Discovery of superconductivity from first principles with neural network variational Monte Carlo

Recent advances on neural quantum states have shown that correlations between quantum particles can be efficiently captured by attention — a neural network element that describes relations between objects. Integrating this ansatz with a variational Monte Carlo technique, we demonstrate the discovery of a superconductivity in a repulsive Fermi system only by energy minimization and without prior knowledge on the result.