Author

W. Smith

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Preprint Aug 2026

Neuro-dispersive extractions of light-meson resonances

We present the first dispersive extraction of resonant poles from analytically continued neural networks. We use S-matrix informed neural networks (SINNs) trained to respect unitarity, analyticity, and crossing symmetry, without fixing a specific amplitude parametrization. The SINN framework controls representation dep...

W. Smith, A. Rodas, Marius D. Thomas et al. · 0 citations

Preprint Aug 2026

S-matrix informed neural networks for amplitude analysis

This work introduces S-matrix informed neural networks (SINNs), and demonstrates their ability to learn scattering amplitudes directly from data while respecting first principles, and develops a novel data selection procedure which uses the response of constrained neural network ensembles to identify a set of experimen...

W. Smith, A. Rodas, Marius D. Thomas et al. · 0 citations