Kavli Affiliate: Eliska Greplova | Summary:Neural quantum states (NQS) provide a flexible and scalable framework for approximating quantum many-body wavefunctions. Among NQS parameterizations, autoregressive models are especially attractive because they enable exact, independent sampling from the Born distribution, avoiding the autocorrelation and mixing issues of Markov chain methods. Yet their optimization remains comparatively underexplored: Adam […]
Continue.. One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective