Fast GPU-based absolute intensity determination for energy-dispersive X-ray Laue diffraction

摘要

This paper presents a novel method for fast determination of absolute intensities in the sites of Laue spots generated by a tetragonal hen egg-white lysozyme crystal after exposure to white synchrotron radiation during an energy-dispersive X-ray Laue diffraction experiment. The Laue spots are taken by means of an energy-dispersive X-ray 2D pnCCD detector. Current pnCCD detectors have a spatial resolution of 384 × 384 pixels of size 75 × 75 μm~2 each and operate at a maximum of 400 Hz. Future devices are going to have higher spatial resolution and frame rates. The proposed method runs on a computer equipped with multiple Graphics Processing Units (GPUs) which provide fast and parallel processing capabilities. Accordingly, our GPU-based algorithm exploits these capabilities to further analyse the Laue spots of the sample. The main contribution of the paper is therefore an alternative algorithm for determining absolute intensities of Laue spots which are themselves computed from a sequence of pnCCD frames. Moreover, a new method for integrating spectral peak intensities and improved background correction, a differentway of calculating mean count rate of the background signal and also a new method for n-dimensional Poisson fitting are presented. We present a comparison of the quality of results from the GPU-based algorithm with the quality of results from a prior (base) algorithm running on CPU. This comparison shows that our algorithm is able to produce results with at least the same quality as the base algorithm. Furthermore, the GPU-based algorithm is able to speed up one of the most time-consuming parts of the base algorithm, which is n-dimensional Poisson fitting, by a factor of more than 3. Also, the entire procedure of extracting Laue spots' positions, energies and absolute intensities from a raw dataset of pnCCD frames is accelerated by a factor of more than 3.