Electrostatic field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
Authors/Creators
Description
This repository contains the "Electrostatic field" dataset from the paper
Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
Miltiadis Kofinas, Erik J Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
NeurIPS 2023
https://arxiv.org/abs/2310.20679
https://github.com/mkofinas/aether
It contains simulations of trajectories of 5 charged particles in 2 dimensions, interacting via Coulomb forces.
Particles move under the influence of 20 immovable and unknown sources, which are shared in the whole dataset.
There are 50,000 simulations for training, 10,000 for validation, and 10,000 for testing. Simulations last for 49 timesteps.
The features comprise positions and velocities of particles, while edges describe the product of pairwise charges. The dataset also contains the positions of the field sources, meant to be used for visualization.
Files
static_electrostatic_field.zip
Files
(258.0 MB)
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Additional details
References
- Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. Kofinas, Miltiadis and Bekkers, Erik J, and Nagaraja, Naveen Shankar and Gavves, Efstratios. In: Advances in Neural Information Processing Systems 36 (NeurIPS), 2023.