Mikael de Alcantara Santos

Learning quantum eigenspaces under geometric symmetry breaking with Rayleigh-Ritz physics-informed neural networks

We develop a Rayleigh–Ritz physics-informed neural formulation for quantum eigenproblems on geometry-parametrized domains, in which the neural representation and its validation diagnostic track the spectral object selected by the physics rather than the eigenvalue index alone. Tested on the one-dimensional well, the...