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Manuscript Title: Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques.
Authors: Bruno Golosio, Tom Schoonjans, Antonio Brunetti, Piernicola Oliva, Giovanni Luca Masala
Program title: XRMC
Catalogue identifier: AERO_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 185(2014)1044
Programming language: C++.
Computer: Tested on several PCs and on Mac.
Operating system: Linux, Mac OS X, Windows (native and cygwin).
RAM: It is dependent on the input data but usually between 1 and 10 MB.
Keywords: X-ray imaging, X-ray spectroscopy, Monte Carlo simulation.
PACS: 87.10.Rt, 87.59.-e, 87.64.-t, 87.64.Aa.
Classification: 2.5, 21.1.

External routines: XrayLib (https://github.com/tschoonj/xraylib/wiki)

Nature of problem:
Simulation of a wide range of X-ray imaging and spectroscopy experiments using different types of sources and detectors.

Solution method:
XRMC is a versatile program that is useful for the simulation of a wide range of X-ray imaging and spectroscopy experiments. It enables the simulation of monochromatic and polychromatic X-ray sources, with unpolarised or partially/completely polarised radiation. Single-element detectors as well as two-dimensional pixel detectors can be used in the simulations, with several acquisition options. In the current version of the program, the sample is modelled by combining convex three-dimensional objects demarcated by quadric surfaces, such as planes, ellipsoids and cylinders. The Monte Carlo approach makes XRMC able to accurately simulate X-ray photon transport and interactions with matter up to any order of interaction. The differential cross-sections and all other quantities related to the interaction processes (photoelectric absorption, fluorescence emission, elastic and inelastic scattering) are computed using the xraylib software library, which is currently the most complete and up-to-date software library for X-ray parameters. The use of variance reduction techniques makes XRMC able to reduce the simulation time by several orders of magnitude compared to other general-purpose Monte Carlo simulation programs.

Running time:
It is dependent on the complexity of the simulation. For the examples distributed with the code, it ranges from less than 1 second to a few minutes.