Jun 12–16, 2023
Perimeter Institute for Theoretical Physics
America/Toronto timezone

Investigating Topological Order with Recurrent Neural Network Wave Functions

Jun 14, 2023, 2:30 p.m.
30m
PI/1-100 - Theatre (Perimeter Institute for Theoretical Physics)

PI/1-100 - Theatre

Perimeter Institute for Theoretical Physics

190

Speaker

Mohamed Hibat Allah (Vector Institute)

Description

Recurrent neural networks (RNNs), originally developed for natural language processing, hold great promise for accurately describing strongly correlated quantum many-body systems. In this talk, we will illustrate how to use 2D RNNs to investigate two prototypical quantum many-body Hamiltonians exhibiting topological order. Specifically, we will demonstrate that RNN wave functions can effectively capture the topological order of the toric code and a Bose-Hubbard spin liquid on the kagome lattice by estimating their topological entanglement entropies. Overall, we will show that RNN wave functions constitute a powerful tool for studying phases of matter beyond Landau's symmetry-breaking paradigm.

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