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REVIEW 3 major objections 6 minor 12 references

Simulation of Solar Wind Charged Particle Energy Deposited and Particle Identification by $\Delta$E-E Discrimination in the SNAPPY Cubesat Detector

T0 review · 3 major / 6 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read Simulation shows a CubeSat detector designed for neutrino background studies can identify electrons, protons, and alpha particles from the solar wind via Delta E-E discrimination, while heavier ions remain unresolved under isotropic…

desk verdict A transparent but idealized GEANT4 feasibility study whose central claim about dE-E discrimination for the SNAPPY detector outruns the simulation's 1% scintillation-yield shortcut and noise-free readout. read the letter →

arxiv 2411.08170 v2 pith:QZUSUCCW submitted 2024-11-12 astro-ph.SR astro-ph.IMphysics.ins-detphysics.plasm-phphysics.space-ph

Daniel Reichart , Nickolas Solomey This is my paper · ORCID
classification astro-ph.SRastro-ph.IMphysics.ins-detphysics.plasm-phphysics.space-ph
keywords solarwindenergeticparticlesDeltaE-EparticleidentificationCubeSatdetectorscintillatorMonteCarlosimulationGAGGdiscrimination
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

The paper asks whether the SNAPPY CubeSat, a scintillator detector built to veto background for a future solar-neutrino mission, can also identify solar-wind charged particles while in low Earth orbit. Using Monte Carlo simulations of electrons, protons, $\alpha$ particles, and several heavier ions over realistic solar-energetic-particle energies, it finds that the veto and GAGG crystals behave like a $\Delta$ E-E telescope. In most simulated geometries, electrons, protons, and $\alpha$ particles fall into separate regions of the veto-versus-GAGG plot, so their species and approximate energies could be read off. Under isotropic illumination, carbon, nitrogen, oxygen, and neon overlap and cannot be told apart, and helium-3, magnesium, silicon, and iron are essentially invisible to this method. If the simulation faithfully reflects the detector, the flight could deliver light-ion solar-wind spectra as a secondary science product.

What carries the argument

The central object is the $\Delta$ E-E discrimination plot: for each event, the energy deposited in the veto (or the corresponding photon count) is plotted against the energy deposited in the GAGG (or its photon count). Because ions of different mass lose energy at different rates, each species should occupy its own band. The geometry differs from a classical telescope in that the GAGG is fully encased in the veto, so a penetrating particle re-enters the veto and creates a discontinuity at the punch-through energy; the simulation tracks both true energy deposition and idealized photon counts (with scintillation yield reduced to one percent of the material value) to mimic the PMT and SiPM readout.

What would settle it

A dedicated accelerator test using the actual veto-GAGG detector with beams of electrons, protons, and $\alpha$ particles spanning the simulated energy ranges (roughly 1 to 10 MeV electrons, 1 MeV to 3.2 GeV protons, and 4 MeV to 3.2 GeV alphas) would settle the claim: if the measured $\Delta$ E-E scatter does not show three distinct, separable bands under isotropic or face-on illumination, the simulation's conclusion fails.

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Extended reading notes

Core claim

The paper argues that a veto-GAGG scintillator CubeSat, originally intended for neutrino background rejection, can double as a $\Delta$ E-E particle telescope: the surrounding veto acts as the $\Delta$ E layer and the inner GAGG crystals as the E layer. In the simulations across seven incidence geometries, electrons, protons, and $\alpha$ particles form distinct bands in veto-vs-GAGG energy-deposition and photon-count scatter plots in most scenarios, so these species can be identified and their energies roughly measured. Under isotropic illumination resembling the low-Earth-orbit environment, heavier ions (carbon, nitrogen, oxygen, neon) collapse into a single overlapping region and cannot be separated; helium-3, magnesium, silicon, and iron never reach both detector volumes within the simulated energies and are not discriminated at all.

