Detecting and Correcting Gain Jumps in TES Microcalorimeters

Arrays of microcalorimeters based on transition-edge sensors (TESs) are being actively deployed to laboratories all over the world. A TES microcalorimeter array produces very large quantities of data and users of these devices have varying levels of experience, so it is important to provide robust software for data acquisition and analysis that can function with minimal user supervision. This software should be capable of addressing common phenomena that can adversely affect spectrum quality. Gain jumping is one such phenomenon that is characterized by abrupt changes in the gain of a device. Left unaddressed, gain jumps can degrade spectra by introducing false peaks. We are not aware of any previously published methods for resetting gain jumps during data acquisition or existing algorithms for correcting data that is degraded by gain jumps. We have developed automated methods for detecting and correcting gain jumps in gamma-ray TES microcalorimeters. We present a procedure for resetting gain jumps during a live data acquisition that involves briefly driving the TES into its normal state using the bias current. We also describe an algorithm for locating gain jumps and identifying unique gain states within existing microcalorimeter data. Finally, we provide a possible approach for correcting gain jumps after they have been identified.

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Publication Details

Journal
IEEE Transactions on Applied Superconductivity
Published
2024-12-16
DOI
https://doi.org/10.1109/tasc.2024.3517565
Primary Topic
Superconducting and THz Device Technology
Type
article
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article

Detecting and Correcting Gain Jumps in TES Microcalorimeters

Daniel Becker, Daniel S. Swetz, Mark W. Keller, Joel N. Ullom et al.
3 links
IEEE Transactions on Applied Superconductivity
Superconducting and THz Device Technology
article

Detecting and Correcting Gain Jumps in TES Microcalorimeters

Daniel Becker, Daniel S. Swetz, Mark W. Keller, Joel N. Ullom, Thomas A. Baker, Joseph W. Fowler
article en

Abstract

Arrays of microcalorimeters based on transition-edge sensors (TESs) are being actively deployed to laboratories all over the world. A TES microcalorimeter array produces very large quantities of data and users of these devices have varying levels of experience, so it is important to provide robust software for data acquisition and analysis that can function with minimal user supervision. This software should be capable of addressing common phenomena that can adversely affect spectrum quality. Gain jumping is one such phenomenon that is characterized by abrupt changes in the gain of a device. Left unaddressed, gain jumps can degrade spectra by introducing false peaks. We are not aware of any previously published methods for resetting gain jumps during data acquisition or existing algorithms for correcting data that is degraded by gain jumps. We have developed automated methods for detecting and correcting gain jumps in gamma-ray TES microcalorimeters. We present a procedure for resetting gain jumps during a live data acquisition that involves briefly driving the TES into its normal state using the bias current. We also describe an algorithm for locating gain jumps and identifying unique gain states within existing microcalorimeter data. Finally, we provide a possible approach for correcting gain jumps after they have been identified.

IEEE Transactions on Applied SuperconductivityVol. 35(5)
National Institute of Standards and Technology (US), University of Colorado Boulder (US)
Openalex Percentile: Top 83%
Superconducting and THz Device Technology
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