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40 results for “Hubbard model”
Data files for "Ground state and spectral properties of the doped one-dimensional optical Hubbard-Su-Schrieffer-Heeger model"
<p>This repo contains the relevant data files for the paper D. Banerjee et al., "Ground state and spectral properties of the doped one-dimensional optical Hubbard-Su-Schrieffer-Heeger model". (2023) Preprint: arXiv:2303.10193</p> <p> </p>
Data underpinning "Disorder-induced spin-charge separation in the 1-D Hubbard model"
<p>Many-body localisation is believed to be generically unstable in quantum systems with continuous non-Abelian symmetries, even in the presence of strong disorder. Breaking these symmetries can stabilise the localised phase, leading to the emergence of an extensive number of quasi-locally conserved quantities known as local integrals of motion, or l-bits. Using a sophisticated non-perturbative technique based on continuous unitary transforms, we investigate the one-dimensional Hubbard model subject to both spin and charge disorder, compute the associated l-bits and demonstrate that the disorder gives rise to a novel form of spin-charge separation. We examine the role of symmetries in delocalising the spin and charge degrees of freedom, and show that while symmetries generally lead to delocalisation through multi-particle resonant processes, certain subsets of states appear stable.</p>
Supporting data for "Measuring the Loschmidt amplitude for finite-energy properties of the Fermi-Hubbard model on an ion-trap quantum computer"
<p>This repository contains the supporting data for the publication: "Measuring the Loschmidt amplitude for finite-energy properties of the Fermi-Hubbard model on an ion-trap quantum computer".</p>
z4ch4ry/leadershipdata: Garfield, Hubbard, & Hagen, 2019, Evolutionary models of leadership: Tests and synthesis
<p>Public release of data associated with publication in Human Nature 30 (1) 2019 and Evolution and Human Behavior 31 (2) 2020.</p> <p>Updated to reflect additional data used in the second publication in Evolution and Human Behavior, <a href="https://doi.org/10.1016/j.evolhumbehav.2020.07.012">https://doi.org/10.1016/j.evolhumbehav.2020.07.012</a>.</p> <p> </p> <p> </p>
QMC Raw Data for Disentangling the Physics of the Attractive Hubbard Model via the Accessible and Symmetry-Resolved Entanglement Entropies
<p><strong>Data Summary</strong></p> <p>Raw data of 'Disentangling the Physics of the Attractive Hubbard Model via the Accessible and Symmetry-Resolved Entanglement Entropies'.</p> <p>The default Julia RNG generates random seeds, with the seed number corresponding to the last four digits of each file name..</p> <p>For more details, please check README.md on the GitHub repository.</p> <p>The scripts for processing the raw data are located in the data folder within the same repository.</p>
Reproducibility package for "Super-Tonks-Girardeau Quench in the Extended Bose-Hubbard Model"
Open the record for dataset details and reuse information.
Data set for "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit"
<p>This data set is for the paper "Intertwined spin, charge, and pair correlations in the two-dimensional Hubbard model in the thermodynamic limit". It contains the raw DCA HD5 and DQMC plain text output files, as well as the scripts and final processed data used to generate figures 1-5 of the main text and supplementary figures 1-12. Copies of the figures and latex files are also included for completeness. </p>
Determinant Quantum Monte Carlo data for the Hubbard model on the square lattice on a (t,U) grid.
