ECCS-CDS&E: High-performance computational framework for real-time phase retrieval X-Ray imaging

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Modern science and technology increasingly rely on materials and devices utilizing unique properties of nanometer-scale composition. It is critical to be able to characterize such complex nanoscale configurations. A unique tool for characterization of nanoscale materials and devices is X-ray imaging, which can provide structural images with a high spatial and time resolution. In a typical X-ray imaging setup an X-ray source generates an X-ray beam that is scattered from the structure. The scattered X-ray beam is captured by a camera, and the resulting picture is processed to reconstruct the actual structure configuration. Due to their short wavelength X-rays can penetrate the structure's volume thus enabling not only two-dimensional but also three-dimensional imaging. X-ray imaging typically requires a significant computational effort for image reconstruction and often the computational time is longer than the time for performing the experiment. This project aims at closing this gap by creating high-performance computational tools for real-time X-ray imaging. The created software is to serve a broad community of synchrotron scientists. The developments in nanoscale imaging are intended to have applications in areas ranging from condensed matter physics to biology and chemistry of single molecules. A close interdisciplinary research effort between a computational researcher and an expert in X-ray scattering and material physics will benefit graduate students and postdocs working in these fields, and is likely to result in new and unexpected discoveries. The goal of this research project is to create a high-performance computational framework for real-time X-ray imaging to be performed at X-ray scattering facilities. The X-ray imaging is to be accomplished using a new emerging three-dimensional X-ray imaging methodology called Coherent X-ray Diffractive Imaging (CXDI), which is based on computational phase-retrieval of the X-ray diffraction patterns. The proposed research includes algorithm and code implementation, practical application, and educational components. A set of algorithms for phase retrieval X-ray imaging are to be introduced, including methods for image representation and use of relevant constraints, methods for computing transformations between real to reciprocal spaces, and implementations on massively parallel computing systems. The research effort also introduces a virtual synchrotron framework utilizing computational methods to simulate experimental image reconstruction and provide required constraints, with magnetic nanostructures as a testbed. The developed computational framework is to be applied to real-time study of nanostructured materials and devices, such as nanoscale magnetic devices. The program integrates research and education by enhancing undergraduate and graduate courses on computational physics, micromagnetics and electromagnetics as well as providing graduate and undergraduate student training and contributing to diversity.