Characterization of the Particle-induced Background of XMM-Newton EPIC-pn: Short- and Long-term Variability

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Published 2020 February 27 © 2020. The American Astronomical Society. All rights reserved.
, , Citation Esra Bulbul et al 2020 ApJ 891 13 DOI 10.3847/1538-4357/ab698a

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0004-637X/891/1/13

Abstract

The particle-induced background of X-ray observatories is produced by galactic cosmic ray (GCR) primary protons, electrons, and He ions. Events due to direct interaction with the detector are usually removed by onboard processing. The interactions of these primary particles with the detector environment produce secondary particles that mimic X-ray events from celestial sources, and are much more difficult to identify. The filter-wheel closed data from the XMM-Newton EPIC-pn camera in small window mode (SWM) contains both the X-ray-like background events, and the events due to direct interactions with the primary particles. From this data, we demonstrate that X-ray-like background events are spatially correlated with the primary particle interaction. This result can be used to further characterize and reduce the non-X-ray background in silicon-based X-ray detectors in current and future missions. We also show that spectrum and pattern fractions of secondary particle events are different from those produced by cosmic X-rays.

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1. Introduction

X-ray studies of the assembly processes of extended large-scale structures, constraints on cosmology and the nature of dark matter, and studies of the cosmic X-ray background (CXB) that holds clues about the formation of the first black holes are among the primary science goals of current (e.g., Chandra, XMM-Newton, and Spectrum-RG (SRG)) and future X-ray telescopes (Athena, Lynx; Nandra et al. 2013; Gaskin et al. 2019). These measurements are sensitive to the level of the total flux and related systematic uncertainties of the instrumental X-ray background. Understanding, accurately characterizing, and reducing the absolute level of this X-ray background are fundamental to the X-ray analysis of faint X-ray sources and deep surveys.

The X-ray background can be classified into two major components: the CXB and particle-induced non-X-ray background (NXB). The CXB is dominated by three main components: the Galactic local foreground, solar wind charge exchange emission, and unresolved X-ray emission by distant celestial sources. At lower energies (<1 keV) the dominant component is thermal emission from the Galactic Halo contributing at intermediate and high Galactic latitudes (Burrows & Mendenhall 1991; Snowden et al. 1991; Lumb et al. 2002; Warwick 2002) and the Local Hot Bubble, a region of hot plasma (T ∼ 106 K) mostly filling the local cavity extending 100 pc away from the Sun (Snowden et al. 1998). Another component, which is composed of C vi, O vii, O viii, Ne ix, and Mg xi line emission at lower energies (<1 keV), is the solar wind charge exchange produced when highly charged solar wind ions interact with neutral atoms in the solar system (Robertson & Cravens 2003; Koutroumpa et al. 2006). Unresolved X-ray emission from distant astrophysical sources, e.g., active galactic nuclei, contributes a power-law continuum spectrum that dominates at higher energies (>1 keV) with a possible change in slope at lower energies and has been extensively studied in the literature, e.g., Lumb et al. (2002), Moretti et al. (2009). The magnitude of this component varies with position on the sky and it clearly suffers from cosmic variance (Hickox & Markevitch 2007). If an observation is deep enough to resolve the brightest sources (e.g., the strong shot noise), the residual contribution reaches to the expected cosmic variance given the Log N–log S relation (see for example Figure 9 in Moretti et al. 2009 and discussion therein).

The non-X-ray background due to particles in missions operating above the Earth's magnetic belts consists of two major background components: soft protons focused by the mirrors onto the focal plane and particle-induced instrumental background. Soft protons that are generated in the solar corona and in the Earth's magnetosphere with energies less than a few 100 keV can follow the optical path through the telescope and be focused onto the detectors. The spectral shape of this component can be described by a power-law continuum with highly variable magnitude and slope (Kuntz & Snowden 2008). When present, soft protons can increase the total background intensity by three orders of magnitude on short timescales of 10–104 s (Kuntz & Snowden 2008). They deposit most of their energy near the surface of the detector and produce valid event patterns (Gastaldello et al. 2017).

On the other hand, the unfocused particle-induced internal detector background is generated by energetic Galactic Cosmic Ray (GCR) primaries with energies from several tens of MeV to several GeV. GCR particles consisting of protons, electrons, and He ions are subject to variations over the solar cycle. These incoming particles interact with the detector and produce secondary particles. The interactions constitute the major components of the unfocused portion of the particle-induced instrumental background (Kuntz & Snowden 2008; Snowden et al. 2008; von Kienlin et al. 2018). Based on their high total energies or the pattern of pixels excited in the event, particle events generated by primary GCRs are mostly discarded on board by the event processing (e.g., by the Minimum Ionizing Particle, minimum ionizing particle (MIP), rejection algorithm for XMM-Newton) to prevent them from saturating the limited bandwidth for telemetry (Lumb et al. 2002). However, the secondary electrons and photons due to this unfocused component deposit charge in the detector that it is challenging to distinguish from X-ray events from celestial sources and thus contribute significantly to (and often dominate) the quiescent instrumental background.

Quantifying the particle-induced instrumental background of X-ray observatories is not a trivial process and needs careful examination of observations while the detector is not exposed to sky. The XMM-Newton observatory, carrying two types of silicon-based X-ray detectors on board, the European Photon Imaging Camera (EPIC) MOS (Turner et al. 2001) and the EPIC-pn (Strüder et al. 2001), provides an excellent opportunity to explore the instrumental background of silicon-based X-ray detectors. The unexposed corners of the XMM-Newton EPIC MOS detector that are masked off and the MOS data obtained when the filter wheel is in the closed position (FWC data) serve as estimators of the particle background for each observation that are used in the X-ray analysis of faint extended sources (De Luca & Molendi 2004; Kuntz & Snowden 2008; Gastaldello et al. 2017). The particle background of XMM-Newton EPIC-pn is difficult to predict and eliminate due to the fact that the unexposed region on the detector is small, i.e., statistics on the background level is limited.

In this paper, we examine the long-term variability of the unfocused EPIC-pn background. We present results from an analysis of all archival EPIC-pn data in the small window mode (SWM) with the filter-wheel closed and MIP rejection disabled. The filter-wheel closed observations with 1.05 mm of Al shielding do not allow any photons from celestial sources or soft protons to reach the focal plane. Additionally, all of the pixel data from both valid events and normally rejected particle tracks (GCR primaries) are telemetered to the ground in SWM mode observations. This setup provides a unique opportunity to quantitatively investigate the relationship between the energetic primaries (i.e., GCRs) and the secondaries that mimic X-rays from celestial sources which constitute the dominant component of the instrumental background. We describe our sample and data analysis methods in Section 2. Our results for the XMM-Newton EPIC-pn SWM observations are described in Section 3. Our conclusions are given in Section 4.

