208 citations · 2.4k across the 75 of their papers we have counts for
76 papers
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…
Thermal Double-Twist Data in Holography
V. Niarchos, C. Papageorgakis, A. Stratoudakis
We explain how to extract thermal OPE coefficients of double-twist operators in scalar two-point functions at infinite spatial volume from suitably regularized integrals of thermal…
Neural Networks, Dispersion Relations and the Thermal Bootstrap
Vasilis Niarchos, Constantinos Papageorgakis
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 throug…
Neural Operators as Efficient Function Interpolators
Vasilis Niarchos, Angelos Sirbu, Sokratis Trifinopoulos
Neural operators (NOs) are designed to learn maps between infinite-dimensional function spaces. We propose a novel reframing of their use. By introducing an auxiliary base-space, a…
When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning
Vasilis Niarchos, Constantinos Papageorgakis, Alexander G. Stapleton +1
As large language models (LLMs) show increasing promise on research-level physics reasoning tasks and agentic AI becomes more common, a practical question emerges: How does the int…
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…