A tale of two compact bosons

Neural network field theory (NN-FT) defines a field theory by a network architecture together with a probability density on its latent variables. For compact theories the local Gaussian sector is only part of the story: one must also sum over discrete topological sectors. We review a mixed continuous/discrete latent-variable construction and apply it to two compact bosons. For the Berezinskii–Kosterlitz–Thouless transition, a random Fourier feature spin-wave sampler supplemented by an explicit Coulomb gas vortex sector reproduces the Gaussian critical line below [Formula: see text], vortex proliferation above [Formula: see text], the essential singularity of the correlation length, and the Nelson–Kosterlitz jump. For the bosonic string, oscillator modes augmented by momentum–winding labels reproduce circle T-duality, Buscher transformations on constant toroidal backgrounds, self-dual current algebra enhancement, and a toy T-fold. The common lesson is that the same local neural sampler, paired with different discrete topological data, yields physically distinct compact theories. These proceedings are based on [1].

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Publication Details

Journal
AI in Mathematics and Theoretical Physics
Published
2026-09-11
DOI
https://doi.org/10.1142/s3082883x26400059
Primary Topic
Quantum many-body systems
Type
article
Field-Weighted Citation Impact
0.00

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article

A tale of two compact bosons

Brandon Robinson, Christian Ferko, Vishnu Jejjala
AI in Mathematics and Theoretical Physics
Quantum many-body systems
article

A tale of two compact bosons

Brandon Robinson, Christian Ferko, Vishnu Jejjala
article en

Abstract

Neural network field theory (NN-FT) defines a field theory by a network architecture together with a probability density on its latent variables. For compact theories the local Gaussian sector is only part of the story: one must also sum over discrete topological sectors. We review a mixed continuous/discrete latent-variable construction and apply it to two compact bosons. For the Berezinskii–Kosterlitz–Thouless transition, a random Fourier feature spin-wave sampler supplemented by an explicit Coulomb gas vortex sector reproduces the Gaussian critical line below [Formula: see text], vortex proliferation above [Formula: see text], the essential singularity of the correlation length, and the Nelson–Kosterlitz jump. For the bosonic string, oscillator modes augmented by momentum–winding labels reproduce circle T-duality, Buscher transformations on constant toroidal backgrounds, self-dual current algebra enhancement, and a toy T-fold. The common lesson is that the same local neural sampler, paired with different discrete topological data, yields physically distinct compact theories. These proceedings are based on [1].

AI in Mathematics and Theoretical Physics
National Institute for Theoretical Physics (ZA), The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (US), University of Amsterdam (NL)
National Science Foundation, National Research Foundation, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Banff International Research Station for Mathematical Innovation and Discovery
Sustainable cities and communities
Openalex Percentile: Top 25%
Quantum many-body systems
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