2022
DOI: 10.1109/tci.2022.3218993
|View full text |Cite
|
Sign up to set email alerts
|

Inverse Multislice Ptychography by Layer-Wise Optimisation and Sparse Matrix Decomposition

Abstract: We propose algorithms based on an optimisation method for inverse multislice ptychography in, e.g. electron microscopy. The multislice method is widely used to model the interaction between relativistic electrons and thick specimens. Since only the intensity of diffraction patterns can be recorded, the challenge in applying inverse multislice ptychography is to uniquely reconstruct the electrostatic potential in each slice up to some ambiguities. In this conceptual study, we show that a unique separation of at… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
4
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6
1

Relationship

1
6

Authors

Journals

citations
Cited by 9 publications
(4 citation statements)
references
References 39 publications
0
4
0
Order By: Relevance
“…However, to our knowledge none of the methods for blind ptychography guarantees a sublinear convergence rate as in Theorem 3.4. The proofs presented in this paper can be extended for layerwise optimization algorithm for multislice ptychography [30]. While Algorithm 2 is supported by theoretical analysis, numerical examples point towards its underperformance in terms of computation time.…”
Section: Conclusion and Discussionmentioning
confidence: 94%
“…However, to our knowledge none of the methods for blind ptychography guarantees a sublinear convergence rate as in Theorem 3.4. The proofs presented in this paper can be extended for layerwise optimization algorithm for multislice ptychography [30]. While Algorithm 2 is supported by theoretical analysis, numerical examples point towards its underperformance in terms of computation time.…”
Section: Conclusion and Discussionmentioning
confidence: 94%
“…Because at low-dose settings, single events at high angles dominate the whole COM calculation due to their weighting with the spatial frequency, determining the COM from diffraction within a cutoff spatial frequency typically improves the signal-to-noise ratio. A 4D-STEM setup also enables advanced processing, e.g., iterative ptychography as with the extended ptychographic iterative engine 11 (ePIE) or potentially inverse multislice 39 , 40 . For iterative 4D-STEM ptychography defocusing leads to a larger overlap of probe positions which is beneficial for the deconvolution of specimen and probe.…”
Section: Discussionmentioning
confidence: 99%
“…Conceptually, 4D STEM possesses the advantage of allowing an enormous flexibility for data processing, with current developments going far beyond direct inversion schemes and single-slice models. In particular, ptychographic iterative engine algorithms perform very well with regards to spatial resolution (Maiden et al, 2009) and developments for inverse multislice ptychography (Bangun et al, 2022;Chen et al, 2021;Maiden et al, 2012) provide solutions beyond the projection assumption. Overcoming the (W)PO limitations to CTEM by 2-3-slice phase retrieval in 4D STEM is thus a promising way to explore the opportunity of resolution and contrast enhancement in future cryo-EM.…”
Section: Discussionmentioning
confidence: 99%