No abstract

Transition-edge sensors (TESs) as microcalorimeters offer high resolving power, owning to their sharp response and low operating temperature. In the hard X-ray regime and above, the demand for high quantum-efficiency requires the use of absorbers. Bismuth (Bi), owing to its low heat carrier density and high X-ray stopping power, has been widely used as an absorber material for TESs. However, distinct spectral responses have been observed for Bi absorbers deposited via evaporation versus electroplating. Evaporated Bi absorbers are widely observed to have a non-Gaussian tail on the low energy side of measured spectra. In this study, we fabricated Bi absorbers via these two methods, and performed microstructure analysis using scanning electron microscopy (SEM) and X-ray diffraction microscopy. The two types of material showed the same crystallographic structure, but the grain size of the evaporated Bi was about 40 times smaller than that of the electroplated Bi. This distinction in grain size is likely to be the cause of their different spectral responses.

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.