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Density Functional Theory with Finite Difference and Lagrange Function Basis Sets

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lfdft

###Density Functional Theory with Finite Difference and Lagrange Function Basis Set A easy to run, understand and modify package allowing rapid implementation and testing of computational methods.

Current features

  • LDA approximation for exchange and correlation
  • non-periodic systems only
  • finite difference or Lagrange function kinetic operator
  • built-in set of Pseudopotentials:
    • Ag, Al, Au, Be, B, Br, Cl, C, Cs, Cu, F, Ge, He, H, K, Li, Mg, Na, Ni, N, O, Pd, P, Rb, Si, S, Ti, V, W

Coming soon

In general these features have been implemented, but need to be integrated with this code base and/or tested.

  • Real-time time-dependent density functional theory
  • Time-dependent current (including non-local contribution)
  • Erhenfest dynamics
  • Laser Pulse
  • Periodic boundary conditions
  • Atomic Orbitals (LCAO)
  • Atomic forces (e.g. geometry optimization)
  • Complex potential transport

Install

Requirements: NumPy and SciPy. Installing in a virtualenv is recommended.

Usage

After e.g. python setup.py develop to install the package run from the command line with $ lfdft input_file

Atomic geometry is specified by XYZ format where the comment line contains the unit cell size in Angstroms. Example C2H4 in 10.0 x 10.0 x 10.0 Angstrom box:

6
10.0 10.0 10.0
C       5.000000000000000      5.000000000000000      5.667480000000000
C       5.000000000000000      5.000000000000000      4.332520000000000
H       5.000000000000000      5.922832000000000      6.237695000000000
H       5.000000000000000      4.077168000000000      6.237695000000000
H       5.000000000000000      5.922832000000000      3.762305000000000
H       5.000000000000000      4.077168000000000      3.762305000000000

Note: the computational grid is defined on [0, L] where L is length of the cell in a given direction. Therefore it is important to ensure the atoms are centered in the compuational box.

This material is based upon work supported by the National Science Foundation under Grant Number (1226258). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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