Neural Network Learning and Quantum Gravity

arXiv:2403.03245v1 Announce Type: cross
Abstract: The landscape of low-energy effective field theories stemming from string theory is too vast for a systematic exploration. However, the meadows of the string landscape may be fertile ground for the application of machine learning techniques. Employing neural network learning may allow for inferring novel, undiscovered properties that consistent theories in the landscape should possess, or checking conjectural statements about alleged characteristics thereof. The aim of this work is to describe to what extent the …

abstract application arxiv consistent cs.lg energy exploration gravity hep-th however landscape low low-energy machine machine learning machine learning techniques network neural network novel quantum stemming string theory type vast