This work was originally performed as part of a program to develop algorithms for improved background characterization and reduction for the Athena Wide-Field Imager (WFI) Science Products Module (SPM) (Bulbul et al. 2018; Burrows et al. 2018; Grant et al. 2018). One of the goals of the SPM would have been to use the full data stream from the WFI, not just the ground science event data available to the observer, to reduce the instrumental background. In an effort to better understand the instrumental background in X-ray observatories, we examined the XMM-Newton EPIC-pn SWM data as described in this paper and modeled the WFI background using the GEANT4 software (Tenzer et al. 2010). The latter modeling was done using the measured particle background at the Athena orbit (L2) with a mass model of the flight instrument (von Kienlin et al. 2018). Results from this study will be presented in a separate publication (E. D. Miller et al. 2019, in preparation).

2. XMM-Newton EPIC-pn Data Analysis

2.1. Filter-wheel Closed Slew and Pointed Observations

The EPIC-pn CCD camera is one of the primary instruments on on board XMM-Newton, with a collecting area of ∼2500 cm2 at 1 keV and a 27farcm2 by 26farcm2 field of view over the broad energy range of 0.1 keV to 12 keV (Strüder et al. 2001). The XMM-Newton EPIC-pn data used in this work were taken during slews when the filter wheel was closed and performed in the SWM. In this mode, a 63 pixel by 64 pixel (4farcm3 by 4farcm4) region on detector CCD4 is active and the readout time is 5.67 ms, roughly a factor of 13 faster than the full-frame readout time of the primary science observing mode (full-frame mode). A total of 309 observations have been completed since 2007 between revolutions 1360–3217, with typical exposures of 3–7 ks, adding up to a total exposure time of 1 Ms. The observation IDs and exposure times of the slew FWC observations are given in Table 4 in the Appendix.

FWC observations are performed with 1.05 mm aluminum shielding, preventing low-energy soft protons and X-rays from celestial sources from reaching the EPIC-pn detector. Thus, FWC exposures contain only the particle-induced internal detector background, generated as a result of interactions of energetic GCRs (E > 100 MeV) with the material surrounding the EPIC-pn camera. Additionally, in the observations taken in the SWM setup, the standard MIP rejection algorithm, which identifies and automatically eliminates the pixels above a certain energy threshold and invalid patterns identified on board from the telemetered data, is inactive. As a result, these observations represent an ideal data set to characterize the long-term behavior of the XMM-Newton EPIC-pn internal background, as the ground observer has full access to all pixels above a threshold set by the ground observer. The data consist of electronic readout noise (at lowest energies, hot pixels, columns, and readout noise), primary high-energy GCRs, secondaries generated by high-energy galactic cosmic rays, and particle-induced X-rays (continuum and fluorescent lines, von Kienlin et al. 2018).

The SWM frame time is sufficiently short in a sufficiently small readout area that the particle rate is much smaller than the frame rate. We thus have the unique opportunity to associate the normally rejected charged-particle events with the valid events that comprise the instrumental background. Since these observations are mostly dominated by the unfocused X-ray background, we use the term NXB for these FWC slew observations hereafter.

For a comparison, we also examine the pointed XMM-Newton EPIC-pn SWM observations from two celestial sources: observations of the AB Doradus star system with the closed and thick filters, and a supernova remnant G21.5−0.9 (SNR 21.5−09, hereafter) performed with the thin filter. The details of these observations are given in Table 5 in the Appendix. The AB Doradus observations with the closed filter are not expected to include any source photons (NXB dominated), while the observation with the thick filter is expected to be dominated by soft protons. SNR 21.5−09 observations, on the other hand, are dominated by photons from the supernova remnant in the FOV in the 2–7 keV band, while the contribution from the non-X-ray background is subdominant. These pointed observations, taken in the SWM setup, are similarly telemetered to the ground with the "onboard" MIP rejection algorithm inactive, thus including all pixels above the energy threshold. Having a longer uninterrupted exposure time, these data provide information on short term variability of the unfocused X-ray background.

2.2. Data Reduction and Analysis

We first run the standard the Science Analysis Software (SAS) algorithm epchain to eliminate hot pixels and columns from the data and to form event lists for single exposures and for a given list of CCDs from the relevant observation data files (Gabriel et al. 2004). We note that a non-standard parameter setting is selected in the epchain runs to switch off the "on-ground" MIP rejection. We then construct individual frames from the event files using the frame rate of 5.67 ms. The total number of frames constructed is given in Table 4 in the Appendix. We examined a total of ∼1.86 × 108 frames in the XMM-Newton EPIC-pn slew observations in this work. These observations span 10 yr covering a full solar cycle.

After the construction of frames, we run an image segmentation algorithm on each frame to identify the independent event islands. This algorithm finds connected pixels and traces the long charge tracks of the energetic particle interactions. The charge of each event island is determined by the total charge enclosed in that particular event island. The centroids of these event islands are defined by the maximally charged pixel. We then assign a pattern ID by the pattern detection algorithm, i.e., epchain, to each event island. We note that this image segmentation algorithm developed by our team, is not the same algorithm used by the onboard software.

The standard XMM-Newton EPIC-pn event processing flags event islands with pattern ID ≤ 12 as valid events, while particle events are marked with pattern IDs >12.11 The pattern ID is related to the number and pattern of the CCD pixels triggered for an X-ray event above a certain threshold. The pattern IDs with 0 mark valid single pixel events, double pixel events are marked with pattern IDs 1–4, while triple and quadruple events have pattern IDs of 5–8 and 8–12, respectively. We note that in this FWC data set, the valid events are dominated by secondary particles that are produced by interactions of primary GCRs with the surroundings of the instrument. This component is mostly composed of secondary electrons and photons that deposit their energy in the active volume of the detector. The contributing secondary electrons are generated in ionization processes, while the secondary photons are mainly generated in bremsstrahlung and inelastic scattering processes (see von Kienlin et al. 2018 for more detail). In this work, we only consider valid events in the 2–7 keV energy band to avoid low-energy detector noise, unless otherwise noted. The event islands marked with pattern IDs >12 are mostly the incoming background GCR particles (∼200 MeV–GeV), and Supra-thermal Ions, mostly protons, accelerated in the Heliosphere to energies up to <100 keV hitting the detector (von Kienlin et al. 2018). These particle event islands are identified based on their patterns and the total charge encapsulated within the island. For most of these energetic events, there exists more than one pixel with a total charge exceeding the saturation level of the analog-to-digital converter (ADC; corresponding to 22.5 keV when MIP rejection is off). In those cases, the centroid of a particle event island is the maximally charged pixel last read by the image segmentation algorithm.

2.3. Classification of Frames

We next analyze the data sets on a frame-by-frame basis and identify event islands and divide the frames into four categories: frames with just particle tracks (Case A), frames with only valid events (Case B), frames with at least one particle track and at least one valid event (Case C), and frames with no particle tracks or events (Case D). This categorization allow us to examine the frames with particle primaries without a secondary (Case A), secondaries that are created by particle primaries but not detected on the same frame (Case B), and the frames with the primary particle events and their secondaries detected on the same frame (Case C). Figure 1 illustrates the subdivision of frames. We find that overall the total number of Case A frames is 2089948, while 39186 of the frames are in the Case B, and 5175 of the frames are in Case C categories.

