# Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations

@article{Cheng2021UsingNN, title={Using neural networks to solve the 2D Poisson equation for electric field computation in plasma fluid simulations}, author={Li Mei Cheng and Ekhi Ajuria Illarramendi and Guillaume Bogopolsky and Micha{\"e}l Bauerheim and B{\'e}n{\'e}dicte Cuenot}, journal={ArXiv}, year={2021}, volume={abs/2109.13076} }

The Poisson equation is critical to get a self-consistent solution in plasma fluid simulations used for Hall effect thrusters and streamers discharges. Solving the 2D Poisson equation with zero Dirichlet boundary conditions using a deep neural network is investigated using multiple-scale architectures, defined in terms of number of branches, depth and receptive field 1. The latter is found critical to correctly capture large topological structures of the field. The investigation of multipleβ¦Β

## 9 Citations

### PlasmaNet: a framework to study and solve elliptic differential equations using neural networks in plasma fluid simulations

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### Calculation of Photoionization Rates During Streamer Discharge Using Neural Networks

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- Computer SciencePlasma Sources Science and Technology
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A tutorial overview of some of the widely-used ML methods that can be useful, amongst others, for discovering and correlating patterns in the data that may be otherwise impractical to decipher by human intuition alone.

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