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Unveiling the origin of XMM-Newton soft proton flares II. Systematics in the proton spectral analysis

T0 review · 4 major / 4 minor · reviewed 2026-08-09 · deepseek-v4-flash

Pith's one-line read The paper argues that the input spectrum of XMM-Newton soft proton flares is a power law, and that the soft excess below 5 keV is an artifact of the proton response matrices rather than a real proton component.

desk verdict First real-data test of the XMM soft-proton response matrices; the systematics are useful, but the pure power-law claim rests on an interpretation of the soft excess that the paper doesn't fully nail down. read the letter →

arxiv 2501.18346 v1 pith:VMMLDQ53 submitted 2025-01-30 astro-ph.HE hep-ph

classification astro-ph.HEhep-ph
keywords softprotonflaresXMM-Newtonresponsematricespower-lawspectrumspectraldeconvolutionMOSandPNdetectorsmagnetosphericprotonssolaractivity
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

XMM-Newton's mirrors focus not only X-rays but also low-energy protons, which arrive as sudden soft proton flares that contaminate observations. This paper tests, for the first time on real data, the response matrices built to convert those proton detections back into the incoming proton spectrum. The central claim is that the input proton spectrum is a power law; the extra soft component needed to fit the 2–5 keV band is a symptom of imperfect matrices, not a real proton population. The analysis of 55 simultaneous MOS and PN flare spectra also quantifies how much the two detector types disagree, giving systematic uncertainties of about 3% between the two MOS cameras and about 24% between MOS and PN. If right, the result clears the way for using flare spectra to monitor the Earth's magnetospheric proton environment across the mission's 20-year lifetime.

What carries the argument

The central object is the proton response matrix: a Monte Carlo–generated transfer function that maps an incoming proton energy to the charge deposited in the MOS or PN CCD, folded into the ancillary response and redistribution files used by standard spectral fitting software. It is what lets the authors turn a measured flare spectrum into an inferred input spectrum. The second ingredient is a phenomenological black-body component added below 5 keV to absorb the discrepancy between the extrapolated power law and the data; the paper's argument is that this component tracks matrix error rather than real emission, because it is strongest where passive material in front of the detectors is largest.

What would settle it

A laboratory measurement of proton transmission through the actual MOS optical filters and electrode structures, compared with the simulated response, would settle whether the 2–5 keV excess is a matrix artifact; if the simulated transmission is correct, the black-body component should disappear once the matrices are corrected, while a residual excess would support a real low-energy component such as heavier ions.

Watch

Extended reading notes

Core claim

Using 55 simultaneous MOS and PN flare observations taken at solar maximum (2001–2002) and solar minimum (2019–2020), the authors deconvolved background-subtracted spectra in the 2–11.5 keV band with the proton response matrices. A single power law fails for 72% of the spectra over the full band, but fits 96% of them in the 5–11.5 keV range; extrapolating that power law downward leaves an excess that is 21% of the MOS count rate and 5% of the PN count rate in the 2–5 keV band. Adding a phenomenological black-body component with a temperature near 1 keV recovers acceptable fits for 83% of the spectra, and the authors argue this component is an artifact of the matrices: the excess is larger for the front-illuminated MOS, which have electrode structure in front of the detector, than for the back-illuminated PN, and its size grows with passive material in the filters. They conclude that the physical input spectrum of soft proton flares is a power law, that the soft excess reflects imprecise modeling of proton transmission at the focal plane, and that the remaining cross-instrument differences set the systematic errors: about 3% on spectral indices between the two MOS cameras, about 24% between MOS and PN, and a factor of about two on the inferred input flux.

Load-bearing premise

The analysis assumes the simulated proton response matrices accurately describe how protons of each energy are transmitted and deposit charge in the real MOS and PN detectors; if the simulated effective area is wrong in the 2–5 keV band, what looks like a matrix artifact could be a real spectral component.

