Digital signal processing based on a clustering algorithm for Ir/Au TES microcalorimeter

In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction met...

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Bibliographic Details
Published in:IEEE transactions on nuclear science 2006-02, Vol.53 (1), p.259-264
Main Authors: Zen, N., Kunieda, Y., Takahashi, H., Hiramoto, K., Nakazawa, M., Fukuda, D., Ukibe, M., Ohkubo, M.
Format: Article
Language:English
Subjects:
Clustering
Clustering algorithms
Clustering methods
Cryogenics
Digital signal processing
Energy resolution
Gold
Iridium
Microcalorimeters
Optical imaging
Signal processing algorithms
Spectroscopy
Superconductivity
X-ray imaging
X-rays
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Summary:In recent years, cryogenic microcalorimeters using their superconducting transition edge have been under development for possible application to the research for astronomical X-ray observations. To improve the energy resolution of superconducting transition edge sensors (TES), several correction methods have been developed. Among them, a clustering method based on digital signal processing has recently been proposed. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost a 10% improvement in the energy resolution. Conversely, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will thus show how a clustering method which sorts signals by their shapes is also useful for position identification
ISSN:0018-9499
1558-1578
DOI:10.1109/TNS.2006.869824