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arXiv · 2406.02451

Quantum states from normalizing flows

Scott Lawrence·Arlee Shelby·Yukari Yamauchi
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Abstract

We introduce an architecture for neural quantum states for many-body quantum-mechanical systems, based on normalizing flows. The use of normalizing flows enables efficient uncorrelated sampling of configurations from the probability distribution defined by the wavefunction, mitigating a major cost of using neural states in simulation. We demonstrate the use of this architecture for both ground-state preparation (for self-interacting particles in a harmonic trap) and real-time evolution (for one-dimensional tunneling). Finally, we detail a procedure for obtaining rigorous estimates of the systematic error when using neural states to approximate quantum evolution.

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Scott Lawrence, Arlee Shelby, Yukari Yamauchi. 2024-06-04. Quantum states from normalizing flows. https://arxiv.org/abs/2406.02451

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