is shifted to higher energies. Additionally, we find that increasing the size of the neutron component also increases the total radiated energy of the outflow across multiple viewing angles. Our results not only shed light on LGRBs, but are also relevant to short-duration gamma-ray bursts associated with binary neutron star mergers, due to the likelihood of a prominent neutron component in such systems.

Gamma-ray bursts

Numerical simulations of fission

Hydrodynamic simulation techniques to the fission problem of the lunar origin were applied. It is indicated that, for fluids with the compressibility of stars, dynamic fission instabilities lead to spiral arm ejection of mass and angular momentum in the form of a ring or disk of debris, not as a single body. Some quantitative aspects of these results seem favorable to lunar origin by fission. Fission instabilities in fluid objects with a smaller degree of compressibility, more closely approximating terrestrial material are considered. Although the qualitative features are similar, there are significant quantitative differences for the stiffer equation of state. The implications of the results for the fission hypothesis of lunar origin are discussed. Evolutions illustrating possible approaches to instability are presented.

Durisen, R. H.