Figure 1.

Figure 1. Frames with just particle tracks (Case A), valid events (Case B), and both particle tracks and valid events (Case C) are shown. The circles in red mark the detected primary particle events, while the green circles show the secondary valid events.

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3. Results

In the next subsections, we investigate the spectral properties, light curves, and spatial correlations between valid events and particle tracks in Cases A, B, and C frames in detail.

3.1. Long-term Variability

Investigating the temporal changes in the number of frames, we find that the overwhelming majority of the frames are empty and fall under the Case D category independent of solar cycle or orbit (see Figure 2). We find that overall the total number of Case A frames is 2089948 (1.12% of the total), while 39186 (0.02%) of the frames are Case B, 5175 (0.003%) of the frames are Case C, and the remainder (98.8%) are empty Case D frames (see Table 1). The temporal changes in the fractional A, B, and C frame rates are shown in Figure 2. The clear modulation with solar cycle observed in the fraction of Case A, B, and C frames is consistent with the previously observed modulations in the count rates in unexposed corners of MOS2 detector, EPIC Radiation Monitor on board XMM-Newton (Gastaldello et al. 2017), and Chandra high-energy (12–15 keV) count rate for the ACIS-S3 CCD as a function of year.12 GCR flux is modulated in anti-correlation with solar activity due to the solar wind (Neher & Anderson 1962). While Earth's magnetic field provides a varying degree of geomagnetic shielding from these GCR particles, the level of the modulation depends on the energy of GCRs. The observed modulation on the EPIC-pn data shows that the FWC data are dominated by GCRs.

Figure 2.

Figure 2. Left: the fraction of frames with just primary particle events (red: Case A), just secondary valid events (blue: Case B), and with both valid and particle events (green: Case C) as a function of time. Black curve shows the total rate of particle events. Strong modulation with the solar cycle observed for all the frames indicates that the XMM-Newton EPIC-pn unfocused background is dominated by Galactic cosmic rays. Right: zoom onto Case B and Case C frame to enhance the visibility of the solar modulation cycle.

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Table 1.  Fractions of Frames

Frame Type Number of Frames Percent Fractions
Case A 2089948 1.12
Case B 39186 0.02
Case C 5175 0.003
Case D 184541368 98.8

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3.2. Branching Ratios of Valid Events

Having the largest number of valid events, Case B frames dominate the unfocused background of the XMM-Newton EPIC-pn. We next examine the branching ratios, i.e., the fraction of the patterns of the valid events (singles, doubles, triples, and quadruples) in Case B frames, where only secondary events are detected. We detect a total number of 39190 valid events in non-X-ray background observations (i.e., slew filter-wheel closed observations listed in Table 4 in the Appendix). The fractions of these valid patterns in Case B frames are shown in Table 2. Of the total valid events, 65.6% ± 0.2% of them are singles, 31.3% ± 0.2% are doubles, while 1.47% ± 0.06% and 1.59% ± 0.06% are triples and quadruples, respectively. Comparing these ratios with Case B frames observed in the closed filter AB Doradus observations, of the total 4172 valid events, 65.3% ± 0.7% are singles, 32.1% ± 0.7% are doubles, and triples and quadruples make up 1.0% ± 0.1% and 1.6% ± 0.2% of them, respectively. These pattern fractions are consistent with the ratios observed in the NXB slew observations, indicating that the 2–7 keV energy band of the AB Doradus observations with the filter closed is also dominated by the unfocused background of the XMM-Newton EPIC-pn. Case B frames for the SNR 21.5−09 observations include a total of 170114 valid events and have a lower fraction of singles (61.6% ± 0.1%) and a larger percentage of doubles (34.5% ± 0.1%) is detected compared with the AB Doradus and NXB observations.

Table 2.  Pattern Distribution of Valid Events in Case B and Case C Frames of the Non-X-Ray Background (NXB) Taken in Filter-wheel Closed Setup, AB Doradus Observations in Filter-wheel Closed Setup, and SNR 21.5−09 Observations Performed with Thin Filter

Frames NXB     AB Doradus     SNR 21.5−09  
  Closed Flt.     Closed Flt.     Thin Flt.  
  Case B Case C   Case B Case C   Case B Case C
Singles 65.6 ± 0.2 67.8 ± 0.8   65.3 ± 0.7 69.4 ± 2.6   61.6 ± 0.1 60.7 ± 0.7
Doubles 31.3 ± 0.2 30.1 ± 0.7   32.1 ± 0.7 28.5 ± 2.5   34.5 ± 0.1 35.9 ± 0.7
Triples 1.47 ± 0.06 1.0 ± 0.2   1.0 ± 0.1 1.0 ± 0.6   2.0 ± 0.6 1.7 ± 0.2
Quadruples 1.59 ± 0.06 1.1 ± 0.2   1.6 ± 0.2 1.0 ± 0.6   1.9 ± 0.6 1.6 ± 0.2

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In Case C, frames of the NXB observations, we find a total of 3622 valid events in the 2–7 keV band. The majority of the valid events (67.8% ± 0.8%) are singles, while doubles make up 30.1% ± 0.7 % of the total events. We find that 1.0% ± 0.2% and 1.1% ± 0.2% are triples and quadruples, respectively. Fractions of the valid patterns in Case C frames are shown in Table 2. Examining AB Doradus observations with the closed filter, we find a much lower number of valid events (a total of 322) in the Case C frames compared with Case B frames, consistent with the results we find in NXB observations (see Figure 2). Of these events 69.4% ± 2.6% are singles, 28.5% ± 2.5% are doubles, 1.0% ± 0.6% and 1.0 ± 0.6% of them are triples and quadruples. The branching ratios in this band are consistent with the fractions of valid event patterns observed in the slew NXB SWM data, indicating that the 2–7 keV band of AB Doradus observations is dominated by the EPIC-pn's unfocused X-ray background, as in the Case C frames.

In Case C frames in the SNR 21.9-05 observations (a total of 4663 frames), the fraction of singles is lower (60.7% ± 0.7%), while doubles are higher (35.9% ± 0.7%) compared with both NXB-dominated slew and AB Doradus observations in the source dominated hard band. Sparse statistics of triples and quadruples do not allow us to compare their branching ratios with the unfocused X-ray background. The key result here is that the valid events that make up the instrumental background have slightly different branching ratios to celestial X-rays in the 2–7 keV band. High-energy events with harder spectra have more probability to have high splint event ratios compared with the low-energy photons with soft spectrum. As SNR 21.9-05 has a harder spectrum, the split event ratios are expected to be higher than the split event ratios in the non-X-ray background.

