AI Article Synopsis
- The development of hard X-ray nanoprobe techniques has led to various experimental methods such as nano-XAS, nano-XRD, nano-XRF, ptychography, and tomography, each requiring its own data processing algorithms.
- The increase in data acquisition rates has created significant challenges for these algorithms due to the large volumes of generated data.
- This work presents an intuitive software system that integrates and optimizes these algorithms, enhancing data processing speed and addressing the complexities in synchrotron data processing through a component-based design approach.
Article Abstract
The development of hard X-ray nanoprobe techniques has given rise to a number of experimental methods, like nano-XAS, nano-XRD, nano-XRF, ptychography and tomography. Each method has its own unique data processing algorithms. With the increase in data acquisition rate, the large amount of generated data is now a big challenge to these algorithms. In this work, an intuitive, user-friendly software system is introduced to integrate and manage these algorithms; by taking advantage of the loosely coupled, component-based design approach of the system, the data processing speed of the imaging algorithm is enhanced through optimization of the parallelism efficiency. This study provides meaningful solutions to tackle complexity challenges faced in synchrotron data processing.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11371055 | PMC |
| http://dx.doi.org/10.1107/S1600577524006994 | DOI Listing |
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