Abstract
The analysis of data from X-ray microcalorimeters requires great care; their excellent intrinsic energy resolution cannot usually be achieved in practice without a statistically near-optimal pulse analysis and corrections for important systematic errors. We describe the essential parts of a pulse-analysis pipeline for data from X-ray microcalorimeters, including steps taken to reduce systematic gain variation and the unwelcome dependence of filtered pulse heights on the exact pulse-arrival time. We find these steps collectively to be essential tools for getting the best results from a microcalorimeter-based X-ray spectrometer.
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Notes
\(10^4\) or \(10^5\) pulses should easily suffice for selecting \(\alpha \).
Naturally, this principle is easier to use when some or all data appear in a few narrow lines.
The bin size should be somewhat smaller than the resolution.
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Acknowledgments
The NIST Innovations in Measurement Science and the NASA Strategic Astrophysics Technology programs supported this work. JWF was supported by an American Recovery and Reinvestment Act fellowship. We thank Harvey Moseley, Simon Bandler, and Dale Fixsen for many discussions of pulse analysis.
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Fowler, J.W., Alpert, B.K., Doriese, W.B. et al. The Practice of Pulse Processing. J Low Temp Phys 184, 374–381 (2016). https://doi.org/10.1007/s10909-015-1380-0
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DOI: https://doi.org/10.1007/s10909-015-1380-0