Editorial extensions

If this is right

  • The soft proton input spectrum can be treated as a power law, so flare observations can be converted into physical proton fluxes at the telescope entrance.
  • The 2–5 keV excess should be absorbed as a systematic (21% for MOS, 5% for PN) rather than modeled as a separate proton population.
  • No seasonal or solar-cycle dependence of mean flare rates is found across the four epochs.
  • MOS proton response has degraded over 20 years (about 30% for MOS1 on top of CCD loss, and more for MOS2), so flare-rate comparisons need epoch-dependent corrections.
  • Cross-instrument systematic uncertainties are quantified: about 3% on spectral indices between MOS1 and MOS2, about 24% between MOS and PN, and a factor of about two on input flux.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the soft excess is a matrix artifact, previous XMM background studies that treated a soft component as real may need to revisit their flare-contamination modeling.
  • The same deconvolution method, applied to the full archive of flares once MOS degradation is modeled, could produce a 20-year map of the magnetospheric proton environment at different orbital distances.
  • A direct laboratory measurement of proton transmission through the filters, which the paper calls for, would either confirm the artifact explanation or revive the heavier-ion alternative.
  • For future grazing-incidence X-ray missions, the lesson is that proton response matrices must be validated on real flares before being used to predict focal-plane proton backgrounds.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 4 minor

Summary. The paper presents the first application of the Geant4-based soft-proton response matrices of Paper I to real XMM-Newton flare spectra, using 55 simultaneous MOS1/MOS2/PN observations in four epochs spanning solar maximum and minimum. The authors find no epoch-dependent variation in mean flare rates, report that a single power law fits the 5-11.5 keV band but leaves a low-energy excess in 2-5 keV that they model phenomenologically with a black body, and attribute this excess to imprecision in the proton response matrices at softer energies. They also derive inter-detector systematic uncertainties in spectral indices and input fluxes and identify a time-dependent degradation of MOS proton response relative to PN.

Significance. If the conclusions hold, this is a valuable first real-data validation of proton response matrices for XMM-Newton, with direct implications for background modeling and for future missions such as Athena. The matrices themselves are derived from independent Geant4 simulations rather than from the fitted data, so the comparison is a genuine external check rather than circular. The multi-instrument comparison and the use of four epochs provide a useful empirical handle on systematic uncertainties. The main result, however, rests on the interpretation of the low-energy excess as a matrix artifact; that interpretation is plausible but not demonstrated, and the paper itself concedes that a physical origin from heavier ions cannot be entirely excluded.

major comments (4)
  1. [Section 6 (and abstract)] The central attribution of the 2-5 keV soft excess to matrix imprecision is not demonstrated. The evidence is an extrapolation of the 5-11.5 keV power law plus a phenomenological black body, and the paper explicitly states that 'a more physical origin—that is, a component coming from heavier ions—cannot be entirely excluded.' The 2-5 keV band is exactly the range where the Geant4 matrices are least independently validated. The Paper I trend with passive material and the lower PN excess are suggestive but do not establish the artifact interpretation. A concrete test is available in the data: compare the amplitude of the soft excess relative to the power law for thin-filter versus medium-filter observations of the same instrument and epoch. This comparison is not performed. The authors should either perform it or reframe the abstract and conclusions to present the matrix-artifact interpretation as a hypothesis rather than the main result.
  2. [Section 4.1] Some PN spectra are excluded from the subsequent analysis after the power-law extrapolation overestimates the 2-5 keV rates. The text says 'we excluded them from the following analysis' for observations 0052140201, 0108061901, 0827241201, 0844210101, 0852190101, 0854590401, and 0862400101. This is a post-hoc selection on the dependent variable: removing cases with negative or zero soft excess biases the sample toward positive excesses and can inflate the reported 21% (MOS) and 5% (PN) excess fractions and the perceived need for a black-body component. The authors should quantify how many spectra are excluded and show that the conclusions are robust when all spectra are included, or adopt a model that can accommodate flattening below 5 keV.
  3. [Section 4.2] The two-step fitting procedure fixes the power-law parameters from the 5-11.5 keV fit before adding the black-body component. As the paper states, allowing all parameters to float in the full 2-11.5 keV range changes the results, and the fixed-parameter approach was adopted to avoid degeneracies. This makes the model comparison unequal: the power-law-plus-black-body model is not compared with alternative models on the same footing, and the reported uncertainties on kT and the excess rates do not propagate the covariance with the fixed power-law parameters. A simultaneous fit with weak priors, or at least a profile-likelihood treatment, is needed to support the claim that the black body is the only model that gives coherent results across detectors.
  4. [Section 4.3.1] The broken power-law test is not a strong test of spectral steepening within the fitted band. For MOS, the best-fit break energies are 22-27 keV, above the fitted 2-11.5 keV range, so within the analysis band the model is effectively a single power law; the indices below the break are explicitly unconstrained. The statement that a broken power law 'cannot be considered physically reliable' and that there is no evidence for steepening is therefore weaker than presented. The log-parabola model also gives incoherent MOS/PN parameters, but the conclusion that the input spectrum is a pure power law should be based primarily on the simultaneous fits and the missing filter comparison, not on the broken-power-law result.
minor comments (4)
  1. [Multiple sections] There are typographical errors and axis-label inconsistencies: Figure 3 uses 'Dic.' instead of 'Dec.', Section 3 has 'corespondent' for 'corresponding', and Section 6 has 'have have formed'. These should be corrected.
  2. [Section 3 / Table 3] The statement that there are no statistically significant variations in the mean rates across epochs is a null result with limited power, given the large rms values and the small number of epochs. It would be more precise to say that no variation is detected rather than that there is no effect.
  3. [Section 4.1] The NHP threshold of 2.7e-3 is applied per spectrum without multiple-testing correction. With 165 spectra the expected number of false rejections under the null is small (about 0.4), so this is not a serious concern, but the paper should state explicitly that no multiple-testing correction was applied.
  4. [Figure 10 caption] The caption says the flux ratio is plotted 'as a function of the PN rates in the same band', but the text describes ratios of MOS1/MOS2, MOS1/PN, and MOS2/PN fluxes as functions of MOS2 or PN rates. The caption and axis labels should be aligned with the text for all three panels.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the power-law input claim and the matrix-systematics interpretation follow from fitting new flare data with an independently simulated Geant4 response matrix, not from a fitted input renamed as a prediction.

