Automatic Optimization of AMS with LabView

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

Accelerator mass spectrometry · Detector · Mass spectrometry · Physics · Repeatability · Statistics · Algorithms and Data Compression · Computer Science · Mass Spectrometry Techniques and Applications · Mathematics · Scientific Research and Discoveries

• Using car4ams, the Bayesian AMS Data Analysis Code

  Open Access•Vesa Palonen, P Tikkanen et al.•Radiocarbon•2010

  Add to list

• The ANSTO Isotope Cycling System

  Open Access•G C Watt, S Boronkay et al.•Radiocarbon•2013

  Add to list