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Keyword: quantum lattice models ×Clear all

2 claims from 1 paper

1. Physics and Astronomy › Quantum many-body systems

   Gauge-invariant and anyonic-symmetric autoregressive neural network for quantum lattice models

   Di Luo, Chen, Hu, Zhao, Hur and Clark · Physical Review Research · 2023

   The paper builds autoregressive neural network quantum states that obey gauge or anyonic symmetries, proves exact representations for some models, and uses them to simulate several lattice models.

   Unchecked2 claims
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   1. UncheckedThe authors prove their symmetry-respecting neural networks can exactly represent the ground and excited states of the 2D and 3D toric codes and the X-cube model.“We prove that our methods can provide exact representation for the ground and excited states of the 2D and 3D toric codes, and the X-cube fracton model.”
   2. UncheckedThe authors say their autoregressive neural networks for quantum lattice models can be sampled efficiently and build in gauge symmetries or anyonic constraints exactly.“These networks can be efficiently sampled and explicitly obey gauge symmetries or anyonic constraint.”