3.3. Time Interval between Valid Events

We further investigate whether there is a temporal correlation between the arrival times of valid events. The distribution of the arrival times of successive events in Case B frames in the 2–7 keV energy band is shown in Figure 3. If the valid events are independent of each other, the distribution is expected to be exponential, with a time constant close to the mean time between events (the reciprocal of the mean rate of Case B frames). We find that the mean difference in the arrival times of the valid events in Case B frames is 26.7 s, which is comparable to the time constant of the exponential distribution. There is no evidence of a characteristic time interval between events shorter than the mean time interval. This also confirms that the 2–7 keV band is dominated by the unfocused background and that our filtering has removed most of the instrumental artifacts associated with the long reset time constant of the output amplifiers (Freyberg et al. 2004). We do not find any significant departures from expectations in the arrival time of valid events depending on the particle environment.

Figure 3.

Figure 3. Distribution of the time intervals between valid events in Case B frames showing the exponential form expected for uncorrelated events. The exponential time constant is equal to the mean time between Case B events.

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3.4. Spectral Properties of Valid and Particle Events

We first extract spectra of all valid events based on their patterns in Case B frames (see Figure 4). Overall the spectra of singles and doubles are quite flat, while the spectra of triples and doubles are slightly positively sloped toward higher energies. Additionally, we removed events that are located at the detector boundaries, as it is challenging to determine if the event detected at the boundary is a single pixel event or is the partially collected charge of an event that landed off the active area of the detector.

Figure 4.

Figure 4. Pulse–height spectra of valid events (single-pixel events in red, doubles in blue, triples in green, and quadruples in purple) in Case B frames observed in the XMM-Newton EPIC-pn filter-wheel closed observations. Fluorescent instrumental lines of Si Kα (1.75 keV), Ti Kα (4.5 keV), Cr Kα (5.4 keV), Cu Kα (8.0 keV), and Zn Kα (8.6 keV) are visible in the spectra.

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Next, we investigate the spectral properties of the particle tracks in Case A and Case C frames. The total energy of particle tracks is obtained by summing the charge in spatially connected pixels found by our image segmentation algorithm. We then generate the spectra of these particle events and normalize them by the total frames in each observation (as given in Table 4 in the Appendix). The spectra of the particle events are shown in Figure 5. The overwhelming statistical power in Case A frames (see Figure 2) allows us to examine particle spectra in different phases of the solar cycle: the observations in the solar activity plateau between 2007 and 2008 (in magenta); 2012 and 2015 (in cyan); decline in solar activity between 2008–2010 (in orange) and 2015–2017 (dark blue); and increase in solar activity between 2010 and 2012 (in green). We then overplot the spectra of particle events in Case C frames from all epochs (2007–2017) in red in Figure 5 with the same bin size of 7 keV. Due to the limited number of Case C frames, we combine all particle events detected between 2007 and 2017. Figure 5 shows spectra of particle events in Case A and Case C frames (left) and the difference between them (right). The spectra of the particle events in Case A frames are strikingly similar to one another and independent of the solar cycle. We find a significant difference between the spectra of particle events that are detected in Case C frames and those detected in Case A frames. We observe a steeper slope in the energy band <200 keV in the Case A spectra, and above >200 keV the Case C spectrum flattens. This may indicate that the particle events that create showers of valid events while passing through the detector housing (in Case C frames) originate from a different particle population or geometry than primary particles detected in Case A frames. The observed flattening of the spectrum of Case C frames above 1.5 MeV is likely due to combination of limited statistics, lack of sensitivity, and ADC saturation limit.

Figure 5.

Figure 5. Left panel: pulse–height spectra of the particle events in Case A frames. The data have been divided into five time intervals to sample the variation of the particle spectra with the solar cycle and normalized by the number of frames in each period. Overplotted in red is the pulse–height spectrum of the particle events in Case C frames between 2007 and 2017. The periodic structure observed at high energies is an aliasing effect due to binning and ADC saturation limit. Flattening of the spectrum of the red (Case C) histogram above ∼200 keV relative to the other histograms (Case A) is clearly visible. Right panel shows the difference between the normalized pulse–height spectra of Case A frames and Case C frames.

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Another implication of Figure 5 is that if the spectra of particle events in the Case B and Case C frames are normalized to the counts in the 250–750 keV energy band, the spectral slopes become consistent between these two spectra. In this case, an excess of low-energy particle events is observed on the Case C frames compared with the Case B frames in the lower-energy band below 200 keV. This may indicate that low-energy particle events are more likely to convert into showers and create secondaries that are detected on the detector.

3.5. Spatial Correlation between Particle and Valid Events

We further examine the distribution of distances between the centroid position of the valid and particle events in Case C frames. In both cases, the centroids of the events are determined by the maximally charged pixels. In the case of the particle event islands, when highly energetic particles interact with the detector, often more than one pixel gets charged at the ADC saturation limits, i.e., 22.5 keV with MIP rejection off. In these cases, the center of the event is marked as the last saturated pixel in an event island to be read. The distribution of distance between particle events and their secondary valid events for the slew NXB observations is shown in blue in Figure 6. The form of the distribution expected for uncorrelated events in these frames is plotted as a dashed yellow curve. The significant excess of event pairs at small separations indicates that the valid events in the immediate <30 pixel area around the particle events are highly spatially correlated with the associated particle track. We note that, due to the small active area of the detector in the SWM observations (63 pixel × 64 pixel), our analysis is not sensitive to correlations at large scales.

Figure 6.

Figure 6. Distribution of distances between valid events in the 2–7 keV energy band and the particle events detected in Case C frames of the NXB with closed filter (in blue), SNR 21.5−09 with thin filter (in black), and AB Doradus with closed filter (in cyan). The dashed curve in yellow indicates the expected distribution for uncorrelated event pairs. Valid events in the immediate ∼30 pixel vicinity of the particle events in NXB and AB Doradus observations are highly correlated, indicating that the 2–7 keV band of these observations are dominated by the unfocused background of XMM-Newton EPIC-pn. Although statistics of Case C frames are limited, an evidence of spatial correlation in small spatial scales (<30 pixels) is visible in the AB Doradus observations on the right panel. The two-point correlation function in the SNR 21.5−09 observations shows a distribution consistent with the theoretical distribution of uncorrelated events, indicating that 2–7 keV band is dominated by the emission from the supernova remnant.

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As a next step, we divide the valid events based on their patterns and reexamine the spatial correlations of singles, doubles, triples, and quadruples. We find a similar correlation between these patterns and particle events, independent of their patterns. We also looked for energy dependence in the correlation between particle tracks and related events by dividing particle events into categories: particles with low energies, <200 keV, and high-energy particles with >200 keV (see Section 3.4). We do not observe any differences in the spatial correlation between valid events and particle tracks as a function of energy of the particle events.

