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Automatic Optimization of AMS with LabVIEW

Published online by Cambridge University Press:  03 January 2017

V Palonen Open the ORCID record for V Palonen [Opens in a new window]  and
P Tikkanen
V Palonen*
Affiliation:
Department of Physics, University of Helsinki, Finland
P Tikkanen
Affiliation:
Department of Physics, University of Helsinki, Finland
*
*Corresponding author. Email: [email protected].
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Abstract

Accelerator systems designed for a wide variety of ion beam analysis (IBA) applications usually have a multitude of beamline components and long beam lines. In the use of these systems, beam optimization is especially important for attaining high-precision accelerator mass spectrometry (AMS) results. The optimization involves multiple parameters, dependencies between parameters, and multiple optimization targets. To improve the repeatability and reliability of AMS results, we have developed a profiling program for automatic beam optimization. In our implementation, the accelerator control parameters, measured beam currents, and AMS detector count rates are all stored in a real-time database. The profiling routine can scan any accelerator parameter and fetch from the database the profile of any measured quantity as a function of the parameter. The routine is usually used to scan over roughly 20 essential parameters of the system and setting them to the optimum values. Automatic optimization is fast, easy to use, robust to noise, and gives reproducible results. In addition, the graphical output in the form of current and count rate profiles is highly informative. Automatic optimization together with other improvements to the AMS setup have enabled us to push the precision of the system to better than 0.2%.

Keywords

AMS datingexperimentradiocarbon dating
Type
Advances in Physical Measurement Techniques
Information
Radiocarbon , Volume 59 , Special Issue 3: Proceedings of the 22nd International Radiocarbon Conference (Part 2 of 2) , June 2017 , pp. 915 - 920
Copyright
© 2016 by the Arizona Board of Regents on behalf of the University of Arizona 

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Footnotes

Selected Papers from the 2015 Radiocarbon Conference, Dakar, Senegal, 16–20 November 2015

References

REFERENCES

DeTurck, TM, Treacy, DJ, Knies, DL, Grabowski, KS, Knoll, C, Kennedy, CA, Hubler, GK. 1999. A new LabVIEW-based control system for the Naval Research Laboratory Trace Element Accelerator Mass Spectrometer. AIP Conference Proceedings 475:668–674.Google Scholar
Longworth, BE, von Reden, KF, Long, P, Roberts, ML. 2015. A high output, large acceptance injector for the NOSAMS Tandetron AMS system. Nuclear Instruments and Methods in Physics Research B 361:211–216.CrossRefGoogle Scholar
Palonen, V, Tikkanen, P. 2015. A novel upgrade to Helsinki AMS: fast switching of isotopes with electrostatic deflectors. Nuclear Instruments and Methods in Physics Research B 361:263–266.Google Scholar
Palonen, V, Tikkanen, T, Keinonen, J. 2010. Using Car4AMS, the Bayesian AMS data analysis code. Radiocarbon 52(3):948–952.CrossRefGoogle Scholar
Tikkanen, P, Palonen, V, Jungner, H, Keinonen, J. 2004. AMS facility at the University of Helsinki. Nuclear Instruments and Methods in Physics Research B 223–224:35–39.CrossRefGoogle Scholar
Watt, GC, Boronkay, S, Smith, AM, Hotchkis, MAC. 2013. The ANSTO Isotope Cycling System. Radiocarbon 55(2):308–318.Google Scholar
Xu, W, McDaniel, FD. 2005. A LabVIEW-based expandable modular control system with a layered structure for a 3MV tandem accelerator. Nuclear Instruments and Methods in Physics Research B 241:890–895.CrossRefGoogle Scholar