Conformal Defects in Neural Network Field Theories

Fuente: arXiv
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Hauptverfasser: Capuozzo, Pietro, Robinson, Brandon, Suzzoni, Benjamin
Format: Preprint
Veröffentlicht: 2025
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author Capuozzo, Pietro
Robinson, Brandon
Suzzoni, Benjamin
author_facet Capuozzo, Pietro
Robinson, Brandon
Suzzoni, Benjamin
contents Neural Network Field Theories (NN-FTs) represent a novel construction of arbitrary field theories, including those of conformal fields, through the specification of the network architecture and prior distribution for the network parameters. In this work, we present a formalism for the construction of conformally invariant defects in these NN-FTs. We demonstrate this new formalism in two toy models of NN scalar field theories. We develop an NN interpretation of an expansion akin to the defect OPE in two-point correlation functions in these models.
format Preprint
id arxiv_https___arxiv_org_abs_2512_07946
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Conformal Defects in Neural Network Field Theories
Capuozzo, Pietro
Robinson, Brandon
Suzzoni, Benjamin
High Energy Physics - Theory
Machine Learning
Neural Network Field Theories (NN-FTs) represent a novel construction of arbitrary field theories, including those of conformal fields, through the specification of the network architecture and prior distribution for the network parameters. In this work, we present a formalism for the construction of conformally invariant defects in these NN-FTs. We demonstrate this new formalism in two toy models of NN scalar field theories. We develop an NN interpretation of an expansion akin to the defect OPE in two-point correlation functions in these models.
title Conformal Defects in Neural Network Field Theories
topic High Energy Physics - Theory
Machine Learning
url https://arxiv.org/abs/2512.07946