full rationale

The derivation chain is self-contained in the relevant sense. The proton response matrices were built in Paper I from Geant4 simulations and are not fitted to the flare data used here; they are applied to 55 new MOS/PN flare spectra as an external test. The power-law input spectrum is established by fitting the 5–11.5 keV band, where 96% of spectra are consistent with a single power law, and is then extrapolated downward. The soft excess is measured as residuals against that power law and modeled phenomenologically with a black body. No equation defines the input spectrum in terms of the fitted black-body component, and no fitted parameter is renamed as a prediction. The attribution of the soft excess to matrix imprecision is an interpretation, not a construction: it is supported by the larger MOS excess, the back-illuminated PN geometry, and a trend cited from Paper I, and the paper explicitly concedes that a physical origin such as heavier ions cannot be entirely excluded. Same-group citations (Paper I; Lotti et al. 2018; Fioretti et al. 2018) provide prior modeling and a simulation-based trend, but the central power-law result is independently evidenced by the fits and the hardness-ratio correlation. There is minor same-group citation, but it is not load-bearing circularity and does not reduce the conclusion to its own input.

Assumptions & free parameters 1 free parameters · 4 assumptions · 0 invented entities

The analysis rests on the proton response matrices from Paper I, which are Geant4 simulations, and on the assumption that the same proton spectrum hits all three detectors. The black body component is an ad hoc phenomenological addition. No new physical entities are introduced.

free parameters (1)
  • Black body temperature (kT) = ~1 keV for MOS, 0.9 keV for PN
    Phenomenological second component added to fit the soft excess below 5 keV; its physical interpretation (matrix artifact vs. real component) is not established.
assumptions (4)
  • domain assumption The Geant4-based proton response matrices accurately model proton interactions with XMM-Newton optics and detectors.
    The entire deconvolution of flare spectra relies on these matrices; the paper tests but does not independently verify them. Invoked in Section 1 and throughout.
  • domain assumption The input proton spectrum is identical for the three detectors in each observation.
    Inter-calibration ratios (Section 5) assume differences are entirely due to detector responses, not to variations in the incident proton flux.
  • domain assumption Background is well represented by quiescent intervals, and count rates follow a Gaussian distribution for threshold definition.
    Used in Section 2 to define flare and background GTIs with ave + 3*rms and ave + 2*rms thresholds; the Gaussian assumption is not validated for flaring intervals.
  • domain assumption The RGS shading factor reduces the MOS effective area for protons by a constant factor of about 50% independent of energy.
    Stated in Section 1 and taken from Paper I and Nartallo (2002); affects the absolute MOS effective area and hence the input flux.

