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Fully nonlocal inelastic scattering computations for spectroscopical transmission electron microscopy methods
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Materials Theory.ORCID iD: 0000-0002-0074-1349
Leibniz Institute for Solid State and Materials Research, Dresden.
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Materials Theory.ORCID iD: 0000-0002-6550-0087
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy.
2017 (English)In: Physical Review B, ISSN 2469-9950, E-ISSN 2469-9969, Vol. 96, no 24, article id 245121Article in journal (Refereed) Published
Abstract [en]

The complex interplay of elastic and inelastic scattering amenable to different levels of approximation constitutes the major challenge for the computation and hence interpretation of TEM-based spectroscopical methods. The two major approaches to calculate inelastic scattering cross sections of fast electrons on crystals—Yoshioka-equations-based forward propagation and the reciprocal wave method—are founded in two conceptually differing schemes—a numerical forward integration of each inelastically scattered wave function, yielding the exit density matrix, and a computation of inelastic scattering matrix elements using elastically scattered initial and final states (double channeling). Here, we compare both approaches and show that the latter is computationally competitive to the former by exploiting analytical integration schemes over multiple excited states. Moreover, we show how to include full nonlocality of the inelastic scattering event, neglected in the forward propagation approaches, at no additional computing costs in the reciprocal wave method. Detailed simulations show in some cases significant errors due to the z-locality approximation and hence pitfalls in the interpretation of spectroscopical TEM results.

Place, publisher, year, edition, pages
2017. Vol. 96, no 24, article id 245121
National Category
Condensed Matter Physics
Identifiers
URN: urn:nbn:se:uu:diva-339794DOI: 10.1103/PhysRevB.96.245121ISI: 000417831800004OAI: oai:DiVA.org:uu-339794DiVA, id: diva2:1185195
Funder
Swedish Research CouncilGöran Gustafsson Foundation for Research in Natural Sciences and MedicineEU, Horizon 2020, 715620Available from: 2018-02-23 Created: 2018-02-23 Last updated: 2018-04-11Bibliographically approved
In thesis
1. Signal Processing Tools for Electron Microscopy
Open this publication in new window or tab >>Signal Processing Tools for Electron Microscopy
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The detection of weak signals in noisy data is a problem which occurs across various disciplines. Here, the signal of interest is the spectral signature of the electron magnetic chiral dichroism (EMCD) effect. In principle, EMCD allows for the measurement of local magnetic structures in the electron microscope, its spatial resolution, versatility and low hardware requirements giving it an eminent position among competing measurement techniques. However, experimental shortcomings as well as intrinsically low signal to noise ratio render its measurement challenging to the present day.   

This thesis explores how posterior data processing may aid the analysis of various data from the electron microscope. Following a brief introduction to different signals arising in the microscope and a yet briefer survey of the state of the art of EMCD measurements, noise removal strategies are presented. Afterwards, gears are shifted to discuss the separation of mixed signals into their physically meaningful source components based on their assumed mathematical characteristics, so called blind source separation (BSS).    

A data processing workflow for detecting weak signals in noisy spectra is derived from these considerations, ultimately culminating in several demonstrations of the extraction of EMCD signals. While the focus of the thesis does lie on data processing strategies for EMCD detection, the approaches presented here are similarly applicable in other situations. Related topics such as the general analysis of hyperspectral images using BSS methods or the fast analysis of large data sets are also discussed.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 60
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1672
National Category
Physical Sciences Computer Sciences Other Mathematics
Identifiers
urn:nbn:se:uu:diva-348264 (URN)978-91-513-0345-1 (ISBN)
Public defence
2018-06-12, Å2001, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-05-18 Created: 2018-04-11 Last updated: 2018-05-18

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Rusz, JanSpiegelberg, JakobTyutyunnikov, Dmitry

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