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Hauptverfasser: Niarchos, Vasilis, Papageorgakis, Constantinos
Format: Preprint
Veröffentlicht: 2026
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Online-Zugang:https://arxiv.org/abs/2605.13183
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author Niarchos, Vasilis
Papageorgakis, Constantinos
author_facet Niarchos, Vasilis
Papageorgakis, Constantinos
contents We review a framework for the conformal bootstrap that does not rely on positivity and treats the infinite tower of high-dimension OPE contributions to conformal correlators through dispersion relations and neural networks. We apply it to scalar thermal two-point functions on $S^1\times \mathbb R^{d-1}$. We discuss the stability properties of the relevant non-convex optimisation scheme and potential relations to recent discussions of smoothness properties in CFT correlators. We illustrate the numerical application of the method to Generalized Free Fields and 4d holographic CFTs. This is a proceedings contribution to the ``Athens Workshop in Theoretical Physics: 10th Anniversary", held at the National and Kapodistrian University of Athens on December 17-19 2025.
format Preprint
id arxiv_https___arxiv_org_abs_2605_13183
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Neural Networks, Dispersion Relations and the Thermal Bootstrap
Niarchos, Vasilis
Papageorgakis, Constantinos
High Energy Physics - Theory
We review a framework for the conformal bootstrap that does not rely on positivity and treats the infinite tower of high-dimension OPE contributions to conformal correlators through dispersion relations and neural networks. We apply it to scalar thermal two-point functions on $S^1\times \mathbb R^{d-1}$. We discuss the stability properties of the relevant non-convex optimisation scheme and potential relations to recent discussions of smoothness properties in CFT correlators. We illustrate the numerical application of the method to Generalized Free Fields and 4d holographic CFTs. This is a proceedings contribution to the ``Athens Workshop in Theoretical Physics: 10th Anniversary", held at the National and Kapodistrian University of Athens on December 17-19 2025.
title Neural Networks, Dispersion Relations and the Thermal Bootstrap
topic High Energy Physics - Theory
url https://arxiv.org/abs/2605.13183