Litcius/Paper detail

Simulating both parity sectors of the Hubbard model with tensor networks

Manuel Schneider, Johann Ostmeyer, Karl Jansen, Thomas Luu, Carsten Urbach

2021Physical review. B./Physical review. B17 citationsDOIOpen Access PDF

Abstract

Tensor networks are a powerful tool to simulate a variety of different physical models, including those that suffer from the sign problem in Monte Carlo simulations. The Hubbard model on the honeycomb lattice with nonzero chemical potential is one such problem. Our method is based on projected entangled pair states using imaginary-time evolution. We demonstrate that it provides accurate estimators for the ground state of the model, including cases where Monte Carlo simulations fail miserably. In particular, it shows near to optimal, that is linear, scaling in lattice size. We also present an approach to directly simulate the subspace with an odd number of fermions. It allows to independently determine the ground state in both sectors. Without a chemical potential, this corresponds to half-filling and the lowest-energy state with one additional electron or hole. We identify several stability issues, such as degenerate ground states and large single-particle gaps, and provide possible fixes.

Topics & Concepts

Statistical physicsHubbard modelMonte Carlo methodQuantum Monte CarloPhysicsGround stateFermionScalingSubspace topologyDegenerate energy levelsLattice (music)Monte Carlo method in statistical physicsTensor (intrinsic definition)Hybrid Monte CarloQuantum mechanicsComputer scienceMathematicsSuperconductivityGeometryMarkov chain Monte CarloStatisticsArtificial intelligenceAcousticsQuantum many-body systemsPhysics of Superconductivity and MagnetismQuantum and electron transport phenomena