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Cite this review

Pith. "Pith review of Unveiling the origin of XMM-Newton soft proton flares II. Systematics in the proton spectral analysis." pith.science (2026). https://pith.science/paper/VMMLDQ53

@misc{pith2026250118346,
  author       = {Pith},
  title        = {Pith review of: Unveiling the origin of XMM-Newton soft proton flares II. Systematics in the proton spectral analysis},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/VMMLDQ53}},
  note         = {Machine review of arXiv:2501.18346}
}
read the original abstract

Low-energy protons entering the field of view of the XMM-Newton telescope scatter with the X-ray mirror surface and might reach the X-ray detectors on the focal plane. They manifest in the form of a sudden increase in the rates, usually referred to as soft proton flares. By knowing the conversion factor between the soft proton energy and the deposited charge on the detector, it is possible to derive the incoming flux and to study the environment of the Earth magnetosphere at different distances. We present the results of testing these matrices with real data for the first time, while also exploring the seasonal and solar activity effect on the proton environment. The selected spectra are relative to 55 simultaneous MOS and PN observations with flares raised in four different temporal windows: December-January and July-August of 2001-2002 (solar maximum) and 2019-2020 (solar minimum). The main result of the spectral analysis is that the physical model representative of the proton spectra at the input of the telescope is a power law. However, a second and phenomenological component is necessary to take into account imprecision in the generation of the matrices at softer energies.

Figures

Figures reproduced from arXiv: 2501.18346 by the authors.

Figure 1
Figure 1. Proton response matrix effective area for MOS (top panel) and PN (bottom panel). The application of the thin (medium) filter is repre￾sented by a continuous (dash-dotted) curve. Rate (c/s) 1 100.5 2 5 20 MOS1 Rate (c/s) 1 100.5 2 5 20 MOS2 0 2×104 4×104 6×104 8×104 105 10 100 Rate (c/s) Time (s) PN [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Light curves relative to observation ID 0844860601 (2020-01- 06) for MOS1, MOS2, and PN. The dashed vertical lines delimit the interval in which the background rate was evaluated, the dash-dotted lines indicate the highest background rate, and the dotted lines indicate the lowest flare rate. between the MOS and PN matrices under the consideration that the input spectra measured by the three detectors must be statis￾… view at source ↗
Figure 3
Figure 3. Correlations between rates detected by the three instruments in the four epochs. Colors indicate epochs (see text). The superimposed dashed black line is relative to the best fit of epoch B. The top panel is relative to MOS1 vs MOS2 rates, the middle panel to MOS1 vs PN, and the bottom panel to MOS2 vs PN. 1 102 5 20 0.5 1 1.5 2 MOS1 HR MOS1 Rate (c/s) Dic. 2001 − Jan. 2002 Jul. 2002 − Aug. 2002 Dic. 2019 − Jan. 202… view at source ↗
Figures from the paper (6 more)
Figure 5
Figure 5. Figure 5: Spectral fit with a power law. The upper plot shows the MOS1 spectrum relative to observation ID 0108060601. The top panel presents with a continuous line the 5–11 keV best-fit power law extrapolated down to 2 keV, while residuals over the whole range are presented in …
Figure 6
Figure 6. Figure 6: Excess rates with respect of the 5–11.5 keV best-fit power law in the range of 2–5 keV as a function of the total 2–5 rates for MOS1 (top panel), MOS2 (middle panel), and PN (bottom panel). in MOS data. A weak correlation with the excess rate is instead detected for th…
Figure 8
Figure 8. Figure 8: Spectral index computed with Eq. 2 for MOS1 (continuous blue line) and PN (continuous red line) spectra of observation ID 0110980601. The dash-dotted lines indicate the 90% confidence level. For comparison, the spectral index relative to the 90% flux in the active magn…
Figure 9
Figure 9. Figure 9: Ratio of the spectral indices measured by MOS1 and MOS2 (top panel), MOS1 and PN (middle panel), and MOS2 and PN (bottom panel) as a function of the rates in the 5–11.5 keV band. The dashed black line is the best-fit constant, while the dotted lines indicate the relati…
Figure 10
Figure 10. Figure 10: Ratio of the 30-300 proton input flux measured by MOS2 and by PN as a function of the PN rates in the same band. The dashed blue line is the average value for the interval A and B, while the dash-dotted green line is the average for C and D. The dotted lines indicate …
Figure 11
Figure 11. Figure 11: Analysis of spectral variability in the observation ID 0037980401: the top panel shows the color-color diagram and the cor￾relation between rates in the ranges 0.5–2 keV and 5–11.5 keV is pre￾sented in the bottom panel. there is no significant difference in the spectr…

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Works this paper leans on

21 extracted references · 19 canonical work pages

  1. [1]

    & Arnaud, K

    Dorman, B. & Arnaud, K. A. 2001, in Astronomical Society of th e Pacific Con- ference Series, V ol. 238, Astronomical Data Analysis Softw are and Systems X, ed. J. Harnden, F. R., F. A. Primini, & H. E. Payne, 415

