Large Electron Model: A Universal Ground State Predictor
This provides a foundation model for material discovery that handles strong electron correlation better than density functional theory.
The researchers tackled the problem of predicting ground state wavefunctions for interacting electrons across different Hamiltonian parameters and particle numbers by introducing the Large Electron Model, which achieved accurate predictions for up to 50 particles in a 2D harmonic potential.
We introduce Large Electron Model, a single neural network model that produces variational wavefunctions of interacting electrons over the entire Hamiltonian parameter manifold. Our model employs the Fermi Sets architecture, a universal representation of many-body fermionic wavefunctions, which is further conditioned on Hamiltonian parameter and particle number. On interacting electrons in a two-dimensional harmonic potential, a single trained model accurately predicts the ground state wavefunction while generalizing across unseen coupling strengths and particle-number sectors, producing both accurate real-space charge densities and ground state energies, even up to $50$ particles. Our results establish a foundation model method for material discovery that is grounded in the variational principle, while accurately treating strong electron correlation beyond the capacity of density functional theory.