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    Area of Science:

    • X-ray imaging
    • Materials science
    • Computational imaging

    Background:

    • Ptychographic imaging coupled with tomography enables nanoscale 3D imaging.
    • Ptychographic x-ray computed tomography (PXCT) requires extensive diffraction pattern data collection.
    • Current PXCT methods face challenges in efficient data acquisition and processing.

    Purpose of the Study:

    • To derive equations for calculating data collection rates in PXCT.
    • To determine computational system requirements for real-time ptychographic data processing.
    • To expedite the ptychography step within PXCT workflows.

    Main Methods:

    • Derivation of theoretical equations for data collection rates based on experimental setups.
    • Analysis of computational system requirements for real-time processing.
    • Application of theoretical results to simulated diffraction pattern reconstruction data.
    • Evaluation of computational resources for representative experimental setups.

    Main Results:

    • A framework for calculating data acquisition rates in PXCT.
    • Quantification of computational resources needed for real-time ptychographic data processing.
    • Demonstration of theoretical results using simulated data.
    • Results applicable across various ptychographic reconstruction algorithms.

    Conclusions:

    • The derived equations enable efficient planning of PXCT experiments.
    • Understanding computational needs facilitates real-time data processing for PXCT.
    • This work provides a pathway to accelerate PXCT by optimizing the ptychography stage.
    • The findings are algorithm-independent, offering broad applicability in nanoscale imaging.