python3-bornagain
Simulate and fit X-ray and neutron GISAS -- Python3
Description
BornAgain is a software package to simulate and fit small-angle scattering at grazing incidence. It supports analysis of both X-ray (GISAXS) and neutron (GISANS) data. Calculations are carried out in the framework of the distorted wave Born approximation (DWBA). BornAgain provides a graphical user interface for interactive use as well as a generic Python and C++ framework for modeling multilayer samples with smooth or rough interfaces and with various types of embedded nanoparticles. BornAgain supports: Layers: * Multilayers without any restrictions on the number of layers
* Interface roughness correlation
* Magnetic materials
Particles:
* Choice between different shapes of particles (form factors)
* Particles with inner structures
* Assemblies of particles
* Size distribution of the particles (polydispersity)
Positions of Particles:
* Decoupled implementations between vertical and planar positions
* Vertical distributions: particles at specific depth in layers or on top.
* Planar distributions:
- fully disordered systems
- short-range order distribution (paracrystals)
- two- and one-dimensional lattices
Input Beam:
* Polarized or unpolarized neutrons
* X-ray
* Divergence of the input beam (wavelength, incident angles) following
different distributions
* Possible normalization of the input intensity
Detector:
* Off specular scattering
* Two-dimensional intensity matrix, function of the output angles
Use of BornAgain:
* Simulation of GISAXS and GISANS from the generated sample
* Fitting to reference data (experimental or numerical)
* Interactions via Python scripts or Graphical User Interface
If you use BornAgain in your work, please cite
C. Durniak, M. Ganeva, G. Pospelov, W. Van Herck, J. Wuttke (2015), BornAgain
— Software for simulating and fitting X-ray and neutron small-angle
scattering at grazing incidence, version <version you used>,
http://www.bornagainproject.org
This package contains the Python bindings for use in scripts.
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