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 applications in 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 has been recently proposed in terms of a digital signal processing. In this paper, we applied the clustering method to Ir/Au bilayer TES. This method resulted in almost 10% improvement in the energy resolution. On the other hand, from the point of view of imaging X-ray spectroscopy, we applied the clustering method to pixellated Ir/Au-TES devices. We will show the clustering method which sorts signals by their shapes is also useful for a position resolution.