Conformal Defects in Neural Network Field Theories
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866909044251295744 |
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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 |