Papers › Ptychopy: GPU framework for ptychographic data analysis
Ptychopy: GPU framework for ptychographic data analysis
Ke Yue, Junjing Deng, Yi Jiang, Youssef Nashed, David Vine, Stefan Vogt
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
X-ray ptychography imaging at synchrotron facilities like the Advanced Photon Source (APS) involves controlling instrument hardwares to collect a set of diffraction patterns from overlapping coherent illumination spots on extended samples, managing data storage, reconstructing ptychographic images from acquired diffraction patterns, and providing the visualization of results and feedback. In addition to the complicated workflow, ptychography instrument could produce up to several TB's of data per second that is needed to be processed in real time. This brings up the need to develop a high performance, robust and user friendly processing software package for ptychographic data analysis. In this paper we present a software framework which provides functionality of visualization, work flow control, and data reconstruction. To accelerate the computation and large datasets process, the data reconstruction part is implemented with three algorithms, ePIE, DM and LSQML using CUDA-C on GPU.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections