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PIRSA:23060039

Investigating Topological Order with Recurrent Neural Network Wave Functions

APA

Hibat Allah, M. (2023). Investigating Topological Order with Recurrent Neural Network Wave Functions. Perimeter Institute for Theoretical Physics. https://pirsa.org/23060039

Mohamed Hibat Allah University of Waterloo

Talk numberPIRSA:23060039
Talk Type Conference

Abstract

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.