Supplementary information for the thesis: Using data-derived charge densities in electronic structure methods
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This supplementary information contains the data sets and pieces of original code that are part of the thesis: Using data-derived charge densities in electronic structure methods.
We provide configurations for each data set in the form on input files for either the orbital-free or Kohn-Sham density functional theory code PROFESS or CASTEP, respectively.
The code that we submit is partitioned into 2 parts that correspond to the calculations in Chapter 4 and Chapter 5. These codes compute and infer parametric models for data-derived charge densities using the methods detailed in the main thesis. See the README file for more information.
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The input files provided in each data set are for use with either the orbital-free or Kohn-Sham density functional theory code PROFESS or CASTEP, respectively. More information regarding the specific version of each code used for the calculations in the thesis is contained in the README for each data set.
To infer and calculate parametric models of data-derived densities, see the README associated with each chapter. Both chapters contain Python modules that wrap fortran binary, so before using both pieces of code, the fortran must be compiled using the build.sh scripts provided for each chapter. This process is currently only supported on a linux OS.
Keywords
electronic structure, machine learning, charge densities
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EPSRC (1502917)