8 papers
Neural Network Field Theory at Finite Width
Christian Ferko, Aaron Mutchler
Under mild assumptions, any quantum mechanical (QM) model or quantum field theory (QFT) admits a representation in terms of an ensemble of neural networks with countably many rando…
A Tale of Two Compact Bosons
Christian Ferko, Vishnu Jejjala, Brandon Robinson
Neural network field theory (NN-FT) defines a field theory by a network architecture together with a probability density on its latent variables. For compact theories the local Gau…
Anomalies in Neural Network Field Theory
Christian Ferko, Samuel Frank, James Halverson +1
Neural network field theory (NN-FT) formulates field theory in terms of a network architecture and a density on its parameters. We derive Schwinger--Dyson equations and Ward identi…
Topological Effects in Neural Network Field Theory
Christian Ferko, James Halverson, Vishnu Jejjala +1
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 constructio…
Universality of Neural Network Field Theory
Christian Ferko, James Halverson, Aaron Mutchler
We prove that any quantum field theory, or more generally any probability distribution over tempered distributions in , admits a neural network description with a cou…
Machine Learning Invariants of Tensors
Athithan Elamaran, Christian Ferko, Sterling Scarlett
We propose a data-driven approach to identifying the functionally independent invariants that can be constructed from a tensor with a given symmetry structure. Our algorithm procee…