<p>Data generated with QUEST 1.4.9. For documentation see these two homepages:<br> Original homepage: http://quest.ucdavis.edu/<br> Newest version available at: https://code.google.com/archive/p/quest-qmc/</p> <p>Available data from equal time measurements:</p> <ul> <li>up-up charge correlation function</li> <li>up-dn charge correlation function</li> <li>sz-sz spin correlation function</li> <li>pair correlation function</li> <li>greens function</li> <li>kinetic energy</li> <li>total energy</li> <li>chi thermal</li> <li>squared magnetization</li> <li>ZZ AF structure factor</li> </ul> <p>Data for the square lattice calculated for</p> <ul> <li>lattice sizes 8x8, 10x10, 12x12</li> <li>trotter discretizations 0.05, 0.1, 0.2</li> <li>inverse temperature 10.0</li> <li>U 0.0 to 2.7 in steps of 0.1</li> <li>t from 1.0 to 1.48 in steps of 0.02</li> </ul> <p>All simulations are done for half filling.</p> <p>The data are used in the publication "Thermodynamics of the metal-insulator transition in the extended Hubbard model" available on the arXiv (arXiv:1903.09947). There it is used to do an extrapolation of finite size and finite trotter errors and calculate the free energy by integrating the double occupation.</p> <p>The data are available in hdf5 archives and can easily be accessed, e.g., with python and h5py. An example python script is included. Relevant input parameters are included in the h5 files.</p> <p>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.</p> <p>The authors acknowledge the North-German Supercomputing Alliance (HLRN) for providing computing resources via project number hbp00046 that have contributed to these results.</p>
Extended Hubbard Model with spin-valley polarization DMRG solution
<p>The data set for containing observables obtained by means of Density Matrix Renormalization Group for the Extended Hubbard model at filling n=2/3 and with spin-valley polarization included in the single-particle term. For all the considered case the on-site Hubbard repulsion U is set to 15|t| and |t| = 1. The phase for hopping termi is 2*pi/3.</p> <p>Folders naming convention is following:</p> <p>VXYZ</p> <p>V stands for intersite interaction and XYZ is its magnitude.</p> <p> </p> <p>In each folder there are following files:</p> <p>- n_single</p> <p>columns: i j Re_up Im_up Re_dn Im_dn</p> <p>Where: i,j are site indicies Re(Im)_up(dn) stand for the real(imaginary) part of single particle equal-time Green function for up(dn) spin</p> <p>- nn</p> <p>columns: i j Re_up Im_up Re_dn Im_dn Re_(up+dn) Im_(up+dn)</p> <p>Where: i,j are site indicies Re(Im)_up(dn) stand for the real(imaginary) part of two particle equal-time Green function <n_i,up(dn) n_j,up(dn)> for up(dn) spin and two last columns correspond to <(n_i,up+n_i,dn)(n_j,up+n_j,dn)></p> <p>- ss</p> <p>columns: i j Re Im</p> <p>Where: i,j are site indicies Re(Im) stand for the real(imaginary) part of two particle equal-time Green function <S_i S_j> where S_i is total spin operator on site "i"</p> <p>- szsz</p> <p>columns: i j Re Im</p> <p>Where: i,j are site indicies Re(Im) stand for the real(imaginary) part of two particle equal-time Green function <S_z S_z> where S_z is z-th component of spin operator on site "i"</p> <p>- spsm</p> <p>columns: i j Re Im Re Im</p> <p>Where: i,j are site indicies Re(Im) stand for the real(imaginary) part of two particle equal-time Green function <S_i^(+)S_j^(-)> and <S_i^(-)S_j^(+)> where S_i^(+/-) are spin ladder operators</p> <p> </p>
Data Files for P. Mai et al., "Fluctuating charge-density-wave correlations in the three-band Hubbard model" (2024)
<p>These are the data for P. Mai et al., "Fluctuating charge-density-wave correlations in the three-band Hubbard model" (2024)</p> <p>arXiv reference: https://arxiv.org/abs/2405.13164</p> <p>This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number DE-SC0022311. This research used resources of the Oak Ridge Leadership Computing Facility, a DOE Office of Science User Facility supported under Contract No. DE-AC05-00OR22725.</p>
Numerical approaches for DC Hall coefficient of the Hubbard model