Next, we examine the spatial correlation between valid/particle event pairs observed in Case C frames for the pointed observations through the closed filter of the AB Doradus star system (black distribution in Figure 6). As expected, this histogram is similar to the one for the slew NXB observations (e.g., there is a significant excess at small spatial scales up to 30 pixels) indicating that the 2–7 keV band is dominated by the unfocused X-ray background.

The shape of the spatial correlation between valid events and particle tracks for the SNR 21.5-0.9 data (cyan in Figure 6) is similar to the form expected for uncorrelated events (yellow curve). However, the distribution of separations is more peaked than expected for pairs of randomly distributed events. This is because, although a particle is equally likely to land anywhere on the detector, the supernova is centered on the chip, causing the distribution of source photons to be peaked there. This indicates that the 2–7 keV energy band for the SNR 21.5−09 observations is dominated by photons from the supernova remnant and the unfocused X-ray background is subdominant.

These results are the basis of the self-anticoincidence (SAC) method, used to reduce secondary events associated with a particle primary. This method of partial vetoing of valid events around particle tracks shows promise at reducing the systematic error produced by the instrumental background at the expense of eliminating events from real source X-rays (based on private communication with S. Molendi in 2019). We find that by eliminating events that fall within 30 pixels of the peak of a particle track, the particle-induced background of the XMM-Newton EPIC-pn can be reduced by ∼10% (see Figure 7). The results summarized here from the XMM-Newton EPIC-pn FWC observations can be used to reduce the particle background level of the future silicon-based X-ray detectors. For instance, the earlier EPIC MOS results were used to optimize FWC rotation strategy to sample particle background component during Athena WFI observations of faint objects (Gastaldello et al. 2017; von Kienlin et al. 2018).

Figure 7.

Figure 7. Pulse–height spectrum of valid events detected in Case B and C frames (in red). Rejecting valid events associated with a primary GCR by using SAC with a 30 pixels exclusion radius would reduce the particle-induced background level of the XMM-Newton EPIC-pn by ∼10% in the 2–7 keV energy band. The resulting background spectrum is shown in dashed blue.

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3.6. Short-term Variability of the Particle Environment

Owing to the long-term coverage of the XMM-Newton EPIC-pn slew observations with the filter-wheel closed between years 2007 and 2017, we are able to probe short-term variability of particle events in Case A frames. We examine the light curves of particle events in Case A frames in five epochs defined by the phase of the solar cycle as shown in Figure 2 (plateau in 2007, solar minimum in 2009, increase in solar activity in 2011, solar maximum in 2014, decrease in solar activity in 2016). The variability of the rate of particle events in Case A frames in 10 observations taken close together in time, with 100 s binning, is shown in Figure 8 for each epoch. We note that the observations used in producing light curves in this section differ from the observations used to generate the spectra in Section 3.4. The mean, standard deviation, and skewness of the light curve counts of these particle events are given in Table 3. The dashed curves indicate a normal distribution with Poisson standard deviation. There is no statistically significant variability of the particle tracks in any epoch.

Figure 8.

Figure 8. Light curves of particle events detected in Case A frames per 100 s binning for five different epochs in the solar cycle are shown on the left panels. The dashed lines in the right hand panels show the expected Poisson distributions around the mean. The distributions of count rates of particle events in these observations in each epoch are shown on the right panels.

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Table 3.  Statistics of Light Curves of Particle Event Rates in Case A Frames Binned for 100 s

Date Epoch Mean Std Dev. Skewness KS Test
          D-value p-value
2007 Plateau 238 16 0.01 0.16 0.76
2009 Solar minimum 276 19 0.23 0.13 0.93
2011 Solar activity increase 210 18 0.06 0.10 0.99
2014 Solar maximum 159 14 0.24 0.13 0.93
2016 Solar activity decrease 230 18 −0.01 0.13 0.93
2002 AB Doradus (closed Flt.) 133 12 0.08 0.17 0.76
2004 AB Doradus (closed Flt.) 179 15 −0.82 0.25 0.78
2017 AB Doradus (thick Flt.) 239 15 0.25 0.13 0.94
2017 SNR 21.5−09 (thin Flt.) 239 16 0.05 0.16 0.76

Download table as:  ASCIITypeset image

We find that the mean values of the particle counts vary between 133 and 276, depending on the solar activity (see Table 3); however, the standard deviations (12–19) are remarkably small and independent of solar cycle. The mean of particle event counts observed per 100 s can be as high as 276 during solar minimum, while it can be as low as 133 during solar maximum. In general, each distribution is well matched to the Poisson distribution expected for a constant mean rate (shown in dashed curves). We do not observe significant irregularities or outlier particle events in the light curves.

Similarly, we examine the light curves of particle events in Case A frames of the pointed XMM-Newton EPIC-pn SWM observations of AB Doradus and SNR 21.5−09. The histograms of the light curves are similarly tightly distributed around the mean as observed in NXB observations, close to the expected Poisson distribution. The AB Doradus observations were taken in 2002 and 2004, and the observed mean values are 133 and 179 while the Sun was active. The AB Doradus observations with thick filter were taken in 2017, when the solar activity was approaching its minimum, therefore a mean rate of 239 particle tracks is observed during those observations. These count rates are consistent with the count rates we observe in NXB-dominated slew observations. The SNR 21.5−09 observations were also taken in 2017 while solar activity was approaching minimum. The observed mean value of 239 indicates that these observations were performed when the solar activity was at minimum. Figure 9 shows a comparison of the distributions of particle event counts per 100 s in the Case A frames of AB Dor, SNR 21.5–09 observations perfomed in closed, thick, thin filters.

To further test the similarities in the background light curves against the Poisson distribution, we computed Kolmogorov–Smirnov statistics. The Kolmogorov–Smirnov test determines the probability of two samples being drawn from the same distribution. The high values of probabilities (>0.73) indicate that these background light curves distributions are originating from the same underlying Poisson distribution.

We also show distributions of the number of valid events in the 2–7 keV energy band in Case B frames in Figure 10, binned for longer time intervals (200 s) to allow for the lower event rate. Similarly, we do not observe any significant deviations from Poisson distributions for the numbers of particle related events in the filter-wheel closed data.

Figure 9.

Figure 9. Distribution of particle event counts per 100 s bin obtained from light curves of the pointed observations of the AB Doradus star system taken in two different filter configurations; filter closed and with the thick filter. The observations were taken in 2002, 2004, and 2017. Comparing mean count rates with the count rates observed in NXB data (see Table 3), we can infer that the filter closed observations were taken during solar maximum, while the 2017 observations were performed during solar minimum. The unfocused background level measured in the FWC data and solar activity are closely correlated.

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Figure 10.

Figure 10. Light curves of valid events in 2–7 keV band detected in Case B frames per 200 s binning for five different epochs in the solar cycle are shown on the left panels. The dashed lines in the right hand panels show the expected Poisson distributions around the mean. The distributions of count rates of particle events in these observations in each epoch are shown on the right panels.

