Dynamic gravitational field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields
View DatasetDescription
This repository contains the "Dynamic gravitational field" dataset from the paperLatent Field Discovery in Interacting Dynamical Systems with Neural FieldsMiltiadis Kofinas, Erik J Bekkers, Naveen Shankar Nagaraja, Efstratios GavvesNeurIPS 2023https://arxiv.org/abs/2310.20679https://github.com/mkofinas/aetherIt contains simulations of trajectories of 5 charged particles in 3 dimensions, interacting via gravitational forces.Particles move under the influence of 1 immovable and unknown source, which is different in each simulation. The source has a mass of 10, while each particle has a mass of 1.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. The dataset also contains the positions of the field sources, meant to be used for visualization.
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Publication Details
Subfield
Computational Mechanics
Field
Engineering
Domain
Physical Sciences
Confidence Score
53%
Source
Scholar Data Model