Journal of Low Temperature Physics

, Volume 184, Issue 1–2, pp 397–404

Processing of X-ray Microcalorimeter Data with Pulse Shape Variation using Principal Component Analysis

  • D. Yan
  • T. Cecil
  • L. Gades
  • C. Jacobsen
  • T. Madden
  • A. Miceli
Article
  • 150 Downloads

Abstract

We present a method using principal component analysis (PCA) to process x-ray pulses with severe shape variation where traditional optimal filter methods fail. We demonstrate that PCA is able to noise-filter and extract energy information from x-ray pulses despite their different shapes. We apply this method to a dataset from an x-ray thermal kinetic inductance detector which has severe pulse shape variation arising from position-dependent absorption.

Keywords

Principal component analysis (PCA) Pulse processing  Shape variance Microcalorimeter 

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • D. Yan
    • 1
    • 2
  • T. Cecil
    • 2
  • L. Gades
    • 2
  • C. Jacobsen
    • 1
    • 2
  • T. Madden
    • 2
  • A. Miceli
    • 2
  1. 1.Northwestern UniversityEvanstonUSA
  2. 2.Advanced Photon Source, Argonne National LaboratoryArgonneUSA

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