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4. Conclusions

In this work, we present analysis of the unfocused X-ray background of the XMM-Newton EPIC-pn operating in SWM with a fast frame time. These observations were taken while XMM-Newton was slewing to a variable source that was to be observed in SWM, while the filter wheel was in the closed position and the MIP rejection algorithm was turned off. This data set uniquely allows us to study temporal, spectral, and spatial properties of particle primaries and their secondaries generated as a result of the interactions with the detector housing, which constitute the unfocused instrumental background for the science observer. We also compare our results from the unfocused background, NXB, with the pointed filter closed observations of a star system AB Doradus and observations of a supernova remnant SN 21.5−09 taken with the thin filter. Owing to the large number of frames, we were able to independently study the frames with just primary particles (Case A), with just secondary valid events (Case B), and with both primary particle and secondary valid events (Case C). Our major results are as follows:

  • 1.  
    Examining the branching ratios of event morphologies, we find that the vast majority of valid events in Case B frames of NXB observations are single-pixel events (65.6% ± 0.2%) and double pixel events (31.3% ± 0.2%). Comparing these ratios with the observations of a supernova remnant, we find that in both cases, Case B frames have a significantly smaller fraction of singles (61.6 ± 0.1), and larger fraction of doubles (34.5% ± 0.1%). The fraction of singles in Case C frames of the unfocused NXB (67.8% ± 0.8%) is also higher compared with that in the supernova observations (60.7% ± 0.7%). In both cases, the differences are statistically significant. That is, the valid events in the instrumental background have somewhat different branching ratios than those of the celestial X-rays.
  • 2.  
    The mean difference between the observed arrival times of successive valid events in Case B frames matches the reciprocal of the event rate, as expected. We do not observe any structure in the distribution of the time intervals suggestive of a temporal correlation between background events, or detector or background effects on the time interval between valid events. As expected, all background events appear to be independent and uncorrelated.
  • 3.  
    The energy spectrum of the particle tracks in frames with valid events is somewhat flatter than that of the tracks in frames with no valid events. This result indicates that the particle events detected with secondary events in the same frame (Case C) might be due to a different population of particles passing through, or a different geometry compared with the primary particle events that do not generate secondary showers in the detector housing. We also found that when the spectra of particle events are normalized to the high-energy band (250–750 keV), an excess of low-energy particle are observed in the Case C frames (frames with at least one primary and secondary particles) compared with the Case B frames (frames with just primaries). This may indicate that low-energy particles are more likely to interact with the detector housing and create secondary particle showers.
  • 4.  
    We find a significant spatial correlation between particle and valid events in Case C frames on small spatial scales up to 30 pixels (4500 μm) of the unfocused background observations with the closed filter in the 2–7 keV band. In the observations of the supernova remnant SNR 21.5−09 no spatial correlation between the valid events and particle events is observed, as expected. Rejecting valid events "self-anticoincidence" or "SAC") within 30 pixels around the primary GCRs reduces the absolute level of the particle-induced background of XMM-Newton EPIC-pn by ∼10% in the 2–7 keV energy band.
  • 5.  
    Light curves of particle events in Case A frames display a tight distribution, with mean particle counts of 133 to 276 per 100 s bin, depending on the phase of the solar cycle. The mean number of particle events per 100 s bin can be as high as 276 during solar minimum, while it can be as low as 133 during solar maximum. The sample standard deviations of the count per 100 s bin are consistent with expectations for Poisson distributions with the observed means. There is no evidence for any short-term temporal variability in the GCR component of the instrumental background, beyond what is expected for Poisson noise. KS test results indeed indicate that the distribution of count rates in the light curves of Case A and Case B frames are consistent with the Poissonian distribution around the mean rate. These means and distributions can be used to monitor particle rates and estimate the level of unfocused background of future X-ray imaging detectors.
  • 6.  
    Light curves of valid events (secondaries generated by primary GCRs) also display a tight distribution around the mean, consistent with the expected Poissonian distribution. Similarly, there is no significant evidence for any short-term temporal variability in the secondary background events. These observed rates closely correlate with the solar cycle and particle rates and can be used to predict the level of unfocused X-ray background.

Similar analyses of the unfocused component of the X-ray detector background have been performed on the Chandra stowed ACIS data and the Neil Gehrels Swift Telescope XRT data (e.g., Bartalucci et al. 2014; Bulbul et al. 2018; Grant et al. 2018). Results presented in this work should help to understand and reduce the particle background level in other Si-based X-ray detectors (e.g., the Wide Field Imager on board Athena and the eROSITA instrument on board the Spectrum Roentgen Gamma observatory). The SWM frame time of 5.67 ms is similar to the Athena WFI default frame, allowing us to validate GEANT4 simulations of the Athena WFI unfocused background (see E. D. Miller et al. 2019, in preparation).

Beyond validating the GEANT4 simulations for the Athena WFI, this study also lays the ground work for application of self-anticoincidence to reduce the unfocused background in silicon-based X-ray detectors, e.g., WFI on board Athena (Nandra et al. 2013), eROSITA on board SRG (Merloni et al. 2012), EPIC on board XMM-Newton (Jansen et al. 2001), and HDXI on board Lynx (Gaskin et al. 2019). The results obtained from this work will be used to develop both onboard and ground-based algorithms to better characterize and improve background rejection for silicon-based X-ray imaging detectors. The self-anticoincidence method, and the results presented in this work, will help reduce the Athena WFI particle background and increase the signal-to-noise in background-dominated observations, such as galaxy cluster outskirts and deep surveys, enhancing the science return of Athena.

The authors thank the anonymous referee for helpful comments on the draft. We gratefully acknowledge support from NASA grant NNX17AB07G, administered by The Pennsylvania State University, and from NASA contracts NAS 8-37716 and NAS 8-38252.

This paper made use of the simulations from GEANT software (Tenzer et al. 2010) and XMM-Newton SAS analysis software (Gabriel et al. 2004). This work made use of SciPy (Jones et al. 2001), matplotlib, a Python library for publication quality graphics (Hunter 2007), Astropy, a community-developed core Python package for Astronomy (Astropy Collaboration et al. 2013), NumPy (Van Der Walt et al. 2011).

Software: GEANT4 (Tenzer et al. 2010), XMM-Newton SAS (Gabriel et al. 2004), Matplotlib (Hunter 2007), NumPy (Van Der Walt et al. 2011), Astropy (Astropy Collaboration et al. 2013), SciPy (Jones et al. 2001).

Appendix: Observations

A summary of filter-wheel closed slew observations, revolution numbers, dates, and exposures are provided in Table 4. The pointed AB Dor, SNR 21.5-09 observations performed in filter-wheel closed setup, and with thick and thin filters are given in Table 5.

