Planck 2013 results X. Energetic particle effects: characterization, removal, and simulation

TL;DR

Planck 2013 results X develops a comprehensive, empirically driven framework to detect, classify, and remove high-energy particle impacts on Planck-HFI. By identifying three glitch families (short, long, slow) and modeling them with multi-exponential templates, the authors implement a ring-by-ring sky estimation with joint-template deglitching, significantly reducing glitch-induced noise while preserving the sky signal. Realistic simulations show residual glitches contribute well below the instrumental noise and introduce negligible bias ($<5\times10^{-4}$) in the CMB power spectrum for the scales of interest, validating the approach. The work also characterizes the physical origins of glitches—mainly Galactic cosmic rays hitting the Si die and absorber grid—quantifies their temporal behavior, cross-talk, solar-flare effects, and high-coincidence events, and demonstrates robust error budgets for cosmological analyses.

Abstract

We describe the detection, interpretation, and removal of the signal resulting from interactions of high energy particles with the \Planck\ High Frequency Instrument (HFI). There are two types of interactions: heating of the 0.1\,K bolometer plate; and glitches in each detector time stream. The transient responses to detector glitch shapes are not simple single-pole exponential decays and fall into three families. The glitch shape for each family has been characterized empirically in flight data and these shapes have been used to remove glitches from the detector time streams. The spectrum of the count rate per unit energy is computed for each family and a correspondence is made to the location on the detector of the particle hit. Most of the detected glitches are from Galactic protons incident on the die frame supporting the micro-machined bolometric detectors. In the \Planck\ orbit at L2, the particle flux is around $5\,{\rm cm}^{-2}\,{\rm s}^{-1}$ and is dominated by protons incident on the spacecraft with energy $>$39\,MeV, at a rate of typically one event per second per detector. Different categories of glitches have different signatures in the time stream. Two of the glitch types have a low amplitude component that decays over nearly 1\,s. This component produces excess noise if not properly removed from the time-ordered data. We have used a glitch detection and subtraction method based on the joint fit of population templates. The application of this novel glitch subtraction method removes excess noise from the time streams. Using realistic simulations, we find that this method does not introduce signal bias into the \Planck\ data.

Figures (30)

• Figure 1: Top left and right: Completed multimode maffei2010 545 GHz and single-mode 143 GHz SWB bolometer modules. Middle: An exploded view of the assembly of a PSB (showing the definition of the "a" and "b" detectors of the pair). Alignment pins, shown in solid black, fix the aft and fore bolometer assemblies to an angular precision of $<0.1^\circ$. The SWB assembly is similar to the PSB aft bolometer assembly and does not include a feedhorn aperture integrated with the module package. Bottom: PSB pair epoxied in the module parts prior to mating. To the right, the feedhorn aperture can be seen through the fore bolometer in the housing. To the left, the quarter-wave backshort can be seen through the aft bolometer absorber mesh.
• Figure 2: Examples of three distinct families of glitch transfer functions for a typical PSB-a bolometer. Events like the blue curves are called "short" events, those like the black curves are called "long," and those like the red curves are called "slow." Typical variation of the shape within each family is shown for short and long glitches. The differences between long glitch shapes are modelled by a single nonlinearity parameter relating the amplitude of the slow tail of events with their peak amplitude. There is no apparent glitch tail associated with short events.
• Figure 3: Black: Segment of raw data for one detector at 143 GHz before any deglitching; an estimate of the sky signal has been subtracted. Red: A time stream reconstructed from the estimated templates of long glitches with the method presented in Sect. \ref{['sec:method']}. We have chosen a region in the vicinity of a large event. Data that are flagged for the analysis are indicated by the lines at the bottom of the figure. Notice the high level of confusion between long glitch signals.
• Figure 4: Short glitch templates for all detectors obtained using the method discussed in Sect. \ref{['templates']}. Blue lines are for PSB-a, green for PSB-b, and magenta for SWB (see Fig. \ref{['typeGL']} for the definition of the "a" and "b" bolometers in a PSB pair). One sample corresponds to 5 ms.
• Figure 5: Parameters of the glitch templates built from the sum of four decaying exponentials for long glitches and three exponentials for short glitches. Fitted amplitudes versus time constants for all exponentials are displayed for all bolometers. Stars indicate short glitches and circles indicate long glitches. The type of bolometer is indicated by colour (blue is PSB-a, green is PSB-b, and magenta is SWB). Values plotted are obtained after fitting exponentials on templates estimated by stacking a large number of events and normalized to one at the peak. A three-point filter was applied to the data prior to the fit of the exponentials (see text).