  2. [2]

    2016, in So- ciety of Photo-Optical Instrumentation Engineers (SPIE) C onference Series, V ol

    Fioretti, V ., Bulgarelli, A., Malaguti, G., Spiga, D., & Tie ngo, A. 2016, in So- ciety of Photo-Optical Instrumentation Engineers (SPIE) C onference Series, V ol. 9905, Space Telescopes and Instrumentation 2016: Ultraviolet to Gamma Ray, ed. J.-W. A. den Herder, T. Takahashi, & M. Bautz, 99056W

  3. [3]

    2018, ApJ, 867, 9

    Fioretti, V ., Bulgarelli, A., Molendi, S., et al. 2018, ApJ, 867, 9

  4. [4]

    2024, A&A, same vol ume

    Fioretti, V ., Mineo, T., Lotti, S., et al. 2024, A&A, same vol ume

  5. [5]

    2017, Ex perimental Astronomy, 44, 321

    Gastaldello, F., Ghizzardi, S., Marelli, M., et al. 2017, Ex perimental Astronomy, 44, 321

  6. [6]

    2017, Exper imental Astronomy, 44, 273

    Ghizzardi, S., Marelli, M., Salvetti, D., et al. 2017, Exper imental Astronomy, 44, 273

  7. [7]

    2001, A&A, 365, L1

    Jansen, F., Lumb, D., Altieri, B., et al. 2001, A&A, 365, L1

  8. [8]

    A., Gastaldello, F., Haaland, S., et al

    Kronberg, E. A., Gastaldello, F., Haaland, S., et al. 2020, i n AGU Fall Meeting

Show all 21 references
  1. [9]

    2020, NG005–01

    Abstracts, V ol. 2020, NG005–01

  2. [10]

    Kuntz, K. D. & Snowden, S. L. 2008, A&A, 478, 575

  3. [11]

    Lo, D. H. & Srour, J. R. 2003, IEEE Transactions on Nuclear Sci ence, 50, 2018

  4. [12]

    2018, Experimental Astronomy, 45, 411

    Lotti, S., Mineo, T., Jacquey, C., et al. 2018, Experimental Astronomy, 45, 411

  5. [13]

    2017, A THENA Radi ation Environ- ment Models and X-ray Background E ffects Simulators, ESA Contract No

    Macculi, C., Molendi, S., Lotti, S., et al. 2017, A THENA Radi ation Environ- ment Models and X-ray Background E ffects Simulators, ESA Contract No. 4000116655/16/NL/BW

  6. [14]

    2017, Exp erimental Astronomy, 44, 297

    Marelli, M., Salvetti, D., Gastaldello, F., et al. 2017, Exp erimental Astronomy, 44, 297

  7. [15]

    2004, A&A, 422, 103

    Massaro, E., Perri, M., Giommi, P ., Nesci, R., & V errecchia,F. 2004, A&A, 422, 103

  8. [16]

    2017, Radiation B ackground Data Analysis & Lessons Learned from Previous X-ray Missions, AR EMBES WP1 Thecnical Note 1.1

    Molendi, S., Ghizzardi, S., & Rossetti, M. 2017, Radiation B ackground Data Analysis & Lessons Learned from Previous X-ray Missions, AR EMBES WP1 Thecnical Note 1.1

  9. [17]

    2002, Esa /estec/tos-ema/02-067/RN Technical Note

    Nartallo, R. 2002, Esa /estec/tos-ema/02-067/RN Technical Note

  10. [18]

    P ., Beardmore, A

    Plucinsky, P . P ., Beardmore, A. P ., Foster, A., et al. 2017, A&A, 597, A35

  11. [19]

    2017, Exp erimental Astronomy, 44, 309 Strüder, L., Briel, U., Dennerl, K., et al

    Salvetti, D., Marelli, M., Gastaldello, F., et al. 2017, Exp erimental Astronomy, 44, 309 Strüder, L., Briel, U., Dennerl, K., et al. 2001, A&A, 365, L1 8

  12. [20]

    Turner, M. J. L., Abbey, A., Arnaud, M., et al. 2001, A&A, 365, L27

  13. [21]

    C., Brinkman, B., Canizares, C., et al

    Weisskopf, M. C., Brinkman, B., Canizares, C., et al. 2002, P ASP , 114, 1 Article number, page 12 of 12

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