Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses

  • J. W. Fowler
  • C. G. Pappas
  • B. K. Alpert
  • W. B. Doriese
  • G. C. O’Neil
  • J. N. Ullom
  • D. S. Swetz
Article
  • 17 Downloads

Abstract

We consider how to analyze microcalorimeter pulses for quantities that are nonlinear in the data, while preserving the signal-to-noise advantages of linear optimal filtering. We successfully apply our chosen approach to compute the electrothermal feedback energy deficit (the “Joule energy”) of a pulse, which has been proposed as a linear estimator of the deposited photon energy.

Keywords

Microcalorimeters X-ray pulses Pulse analysis 

Notes

Acknowledgements

This work was supported by NIST’s Innovations in Measurement Science program and by NASA SAT NNG16PT18I, “Enabling and enhancing technologies for a demonstration model of the Athena X-IFU.” C.G.P. is supported by a National Research Council Post-Doctoral Fellowship. The contribution of NIST is not subject to copyright.

References

  1. 1.
    J.W. Fowler, B.K. Alpert, W.B. Doriese et al., J. Low Temp. Phys. 184, 374–381 (2016).  https://doi.org/10.1007/s10909-015-1380-0 ADSCrossRefGoogle Scholar
  2. 2.
    B.K. Alpert, R.D. Horansky, D.A. Bennett et al., Rev. Sci. Instrum. 84, 6107 (2013).  https://doi.org/10.1063/1.4806802 CrossRefGoogle Scholar
  3. 3.
    S.J. Smith, Nucl. Instrum. Methods Phys. Res. A 602, 537–544 (2009).  https://doi.org/10.1016/j.nima.2009.01.158 ADSCrossRefGoogle Scholar
  4. 4.
    D.J. Fixsen, S.H. Moseley, T. Gerrits, A.E. Lita, S.W. Nam, J. Low Temp. Phys. 176, 16–26 (2014).  https://doi.org/10.1007/s10909-014-1149-x ADSCrossRefGoogle Scholar
  5. 5.
    B. Shank, J.J. Yen, B. Cabrera et al., AIP Adv. 4, 117106 (2014).  https://doi.org/10.1063/1.4901291 ADSCrossRefGoogle Scholar
  6. 6.
    S.E. Busch, J.S. Adams, S.R. Bandler et al., J. Low Temp. Phys. 184, 382–388 (2016).  https://doi.org/10.1007/s10909-015-1357-z ADSCrossRefGoogle Scholar
  7. 7.
    D. Yan, T. Cecil, L. Gades et al., J. Low Temp. Phys. 184, 397–404 (2016).  https://doi.org/10.1007/s10909-016-1480-5 ADSCrossRefGoogle Scholar
  8. 8.
    J.W. Fowler, B.K. Alpert, W.B. Doriese et al., IEEE Trans. Appl. Supercond. 27, 2500404 (2017).  https://doi.org/10.1109/TASC.2016.2637359 CrossRefGoogle Scholar
  9. 9.
    S.R. Bandler, E. Figueroa-Feliciano, N. Iyomoto et al., Nucl. Instrum. Methods Phys. Res. A 559, 817–819 (2006).  https://doi.org/10.1016/j.nima.2005.12.149 ADSCrossRefGoogle Scholar
  10. 10.
    S.J. Lee, J.S. Adams, S.R. Bandler et al., Appl. Phys. Lett. 107, 223503 (2015).  https://doi.org/10.1063/1.4936793 ADSCrossRefGoogle Scholar
  11. 11.
    P. Peille, M.T. Ceballos, B. Cobo et al., SPIE Astron. Telesc. Instrum. 9905, 99055W-1 (2016).  https://doi.org/10.1117/12.2232011 ADSGoogle Scholar
  12. 12.
    C.G. Pappas, J.W. Fowler, D.A. Bennett et al., J. Low Temp. Phys. (in preparation)Google Scholar
  13. 13.
    K.D. Irwin, G.C. Hilton, Cryogenic Particle Detection (Springer, Heidelberg, 2005), pp. 63–150.  https://doi.org/10.1007/b12169 Google Scholar
  14. 14.
    J.W. Fowler, B.K. Alpert, W.B. Doriese et al., Astrophys. J. Suppl. 219, 35 (2015).  https://doi.org/10.1088/0067-0049/219/2/35 ADSCrossRefGoogle Scholar
  15. 15.
    J.W. Fowler, B.K. Alpert, D.A. Bennett et al., Metrologia 54, 494 (2017).  https://doi.org/10.1088/1681-7575/aa722f ADSCrossRefGoogle Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2018

Authors and Affiliations

  • J. W. Fowler
    • 1
  • C. G. Pappas
    • 1
  • B. K. Alpert
    • 1
  • W. B. Doriese
    • 1
  • G. C. O’Neil
    • 1
  • J. N. Ullom
    • 1
  • D. S. Swetz
    • 1
  1. 1.Quantum Sensors GroupNIST Boulder LaboratoriesBoulderUSA

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