Speaker
Vasileios Niarchos
Description
How much information is needed to reconstruct a correlation function in conformal field theory? Surprisingly, very little. I will introduce a novel approach based on neural networks that produces a remarkably accurate approximation of scalar correlation functions in arbitrary CFTs in any spacetime dimension from a few input data. I will present a wide variety of examples and discuss the underlying mechanisms behind the approach highlighting potential future applications