Observing how deep neural networks understand physics through the energy spectrum of one-dimensional quantum mechanics. (arXiv:2201.06676v2 [physics.comp-ph] UPDATED)

We investigate how neural networks (NNs) understand physics using 1D quantum
mechanics. After training an NN to accurately predict energy eigenvalues from
potentials, we used it to confirm the NN's understanding of physics from four
different aspects. The trained NN could predict energy eigenvalues of different
kinds of potentials than the ones learned, predict the probability distribution
of the existence of particles not used during training, reproduce untrained
physical phenomena, and predict the energy eigenvalues of potentials with an
unknown …

arxiv energy networks neural networks physics quantum quantum mechanics