Version 0.1.0

Dynamic gravitational field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields

View Dataset
Kofinas, Miltiadis;Bekkers, Erik Johannes;Nagaraja, Naveen Shankar;Gavves, Efstratios

Description

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.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.3

FAIR Score

79%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Computational Mechanics

Field

Engineering

Domain

Physical Sciences

Confidence Score

53%

Source

Scholar Data Model

Keywords

Trajectory forecastingGraph neural networksEquivarianceNeural fieldsInteracting dynamical systemsPhysics simulations

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00