<p>This contains the data and the notebooks to generate the data and plots in the paper "Numerical approaches for estimating the DC Hall coefficient of the doped Hubbard model" (arXiv:2103.04998)</p> <p>DQMC code for the zero field data: <a href="https://github.com/wenowang96/3-current">https://github.com/wenowang96/3-current</a></p> <p>DQMC code for the finite field data: <a href="https://github.com/edwnh/dqmc">https://github.com/edwnh/dqmc</a></p> <p>proxy D1 in the code is proxy D in the paper.</p> <p>proxy D2 in the code is proxy D_gamma in the paper.</p>
Avoiding Ergodicity Problems in Lattice Discretizations of the Hubbard Model - Data
<p>These are the datasets used to make the figures in "Avoiding Ergodicity Problems in Lattice Discretizations of the Hubbard Model". The data was generated using Isle v0.1. Install Isle in order to run the scripts proved with the data files.</p> <p> </p>
Data files for Peizhi Mai et al., "Robust charge-density wave correlations in the electron-doped single-band Hubbard model" (2023)
<p>Data files for "Robust charge-density wave correlations in the electron-doped single-band Hubbard model" by P. Mai, N. S. Nichols, S. Karakuzu, F. Bao, A Del Maestro, T. A. Maier, and Steven Johnston</p> <p>Preprint: https://arxiv.org/abs/2210.14930</p>
Supplementary files for "Programmable arrays of alkaline earth atoms: qubits, clocks, and the Bose-Hubbard model"
<p>Supplementary files for "Programmable arrays of alkaline earth atoms: qubits, clocks, and the Bose-Hubbard model"</p><p>Lab construction timelapse: <a href="https://zenodo.org/api/records/10019752/draft/files/lablapse_no_seizure.mov/content">lablapse_no_seizure.mov</a></p><p>Grover's search using pendulums: <a href="https://zenodo.org/api/records/10019752/draft/files/AY_grover_pendulum.mp4/content">AY_grover_pendulum.mp4</a></p>
Data for: Origin and fate of the pseudogap in the doped Hubbard model
<p>Data for publication "Origin and fate of the pseudogap in the doped Hubbard model"</p>
Data files for "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al.
<p>Data files for the manuscript "Stripe correlations in the two-dimensional Hubbard-Holstein model" by S. Karakuzu et al. To appear in Communications Physics. Preprint available at https://arxiv.org/abs/2205.15464 (2022).</p> <p>This work was supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Award Number<br> DE-SC0022311.</p>
Observation of separated dynamics of charge and spin in the Fermi-Hubbard model
<p>Strongly correlated quantum systems give rise to many exotic physical phenomena, including high-temperature superconductivity. Simulating these systems on quantum computers may avoid the prohibitively high computational cost incurred in classical approaches. However, systematic errors and decoherence effects presented in current quantum devices make it difficult to achieve this. Here, we simulate the dynamics of the one-dimensional Fermi-Hubbard model using 16 qubits on a digital superconducting quantum processor. We observe separations in the spreading velocities of charge and spin densities in the highly excited regime, a regime that is beyond the conventional quasiparticle picture. To minimize systematic errors, we introduce an accurate gate calibration procedure that is fast enough to capture temporal drifts of the gate parameters. We also employ a sequence of error-mitigation techniques to reduce decoherence effects and residual systematic errors. These procedures allow us to simulate the time evolution of the model faithfully despite having over 600 two-qubit gates in our circuits. Our experiment charts a path to practical quantum simulation of strongly correlated phenomena using available quantum devices.</p>
Observation of separated dynamics of charge and spin in the Fermi-Hubbard model
Open the record for dataset details and reuse information.
Data set for thermal transport study in single-band Hubbard Model using DQMC: Lorenz number and Wiedemann-Franz law
<p>Data set for thermal transport study in single-band Hubbard Model using DQMC: Lorenz number and Wiedemann-Franz law</p> <p>Labeling in plots are slightly different with the preprint paper.</p>
Thermopower in the Hubbard Model dataset
<p>Thermopower in the Hubbard Model dataset.</p> <p>Preprint: <a href="https://arxiv.org/abs/2302.13169">arXiv:2302.13169</a></p>
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