Table 4.  XMM-Newton EPIC-pn Small Window Mode Observations Taken in the Filter-wheel Closed Setup during the Slewing Phase

Obs. Obs. ID Revolution Exposure Number of   Obs. Obs. ID Revolution Exposure Number of
Index     (ks) Frames   Index     (ks) Frames
0 9136000003 1360 3.91 690114   155 9213400002 2134 3.4 599994
1 9136100002 1361 2.37 418658   156 9214900004 2149 1.42 249893
2 9136200004 1362 6.42 1132080   157 9217500002 2175 1.85 326346
3 9136500003 1365 4.07 717519   158 9218200004 2182 2.58 454189
4 9137500005 1375 5.65 995629   159 9218300002 2183 2.47 435767
5 9138800003 1388 2.24 395752   160 9219200004 2192 3.13 551326
6 9138900004 1389 4.42 778932   161 9223300002 2233 5.31 935852
7 9139200003 1392 2.86 504355   162 9223700003 2237 2.7 475590
8 9139400002 1394 1.15 201914   163 9225900003 2259 3.18 560297
9 9139500004 1395 4.31 759510   164 9226100002 2261 5.88 1035931
10 9139700002 1397 2.18 383899   165 9226400004 2264 2.63 464485
11 9140100004 1401 1.37 241883   166 9227500006 2275 3.48 614237
12 9141000003 1410 4.08 719023   167 9227600002 2276 2.24 394874
13 9142800004 1428 5.71 1005950   168 9229000002 2290 1.84 324827
14 9143300002 1433 3.71 654472   169 9229600003 2296 1.84 323646
15 9144300004 1443 6.17 1087659   170 9229700003 2297 1.52 267659
16 9144500003 1445 2.97 522981   171 9229900003 2299 1.51 265961
17 9144700003 1447 0.99 175325   172 9230900003 2309 4.29 756196
18 9144900005 1449 1.33 234024   173 9231800002 2318 3.82 673051
19 9145700003 1457 5.2 917470   174 9232100004 2321 6.81 1199982
20 9146300006 1463 3.33 587072   175 9233000003 2330 2.29 403991
21 9147500002 1475 1.88 331127   176 9233200003 2332 3.94 693939
22 9147900002 1479 1.86 327992   177 9233900005 2339 4.44 782505
23 9148000004 1480 1.28 225991   178 9236300002 2363 3.8 669151
24 9148400003 1484 2.5 440018   179 9236600002 2366 5.91 1042100
25 9149500002 1495 4.75 838019   180 9236700002 2367 6.49 1144493
26 9151000002 1510 6.67 1175239   181 9236900002 2369 4.91 865822
27 9151000003 1510 3.59 632906   182 9238200002 2382 5.89 1038778
28 9151300002 1513 5.52 973663   183 9238700004 2387 4.35 766698
29 9151600004 1516 1.98 349686   184 9239400003 2394 3.85 678823
30 9151700002 1517 0.95 168322   185 9240900002 2409 3.38 595051
31 9152300002 1523 2.14 377646   186 9241200002 2412 2.11 371796
32 9152400002 1524 3.32 585622   187 9241500002 2415 5.36 944903
33 9152700003 1527 3.79 667745   188 9241600002 2416 1.11 196163
34 9152900002 1529 3.54 624743   189 9242200003 2422 2.04 359330
35 9153000003 1530 4.17 735806   190 9242700002 2427 2.28 401729
36 9153100004 1531 5.72 1007747   191 9243000003 2430 3.56 628516
37 9153200003 1532 5.31 936525   192 9245700004 2457 2.3 405332
38 9153300002 1533 4.7 827869   193 9247900002 2479 1.03 182172
39 9153400002 1534 3.7 652071   194 9248700002 2487 1.23 216006
40 9153400004 1534 4.92 868326   195 9248900002 2489 2.41 425183
41 9153600002 1536 5.47 964802   196 9248900003 2489 3.63 640579
42 9153600003 1536 6.18 1090252   197 9249100002 2491 6.75 1189397
43 9153900002 1539 1.05 184286   198 9249300002 2493 6.28 1106857
44 9154200004 1542 6.26 1103389   199 9249400002 2494 3.42 603517
45 9154300003 1543 2.9 510531   200 9249500003 2495 6.09 1073205
46 9154400005 1544 3.06 538903   201 9249600002 2496 3.48 614271
47 9154600005 1546 4.39 773231   202 9249700002 2497 3.49 615429
48 9156800003 1568 5.83 1027723   203 9249800002 2498 1.72 302452
49 9158100002 1581 4.66 822194   204 9249900002 2499 4.02 708999
50 9158900004 1589 3.34 589018   205 9252900006 2529 0.98 171979
51 9160000002 1600 3.28 578523   206 9253300003 2533 3.06 540308
52 9160700004 1607 1.44 253915   207 9254400002 2544 1.25 220908
53 9160800004 1608 5.82 1025948   208 9254500004 2545 4.1 723228
54 9160900002 1609 2.95 519505   209 9254600004 2546 4.71 830219
55 9161000002 1610 0.95 167732   210 9256500002 2565 5.84 1028961
56 9161300002 1613 1.08 189574   211 9256600002 2566 4.34 764502
57 9161500004 1615 2.03 358285   212 9257300002 2573 1.56 274811
58 9161600002 1616 6.03 1062547   213 9258700002 2587 4.26 751265
59 9161900002 1619 1.53 268946   214 9258800002 2588 3.16 557816
60 9162100003 1621 3.5 617167   215 9259300002 2593 5.78 1018257
61 9163100002 1631 1.93 341051   216 9261200003 2612 5.39 950948
62 9164900002 1649 2.56 450613   217 9261800002 2618 5.7 1004257
63 9164900003 1649 3.04 536480   218 9262500003 2625 5.94 1046693
64 9165500004 1655 2.32 408867   219 9263300002 2633 1.54 271100
65 9166200003 1662 0.99 175344   220 9264200002 2642 1.24 219011
66 9168100003 1681 1.48 260533   221 9264400003 2644 4.18 737026
67 9169500002 1695 1.39 245523   222 9265000003 2650 5.15 908458
68 9169600003 1696 1.55 273414   223 9265400005 2654 5.74 1012829
69 9169700004 1697 3.36 591780   224 9265500003 2655 2.25 396033
70 9169800002 1698 4.11 725288   225 9266200002 2662 1.57 276761
71 9169900004 1699 4.56 804166   226 9266700002 2667 3.01 531492
72 9170200002 1702 2.06 362767   227 9267800004 2678 4.55 801427
73 9170300002 1703 4.63 816310   228 9268600003 2686 6.46 1139449
74 9170500003 1705 3.97 700703   229 9268900002 2689 5.64 993993
75 9171000002 1710 5.26 926909   230 9269100003 2691 1.24 219322
76 9171000003 1710 2.56 450836   231 9269300002 2693 4.37 769649
77 9171100004 1711 1.28 225877   232 9270200002 2702 2.88 508607
78 9171600003 1716 4.29 756501   233 9272100002 2721 6.61 1165708
79 9172300002 1723 4.09 720996   234 9272200003 2722 3.91 689470
