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From the 1 of 7 linked papers with an AI index.

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7 papers

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…

quant-ph2026

Universality of Quantum Gates in Particle and Symmetry Constrained Subspaces

Andreas Stergiou, Nicolas PD Sawaya

Simulating physical systems on near-term quantum computers often requires preparing states within constrained subspaces, like those with fixed particle number or spin. We use Lie a…

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…