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Simulate and fit X-ray and neutron GISAS -- doc

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 BornAgain documentation.

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