Monte Carlo simulation of X-ray imaging and spectroscopy experiments using quadric geometry and variance reduction techniques

Abstract

The simulation of X-ray imaging experiments is often performed using deterministic codes, which can be relatively fast and easy to use. However, such codes are generally not suitable for the simulation of even slightly more complex experimental conditions, involving, for instance, first-order or higher-order scattering, X-ray fluorescence emissions, or more complex geometries, particularly for experiments that combine spatial resolution with spectral information. In such cases, simulations are often performed using codes based on the Monte Carlo method. In a simple Monte Carlo approach, the interaction position of an X-ray photon and the state of the photon after an interaction are obtained simply according to the theoretical probability distributions. This approach may be quite inefficient because the final channels of interest may include only a limited region of space or photons produced by a rare interaction, e.g., fluorescent emission from elements with very low concentrations. In the field of X-ray fluorescence spectroscopy, this problem has been solved by combining the Monte Carlo method with variance reduction techniques, which can reduce the computation time by several orders of magnitude. In this work, we present a C++ code for the general simulation of X-ray imaging and spectroscopy experiments, based on the application of the Monte Carlo method in combination with variance reduction techniques, with a description of sample geometry based on quadric surfaces. We describe the benefits of the object-oriented approach in terms of code maintenance, the flexibility of the program for the simulation of different experimental conditions and the possibility of easily adding new modules. Sample applications in the fields of X-ray imaging and X-ray spectroscopy are discussed

Energy dispersive X-ray fluorescence spectroscopy/Monte Carlo simulation approach for the non-destructive analysis of corrosion patina-bearing alloys in archaeological bronzes: The case of the bowl from the Fareleira 3 site (Vidigueira, South Portugal)

“…For this purpose, two fast Monte Carlo codes have been developed for this kind of application in order to simulate a good quality spectrum in a couple of minutes, the same order of time required by the measurements [8][9][10][11][12]. Both of them are based on a constantly updated X-ray database, called Xraylib [13,14].…”

An Energy-Dispersive X-Ray Fluorescence Spectrometry and Monte Carlo simulation study of Iron-Age Nuragic small bronzes (“Navicelle”) from Sardinia, Italy

“…This time is comparable to the experimental acquisition time and therefore the simulation can be regarded as being performed in real time. Two of such fast and specialized MC codes are readily available [27][28][29][30][31][32]. The first one was developed specifically for XRF experiments, while the second one can be also used to simulate radiographic, CT and phase contrast simulations.…”

“…Both codes are based on the Xraylib database [33,34]. In the current study, we used the second one, called XRMC [31]. Before running the simulation, MC codes require a detailed description of both sample's composition and structure.…”

X-ray fluorescence spectroscopy and Monte Carlo characterization of a unique nuragic artifact (Sardinia, Italy)

“…However, a number of fast Monte Carlo codes have been developed for this specific application. They are based on the so-called variance reduction techniques which allow to reduce the simulation time down to few minutes, such as is the case with the XMI-SIMS and XRMC code packages [16][17][18][19][20]. In this paper we use the XRMC code.…”