mlsanityData to 14 Oct 2026

Spectral functions in Minkowski quantum electrodynamics from neural reconstruction

arXiv 2510.24728 ↗First posted 6 Oct 2025hep-ph cs.LG hep-latcited by 1

Not on the map. Why?

Abstract (arXiv)

We study neural reconstructions of quenched rainbow quantum electrodynamics (QED) Dyson--Schwinger benchmarks in Minkowski-related kinematics. Using the dispersive formulation as motivation, we separate the Euclidean Fukuda--Kugo equation, the spectral unitary equations, and the modified unitary equations. The Fukuda--Kugo benchmark is solved directly and shows the expected zero crossing above the critical region αc=π/3. Neural reconstructions with free output reproduce this behavior, while positivity-constrained ans"atze fail in the supercritical regime. Thus, spectral positivity should be treated as a diagnostic of the Lehmann representation, not imposed blindly as a neural constraint.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 60 references that are in the map. First posted on arXiv 6 Oct 2025.

Builds on

8 of 60 references.

References · 8

  1. 2019DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operatorscited by 2,018
  2. 2020B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Datacited by 335
  3. 2017Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanicscited by 214
  4. 2019Ab-Initio Solution of the Many-Electron Schr"odinger Equation with Deep Neural Networkscited by 200
  5. 2019Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networkscited by 76
  6. 2025Gauge-covariant stochastic neural fields: Stability and finite-width effectscited by 3
  7. 2024A Tutorial on the Use of Physics-Informed Neural Networks to Compute the Spectrum of Quantum Systemscited by 2
  8. 2024Physics-informed neural networks viewpoint for solving the Dyson-Schwinger equations of quantum electrodynamicscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Neural solutions of coupled ghost and gluon Dyson--Schwinger equations in Landau gaugecited by 0