Topological Effects in Neural Network Field Theory
Abstract
Neural network field theory formulates field theory as a statistical ensemble of fields defined by a network architecture and a density on its parameters. We extend the construction to topological settings via the inclusion of discrete parameters that label the topological quantum number. We recover the Berezinskii--Kosterlitz--Thouless transition, including the spin-wave critical line and the proliferation of vortices at high temperatures. We also verify the T-duality of the bosonic string, showing invariance under the exchange of momentum and winding on , the transformation of the sigma model couplings according to the Buscher rules on constant toroidal backgrounds, the enhancement of the current algebra at self-dual radius, and non-geometric T-fold transition functions.
Cite
@article{arxiv.2604.02313,
title = {Topological Effects in Neural Network Field Theory},
author = {Christian Ferko and James Halverson and Vishnu Jejjala and Brandon Robinson},
journal= {arXiv preprint arXiv:2604.02313},
year = {2026}
}
Comments
55 pages, 8 figures