Mitigating tilt-induced artifacts in reflection ptychography via optimization of the tilt angles

Journal Article (2024)
Author(s)

Sander Senhorst (TU Delft - ImPhys/Coene group)

Y. Shao (TU Delft - ImPhys/Coene group)

S. Weerdenburg (ASML, TU Delft - ImPhys/Coene group)

Roland Horsten (TU Delft - ImPhys/Pereira group)

Christina Porter (ASML)

Wim M. Coene (TU Delft - ImPhys/Coene group, ASML)

Research Group
ImPhys/Coene group
DOI related publication
https://doi.org/10.1364/OE.542569
More Info
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Publication Year
2024
Language
English
Research Group
ImPhys/Coene group
Issue number
25
Volume number
32
Pages (from-to)
44017-44030
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Abstract

Ptychography in a reflection geometry shows great promise for non-destructive imaging of 3-dimensional nanostructures at the surface of a thick substrate. A major challenge to obtain high quality reflection-ptychographic images under near-grazing conditions has been to calibrate the incidence angle used to straighten the measured curved diffraction patterns in a process referred to as ‘tilted plane correction’ (TPC). In this work, we leverage the flexibility of automatic differentiation (AD)-based modeling to realize an alternative approach, where the tilted propagation is included in the forward model. Use of AD allows us to jointly optimize the tilt angles with the typical probe and object, eliminating the need for accurate calibration or random search optimization. The approach was validated using datasets generated with an extreme ultraviolet (EUV) beamline based on both a tabletop high harmonic generation (HHG) source and a visible laser. We demonstrate that the proposed approach can converge to a precision of ±0.05◦ for probe beams at 70◦ angle of incidence, possibly precise enough for use as a calibration approach. Furthermore, we demonstrate that optimizing for the tilt angles reduces artifacts and increases reconstruction fidelity. Use of AD not only streamlines the current ptychographic reconstruction process, but should also enable optimization of more complex models in other domains, which will likely be useful for future advancements in computational imaging.