Spin-symmetry-enforced deep learning quantum Monte Carlo

Optimizations in deep learning quantum Monte Carlo methods are not guaranteed to produce quantum states with the desired spin symmetry. This work introduces a low-scaling penalty term that enforces spin symmetry with minimal computational overhead, achieving higher accuracy and efficiency for excited-state calculations.

• Z. Li et al. Nat Comput Sci 4, 910 (2024)