Machine-Learning the Classification of Spacetimes
General Relativity and Quantum Cosmology
2022-06-09 v2 Machine Learning
High Energy Physics - Theory
Abstract
On the long-established classification problems in general relativity we take a novel perspective by adopting fruitful techniques from machine learning and modern data-science. In particular, we model Petrov's classification of spacetimes, and show that a feed-forward neural network can achieve high degree of success. We also show how data visualization techniques with dimensionality reduction can help analyze the underlying patterns in the structure of the different types of spacetimes.
Cite
@article{arxiv.2201.01644,
title = {Machine-Learning the Classification of Spacetimes},
author = {Yang-Hui He and Juan Manuel Pérez Ipiña},
journal= {arXiv preprint arXiv:2201.01644},
year = {2022}
}
Comments
6 pages, 5 figures; v2: minor corrections, published version