metadata

license: cc0-1.0
language:
  - en
tags:
  - physics
  - quantum-monte-carlo
  - fractional-quantum-hall
pretty_name: DeepHall Data
arxiv: 2412.14795
viewer: false

Data for the Study: "Taming Landau Level Mixing in Fractional Quantum Hall States with Deep Learning"

This dataset contains the raw data and plotting code used in the study titled:

"Taming Landau Level Mixing in Fractional Quantum Hall States with Deep Learning"

The relevant code is available at https://github.com/bytedance/DeepHall.

Data Files

The data directories are named following the convention n{number of electrons}l{flux}/k{interaction strength kappa}.

For each calculation, the following data are included:

config.yml: Hyperparameters used in the simulation.
train_stats.csv: Energy, angular momentum, and other quantities at each training step.
ckpt_xxxxxx.npz: Checkpoint of the final state, including network parameters, walker coordinates, and other relevant quantities.
energy/: NetObs energy evaluation results with fixed parameters.
1rdm/, overlap/, pair_corr/: NetObs evaluation of the one-body reduced density matrix (1-RDM), overlap with the Laughlin wavefunction, and the pair correlation function.

For the electron densities of quasiparticle and quasihole states, the data are placed in nxlx/kx/lz{angular momentum in the z direction}, with:

density/: NetObs evaluation of electron density.

Code for Plotting Figures

prep.py: Script to process data and create energy_vs_n.csv and llm_1_3.csv for use in plotting.
plot.ipynb: Jupyter notebook for generating the plots.