Determinant Quantum Monte Carlo data for the Hubbard model on the half filled square lattice, on a (U,B)-grid

Data generated with QUEST 1.4.9. For documentation see these two homepages: Original homepage: http://quest.ucdavis.edu/ Newest version available at: https://code.google.com/archive/p/quest-qmc/ The simulations are done at half filling on a square lattice, with the following parameters: Lattice size...

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Hauptverfasser: Kapetanović, Edin, Schüler, Malte, Czycholl, Gerd, Wehling, Tim O.
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Schüler, Malte
Czycholl, Gerd
Wehling, Tim O.
description Data generated with QUEST 1.4.9. For documentation see these two homepages: Original homepage: http://quest.ucdavis.edu/ Newest version available at: https://code.google.com/archive/p/quest-qmc/ The simulations are done at half filling on a square lattice, with the following parameters: Lattice sizes: 4x4, 6x6, 8x8, 10x10, 12x12, periodic boundary conditions Trotter discretizations: 0.1 and 0.2 Inverse temperature beta = 10.0 48 values for the on-site interaction U from 0.0 to 10.0 48 values for the magnetic field (in z-direction) B from 0.0 to 4.0 10000 warmup sweeps, 30000 measurement sweeps The following data from equal time measurements are available: Charge-Charge Correlation (next neighbors) Greens Function (n.n.) Magnetization Double Occupancy Kinetic Energy Total Energy Spin-Spin Correlation (n.n.) Spin-Spin Correlation (only ZZ) (n.n.) Ferromagnetic Structure Factor (ZZ) Antiferromagnetic Structure Factor (ZZ) The data are available as a hdf5 archive. The python script 'extract.py' illustrates the access with h5py. Relevant QUEST input parameters are provided in the group 'parameters' within the archive. All calculated quantities are averaged over multiple consecutive simulations, which is why the data is not presented in the usual QUEST output. This was necessary due to limited walltime on the used supercomputer. The authors acknowledge the North-German Supercomputing Alliance (HLRN) for providing computing resources via project number hbp00046 that have contributed to these results.
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The python script 'extract.py' illustrates the access with h5py. Relevant QUEST input parameters are provided in the group 'parameters' within the archive. All calculated quantities are averaged over multiple consecutive simulations, which is why the data is not presented in the usual QUEST output. This was necessary due to limited walltime on the used supercomputer. 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subjects DQMC
Hubbard model
magnetic field
square lattice
title Determinant Quantum Monte Carlo data for the Hubbard model on the half filled square lattice, on a (U,B)-grid
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