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Optimized Coincidence Doppler Broadening Spectroscopy using deconvolution algorithms

  • K. F. Ho*
  • , H. M. Ching
  • , K. W. Cheng
  • , C. D. Beling
  • , S. Fung
  • , K. P. Ng
  • *Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

In the last few years a number of excellent deconvolution algorithms have been developed for use in "de-blurring" 2D images. Here we report briefly on one such algorithm we have studied which uses the non-negativity constraint to optimize the regularization and which is applied to the 2D image like data produced in Coincidence Doppler Broadening Spectroscopy (CDBS). The system instrumental resolution functions are obtained using the 514keV line from 85Sr. The technique when applied to a series of well annealed polycrystalline metals gives two photon momentum data on a quality comparable to that obtainable using ID Angular Correlation of Annihilation Radiation (ACAR).

Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Positron Annihilation, ICPA-13
EditorsToshio Hyodo, Yoshinori Kobayashi, Yasuyuki Nagashima, Haruo Saito
PublisherTrans Tech Publications Ltd
Pages477-479
Number of pages3
ISBN (Electronic)9783038599388, 9783035706222
ISBN (Print)9780878499366
DOIs
Publication statusPublished - Jan 2004
EventThe 13th International Conference on Positron Annihilation, ICPA-13 - Kyoto, Japan
Duration: 7 Sept 200312 Sept 2003
https://www.scientific.net/book/positron-annihilation-icpa-13/978-3-0357-0622-2 (Conference proceedings)

Publication series

NameMaterials Science Forum
Volume445-446
ISSN (Print)0255-5476
ISSN (Electronic)1662-9752

Conference

ConferenceThe 13th International Conference on Positron Annihilation, ICPA-13
Abbreviated titleICPA-13
Country/TerritoryJapan
CityKyoto
Period7/09/0312/09/03
Internet address

User-Defined Keywords

  • Coincidence Doppler Broadening Spectroscopy
  • Deconvolution
  • Least-Squares Method
  • Non-Negativity Constraints

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