Incorrect support and missing center tolerances of phasing algorithms.

Area of Science:

• Physics
• Materials Science
• Imaging Science

Background:

• Iterative algorithms in x-ray diffraction microscopy use a priori information, like finite support constraints, to reconstruct real-space images from reciprocal space phase information.
• Experimental limitations such as poorly defined object shapes and incomplete diffraction pattern measurements can hinder accurate image reconstruction.

Purpose of the Study:

• To investigate the impact of object support errors and incomplete diffraction data on iterative reconstruction algorithms in x-ray diffraction microscopy.
• To identify indicators of reconstruction failure and assess the effectiveness of error mitigation strategies.

Main Methods:

• Computer simulations were employed to model the effects of inaccurate object support constraints and missing central diffraction data on common reconstruction algorithms.
• Analysis focused on convergence behavior, phase retrieval transfer function characteristics, and image artifact formation.

Main Results:

• Overly restrictive object support constraints were found to prevent successful algorithm convergence, often indicated by pathological phase retrieval transfer function behavior.
• Missing central diffraction speckles, due to dynamic range limitations, introduce increasing image artifacts, particularly when more than approximately 10 speckles are absent.
• The removal of unconstrained modes proved beneficial only when fewer than approximately 50 central speckles were missing.

Conclusions:

• The study provides crucial insights into the reconstructability of experimental coherent diffraction patterns by highlighting the sensitivity of iterative algorithms to data quality and prior information accuracy.
• Understanding these error effects aids in interpreting experimental results and optimizing data acquisition strategies for improved x-ray diffraction microscopy outcomes.