Introduction to geofractal

This package allows to compute average geometric cross sections of fractal dust aggregates by means of a statistical distribution model of monomers proposed in Tazaki (2021).

Terms of use

geofractal is distributed under the MITlicense and can be used, changed and redistributed freely. If you use this package to publish papers, please cite the following paper

R. Tazaki
Analytic expressions for geometric cross-sections of fractal dust aggregates
Monthly Notices of the Royal Astronomical Society, Volume 504, Issue 2, pp.2811-2821

Examples

fortran

The input parameters can be set in call.f90.
The user can specify following three input parameters in call.f90

• df : Fractal dimension (1 ≦ df ≦ 3)
• k0 : Fractal prefactor
• PN : Number of monomers (1 ≦ PN)

In addition, the user also needs to specify following three options

• Angular integration in the calculation of the mean overlapping efficiency
  iqapp=1 : use numerical integration
  iqapp=3 : use approximate analytical solution
• Small non-fractal cluster limit
  iqcon=1 : without small cluster limit
  iqcon=2 : with small cluster limit
• The two-point correlation function of fractal aggregates
  iqcor=1 : The Gaussian cut-off model
  iqcor=2 : The exponential cut-off model
  iqcor=3 : The fractal dimension cut-off model

I recommend following set of options: iqapp=3,iqcor=3,iqcon=2 (default).

To run the code, first of all, compile the codes via

make

This will create an executable file results.x. Then, perform

./results.x

As a result, the output file gratio.out is created.

python

The python package of geofractal is a shortened version of the fortran package as it runs only with the recommended options: iqapp=3,iqcon=2.

Similar to the fortran package, the user can specify the input parameters in call.py

• df : Fractal dimension (1 ≦ df ≦ 3)
• k0 : Fractal prefactor
• PN : Number of monomers (1 ≦ PN)

In addition, the use also needs to opt a model of two-point correlation function:

• cormodel='EXPNL' : The exponential cut-off model
• cormodel='GAUSS' : The Gaussian cut-off model
• cormodel='FLDIM' : The fractal dimension cut-off model (default)

To run the code, simply perform

python call.py

As a result, the output file gratio.out is created.

History

Version 0.1

• Pre-release