Processing of X-ray Microcalorimeter Data with Pulse Shape Variation using Principal Component Analysis

Yan, Daikang; Cecil, T.; Gades, L.; Jacobsen, Chris; Madden, Timothy J.; Miceli, Antonino

doi:10.1007/s10909-016-1480-5

Cited by 12 publications

(9 citation statements)

References 6 publications

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“…To tackle this issue, a new processing technique based on Principal Component Analysis was also proposed which showed promising results for narrow band studies. 23,24 Its application to continuum spectra using an automated calibration process however needs to be investigated.…”

Section: Discussionmentioning

confidence: 99%

Performance assessment of different pulse reconstruction algorithms for the ATHENA X-ray Integral Field Unit

Peille¹,

Ceballos

Cobo

et al. 2016

SPIE Proceedings

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The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.

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Section: Discussionmentioning

confidence: 99%

Performance assessment of different pulse reconstruction algorithms for the ATHENA X-ray Integral Field Unit

Peille¹,

Ceballos

Cobo

et al. 2016

SPIE Proceedings

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“…20,21 However, r (t; ξ) and C(t, t ; ξ) can be challenging to construct as continuous functions of their parameters. Generative physical models, 22,23 principal component analyses, 7,24 and template interpolation 25,26 have been suggested as ways to properly formulate these functions. However, minimizing equation 6 then becomes a nonlinear optimization problem which cannot be solved in real-time.…”

Section: Photon Energy Estimationmentioning

confidence: 99%

“…A photon's energy, then, can be extracted from the overall size of the signal. These types of MKIDs are called single photon counting, and examples of them include lumped element optical to near-IR detectors, [2][3][4][5][6] X-ray thermal kinetic inductance detectors, [7][8][9][10] and position dependent strip detectors. 11,12 The properties of an MKID are encoded in the forward scattering matrix element, S 21 , of the resonator.…”

Section: Introductionmentioning

confidence: 99%

Improving the dynamic range of single photon counting kinetic inductance detectors

Zobrist,

Klimovich,

Eom

et al. 2020

Preprint

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We develop a simple coordinate transformation which can be employed to compensate for the nonlinearity introduced by a Microwave Kinetic Inductance Detector's (MKID) homodyne readout scheme. This coordinate system is compared to the canonically used polar coordinates and is shown to improve the performance of the filtering method often used to estimate a photon's energy. For a detector where the coordinate nonlinearity is primarily responsible for limiting its resolving power, this technique leads to increased dynamic range, which we show by applying the transformation to data from a hafnium MKID designed to be sensitive to photons with wavelengths in the 800 to 1300 nm range. The new coordinates allow the detector to resolve photons with wavelengths down to 400 nm, raising the resolving power at that wavelength from 6.8 to 17.

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“…1 Optimal filtering estimates pulse sizes well but does not address the problem that pulse size is not proportional to pulse energy. Extensive effort has been devoted in recent years to generalize optimal filtering when a range of pulse shapes must be accommodated 3,4,5,6,7,8 or to apply it to a time-series such as TES resistance for improved energy linearity. 9,10,11 In a companion paper, 12 we explore a nonlinear transformation of the data which we call the Joule energy of a pulse, also known as the electrothermal feedback energy.…”

Section: Tes Resistance R(t)mentioning

confidence: 99%

Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses

et al. 2018

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Processing of X-ray Microcalorimeter Data with Pulse Shape Variation using Principal Component Analysis

Cited by 12 publications

References 6 publications

Performance assessment of different pulse reconstruction algorithms for the ATHENA X-ray Integral Field Unit

Performance assessment of different pulse reconstruction algorithms for the ATHENA X-ray Integral Field Unit

Improving the dynamic range of single photon counting kinetic inductance detectors

Approaches to the Optimal Nonlinear Analysis of Microcalorimeter Pulses

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