arXiv:2604.01279v1 Announce Type: new
Abstract: We introduce Sven (Singular Value dEsceNt), a new optimization algorithm for neural networks that exploits the natural decomposition of loss functions into a sum over individual data points, rather than …
arXiv:2604.02313v1 Announce Type: cross
Abstract: Neural network field theory formulates field theory as a statistical ensemble of fields defined by a network architecture and a density on its parameters. We extend the construction to topological sett…
arXiv:2604.01275v1 Announce Type: cross
Abstract: In this paper, we attempt to explore the landscape of two-dimensional conformal field theories (2d CFTs) by efficiently searching for numerical solutions to the modular bootstrap equation using machine…
arXiv:2512.24420v3 Announce Type: replace-cross
Abstract: Neural Network Field Theories (NN-FTs) typically describe Generalized Free Fields that lack a local stress-energy tensor in two dimensions, obstructing the realization of Virasoro symmetry. We …
arXiv:2509.19162v2 Announce Type: replace-cross
Abstract: This is the third paper of the CayleyPy project applying artificial intelligence to problems in group theory. We announce the first public release of CayleyPy, an open source Python library for…
arXiv:2603.29932v1 Announce Type: cross
Abstract: We explore the capability of a Large Language Model (LLM) to perform specific computations in mathematical physics: the task is to compute the coordinate Bethe Ansatz solution of selected integrable sp…
arXiv:2509.25311v2 Announce Type: replace-cross
Abstract: We implement physics-informed-neural-networks (PINNs) to compute holographic entanglement entropy and entanglement wedge cross section. This technique allows us to compute these quantities for …