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2023

Autoregressive Neural Quantum States with Quantum Number Symmetries

Malyshev, Aleksei, Arrazola, Juan Miguel, Lvovsky, A. I.

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Neural quantum states have established themselves as a powerful and versatile family of ansatzes for variational Monte Carlo simulations of quantum many-body systems.

Of particular prominence are autoregressive neural quantum states (ANQS), which enjoy the expressibility of deep neural networks, and are equipped with a procedure for fast and unbiased sampling.
Yet, the non-selective nature of autoregressive sampling makes incorporating quantum number symmetries challenging.
In this work, we develop a general framework to make the autoregressive sampling compliant with an arbitrary number of quantum number symmetries.

Autoregressive Neural Quantum States with Quantum Number Symmetries · Around

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