80 9175700002 1757 4.69 826810   235 9272300003 2723 1.79 316186
81 9176600004 1766 1.97 346701   236 9272400004 2724 6.2 1093794
82 9176800004 1768 1.7 300522   237 9273200003 2732 4.78 842060
83 9176900004 1769 1.62 285310   238 9273400004 2734 6.58 1160738
84 9177600004 1776 3.42 603085   239 9274300003 2743 5.68 1002279
85 9178100003 1781 1.75 309354   240 9276100002 2761 0.95 167169
86 9179300002 1793 3.36 591642   241 9276400002 2764 2.79 492081
87 9180400003 1804 2.58 454489   242 9276600002 2766 3.79 668182
88 9180700003 1807 4.22 744111   243 9276600003 2766 3.47 611061
89 9181400002 1814 1.19 209206   244 9276700003 2767 4.7 828186
90 9181700003 1817 2.36 415451   245 9278000004 2780 3.44 607388
91 9181900003 1819 4.2 740381   246 9278900002 2789 3.99 703211
92 9182100003 1821 5.27 928537   247 9279400003 2794 0.94 166137
93 9182200003 1822 4.81 848729   248 9280600003 2806 1.98 349925
94 9182500003 1825 3.03 534405   249 9281000002 2810 3.13 552697
95 9185700003 1857 1.52 267126   250 9281200003 2812 3.62 637549
96 9187200003 1872 2.3 405573   251 9281300003 2813 2.18 384111
97 9187300003 1873 3.35 591401   252 9285000003 2850 5.78 1018841
98 9187400002 1874 4.27 751985   253 9285400002 2854 1 176060
99 9187400003 1874 2.52 443917   254 9285400003 2854 3.17 559730
100 9188300003 1883 1.09 192227   255 9285600002 2856 0.98 173367
101 9189000003 1890 2.53 446735   256 9285700003 2857 3.8 669560
102 9189200004 1892 3.79 668616   257 9288200003 2882 1.08 191254
103 9190100002 1901 5.01 882669   258 9289500004 2895 1.73 305505
104 9190400003 1904 1.39 244955   259 9289800002 2898 1.13 200067
105 9190600003 1906 2.32 409140   260 9290800002 2908 3.45 608332
106 9191000002 1910 6.44 1134925   261 9291100003 2911 3 529685
107 9191100005 1911 3.12 549656   262 9291500002 2915 1.03 181709
108 9191300004 1913 4.98 877200   263 9291600004 2916 3.01 530927
109 9191600003 1916 2.83 498338   264 9291800002 2918 4.92 867689
110 9191700004 1917 5.73 1010187   265 9291900002 2919 2.67 470591
111 9191800002 1918 5.73 1010697   266 9292200002 2922 5.23 921950
112 9192100003 1921 2.25 397558   267 9292300002 2923 3.36 592678
113 9193100002 1931 2.14 377032   268 9292300003 2923 3.32 585432
114 9193200002 1932 3.09 545221   269 9292400005 2924 3.6 635465
115 9194500007 1945 2.16 380834   270 9293100002 2931 6.35 1118778
116 9194800004 1948 3.55 625570   271 9293400002 2934 1.11 196290
117 9195000003 1950 3.73 658118   272 9293500002 2935 1.21 213551
118 9196600002 1966 5.18 913961   273 9293700002 2937 4.79 844386
119 9196900002 1969 1.25 220960   274 9294700014 2947 1.85 325342
120 9197000002 1970 5.27 929152   275 9294800004 2948 1.6 282729
121 9197500003 1975 2.27 399390   276 9294900005 2949 4.03 710343
122 9198100002 1981 2.22 390596   277 9305600003 3056 4.35 767630
123 9198300002 1983 4.06 716621   278 9305600004 3056 4.58 807780
124 9198400003 1984 2.51 443394   279 9305700003 3057 5.35 943508
125 9198700006 1987 1.09 192494   280 9305700005 3057 2 352481
126 9198900002 1989 1.82 320276   281 9305800002 3058 4.78 843571
127 9198900004 1989 4.43 780710   282 9306300003 3063 2.3 405608
128 9199200004 1992 1.05 185637   283 9306400004 3064 6.67 1176203
129 9199500004 1995 1.91 336064   284 9307500002 3075 2.49 438811
130 9200100005 2001 3.19 563143   285 9307800002 3078 1.62 285357
131 9200200002 2002 3.23 568866   286 9307900004 3079 3.1 546744
132 9200400003 2004 2.12 373047   287 9307900005 3079 6.48 1142453
133 9200800004 2008 4.74 835613   288 9308100004 3081 3.64 641870
134 9200900003 2009 1.74 307235   289 9308100005 3081 2.51 442592
135 9201300003 2013 4.14 730250   290 9308700003 3087 3.16 557727
136 9201400003 2014 1.66 292367   291 9309200003 3092 2.53 446555
137 9201500003 2015 6.49 1144810   292 9309900002 3099 4.56 804260
138 9202100003 2021 1.87 330235   293 9310100003 3101 7.66 1349994
139 9202900002 2029 4.21 741632   294 9310200004 3102 4.71 830686
140 9204700002 2047 1.6 282537   295 9311100002 3111 1.56 274181
141 9205700003 2057 6.36 1121529   296 9311100005 3111 5.01 883409
142 9207100003 2071 2.63 463072   297 9312000002 3120 0.97 170493
143 9207600004 2076 1.7 299695   298 9312000003 3120 3.08 542823
144 9207700003 2077 3.48 612781   299 9312000004 3120 2.03 358103
145 9208100004 2081 5.96 1051690   300 9313500002 3135 4.54 800551
146 9208400003 2084 5.35 942755   301 9313900002 3139 2.8 492855
147 9209500004 2095 3.19 561571   302 9315100002 3151 1.52 267559
148 9209600002 2096 6.56 1156232   303 9316200002 3162 4.86 857242
149 9209800002 2098 5.43 957569   304 9316200003 3162 1.55 273718
150 9210100003 2101 4.22 744294   305 9317200002 3172 1.54 271656
151 9210700004 2107 3.95 696954   306 9319100004 3191 4.31 760519
152 9211000002 2110 4.87 857875   307 9321200004 3212 3.71 654218
153 9211600002 2116 5.94 1047642   308 9321700003 3217 1.98 348438
154 9211700002 2117 2.14 376952    

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Table 5.  Pointed XMM-Newton EPIC-pn Small Window Mode Observations

Source Obs. ID Year Filter Exp. Number of
      Setup ks Frames (×106)
AB Doradus 0134522101 2002 Closed Flt. 49 8.55
AB Doradus 0160362901 2004 Closed Flt. 56 9.87
AB Doradus 0791980401 2017 Thick Flt. 12 2.08
SNR 21.5−09 0804250201 2017 Thin Flt. 41 7.14

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Footnotes

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10.3847/1538-4357/ab698a