Related papers: Neural Wavefunctions in Quantum Field Theory I: Asymptotic Freedom

Neural Wavefunctions in Quantum Field Theory I: Asymptotic Freedom

URL: http://arxiv.org/abs/2606.20791v1
Date: Thu, 18 Jun 2026 18:00:01 GMT
Title: Neural Wavefunctions in Quantum Field Theory I: Asymptotic Freedom
Abstract summary: We present a variational approach to quantum field theory based on wavefunctions parameterized by neural networks.<n>We show that neural-network wavefunctions, combined with machine-learning techniques, enable competitive variational calculations in nontrivial field theories.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: We present a variational approach to quantum field theory based on wavefunctions parameterized by neural networks. While variational methods have a celebrated history across many fields, their application to quantum field theory has been limited by well-known challenges. We show that neural-network wavefunctions, combined with modern machine-learning techniques, enable competitive variational calculations in nontrivial field theories. As a demonstration, we reproduce the essential features of the two-dimensional nonlinear $σ$-model: asymptotic freedom, dynamical mass generation and the model's step-scaling function.

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