Neutral atoms trapped in optical tweezers and excited to Rydberg states, together with trapped ions, are among the most advanced platforms for quantum simulation and quantum computing. Current experiments often rely on additional atoms in neighboring traps to encode ancilla qubits for local manipulation and readout. He...
Fabian Thielemann, Aaron Götzelmann, Marius D. Thomas et al.· 0 citations
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
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
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