Aug 8 – 13, 2022
Hörsaalzentrum Poppelsdorf
Europe/Berlin timezone

Stochastic and Tensor Network simulations of the Hubbard Model

Aug 13, 2022, 9:50 AM
CP1-HSZ/0.010 (CP1-HSZ) - HS2 (CP1-HSZ)

CP1-HSZ/0.010 (CP1-HSZ) - HS2


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Plenary Algorithms (including Machine Learning, Quantum Computing, Tensor Networks) Plenaries


Mr Johann Ostmeyer (University of Liverpool)


The Hubbard model is an important tool to understand the electrical properties of various materials. More specifically, on the honeycomb lattice it is used to describe graphene predicting a quantum phase transition from a semimetal to a Mott insulating state. In this talk I am going to explain two different numerical techniques we employed for simulations of the Hubbard model: The Hybrid Monte Carlo algorithm on the one hand allowed us to simulate unprecedentedly large lattices, whereas Tensor Networks can be used to completely avoid the sign problem. Respective strengths and weaknesses of the methods will be discussed.

Primary author

Mr Johann Ostmeyer (University of Liverpool)

Presentation materials