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Bayesian Optimization for Multi-dimensional Alignment: Tuning Aberration Correctors and Ptychographic Reconstructions

Published online by Cambridge University Press:  22 July 2022

Chenyu Zhang
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA
Yu-Tsun Shao
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA
Zhaslan Baraissov
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA
Cameron J. Duncan
Affiliation:
Cornell Laboratory for Accelerator-Based Science and Education, Cornell University, Ithaca, NY, USA
Adi Hanuka
Affiliation:
SLAC National Laboratory, Menlo Park, CA, USA
Auralee L. Edelen
Affiliation:
SLAC National Laboratory, Menlo Park, CA, USA
Jared M. Maxson
Affiliation:
Cornell Laboratory for Accelerator-Based Science and Education, Cornell University, Ithaca, NY, USA
David A. Muller
Affiliation:
School of Applied and Engineering Physics, Cornell University, Ithaca, NY, USA

Abstract

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Type
On Demand - Artificial Intelligence, Instrument Automation, and High-Dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

Chen, Z. et al. Mixed-state electron ptychography enables sub-angstrom resolution imaging with picometer precision at low dose. Nature Communications 11, 2994 (2020).CrossRefGoogle ScholarPubMed
Balandat, M. et al. BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization. (2020).Google Scholar
Floettmann, K. Some basic features of the beam emittance. Physical Review Special Topics - Accelerators and Beams 6, 8086 (2003).Google Scholar
Funded by the Center for Bright Beams, an NSF STC (NSF PHY-1549132).Google Scholar