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hep-th2026

Neural Spectral Bias and Conformal Correlators II: Modular and Annulus Bootstrap

Kausik Ghosh, Sidhaarth Kumar, Vasilis Niarchos +1

We develop a neural network bootstrap framework for reconstructing partition functions of two-dimensional conformal field theories (CFTs) based on modular invariance and the Cardy…

hep-th2026

Neural Networks Reveal a Universal Bias in Conformal Correlators

Kausik Ghosh, Sidhaarth Kumar, Vasilis Niarchos +1

The paper shows that simple neural networks trained on crossing symmetry can accurately reconstruct conformal correlators from minimal input, suggesting a universal bias that can b…

hep-th2026

Redundancy Channels in the Conformal Bootstrap

Stefanos R. Kousvos, Andreas Stergiou

A method for obstructing symmetry enhancement in numerical conformal bootstrap calculations is proposed. Symmetry enhancement refers to situations where bootstrap studies initialis…

hep-th2026

Neural Spectral Bias and Conformal Correlators I: Introduction and Applications

Kausik Ghosh, Sidhaarth Kumar, Vasilis Niarchos +1

We demonstrate that simple feed-forward neural networks (NNs) can accurately compute correlation functions of conformal field theories (CFTs) on a line. Strikingly, by optimising a…

hep-th2025

Transdimensional Defects

Elia de Sabbata, Nadav Drukker, Andreas Stergiou

This note introduces a novel paradigm for conformal defects with continuously adjustable dimensions. Just as the standard expansion interpolates between integer space…

hep-th2025

Fine Spectrum from Crude Analytic Bootstrap

Jake Belton, Nadav Drukker, Ziwen Kong +1

The magnetic line defect in the model gives rise to a non-trivial one-dimensional defect conformal field theory of theoretical and experimental value. This model is consider…