Load-bearing premise

The conclusions rest on the assumption that reducing the scintillation light yield to one percent of its true value preserves the shapes of the $\Delta$ E-E plots, and that the real photodetector reads out a voltage directly proportional to photon count with no noise, threshold, gain variation, or quantum-efficiency distortion; if the real readout compresses or shifts the bands, the separation seen in simulation may not appear in flight data.

Editorial extensions

If this is right

  • In flight, the detector can act as a solar energetic particle monitor for electrons, protons, and alpha particles, identifying species without a dedicated particle-ID instrument.
  • Heavy ions (carbon, nitrogen, oxygen, neon) will be detected as an unresolved group, so the mission cannot report separate abundances for these species from isotropic data.
  • Helium-3, magnesium, silicon, and iron are not expected to deposit energy in both detectors at all within the simulated energy ranges, making Delta E-E ineffective for them.
  • The photon-count representation, which is closer to a real readout, preserves the separation of the light species, so the particle-ID conclusion is not purely an artifact of perfect energy-deposition knowledge.
  • Future acceptance-correction work could convert the measured band intensities into an actual solar-wind energy spectrum for the resolved species.

Reading between the lines

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

  • If the distinct bands hold up in beam tests, the SNAPPY detector could produce a solar-wind light-ion spectrum as a by-product of its neutrino mission, requiring no change to flight hardware.
  • The inability to distinguish carbon, nitrogen, oxygen, and neon under isotropic incidence may be fundamental to the single-veto-layer geometry: these species have similar charge-to-mass ratio and thus similar energy-loss rates, so separating them would likely require an added time-of-flight measurement or a second Delta E layer.
  • The one-percent scintillation-yield shortcut deserves a direct check: a short simulation at the full yield for representative energies would confirm whether the band shapes are truly unchanged, a test the future-work section already implies.
  • Because the low-Earth-orbit environment is isotropic, the practical outcome for the 2025 flight is likely light-ion counting only, not heavy-ion composition; heavy-ion discrimination would only be plausible in a collimated or directed-particle context.
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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

3 major / 6 minor

Summary. The paper reports GEANT4 simulations of the SNAPPY CubeSat detector to assess whether the ΔE-E technique can identify solar energetic particles (electrons, protons, alpha particles, and heavier ions) in several illumination scenarios, including pencil beam, face-on, and isotropic incidence. The author concludes that electrons, protons, and alpha particles separate into distinct regions in most scenarios, while heavier ions such as C, N, O, and Ne are not distinguishable under isotropic incidence. The study uses both GEANT4 energy-deposition outputs and photon-count outputs, with the photon-count simulation run at 1% of the true scintillation yield.

Significance. If the conclusion holds, the SNAPPY veto-GAGG detector could provide a parasitic solar-wind particle identification and rough energy measurement capability in low Earth orbit. The strengths of the study are its systematic coverage of multiple incidence geometries, the use of realistic particle species and energy ranges for solar energetic particle events, and the inclusion of both energy-deposition and photon-count views. However, the load-bearing simplification of running the scintillation yield at 1% of its true value, combined with an idealized readout model and the lack of any quantitative separation metric, means that the central claim about the real detector is not yet fully supported. The qualitative result about heavy-ion overlap is plausible, but the evidence presented is insufficient to establish that the planned detector will achieve light-particle discrimination.

major comments (3)
  1. [Section 3.2] The simulation is run with the scintillation yield at exactly 1% of the true material value, and the text asserts that this 'should not affect the overall shape of the graphs' without any supporting demonstration. Because the photon-count plots (e.g., Figures 25 and 26) are the basis for the conclusion about particle separation, this unsupported assertion is load-bearing: reducing the yield by a factor of 100 increases relative Poisson fluctuations by a factor of 10 and quantizes low-energy signals into few-photon bins, which can broaden or split the particle bands and alter the apparent separation. Please either rerun a representative subset of scenarios at the true yield, or quantitatively demonstrate shape invariance by comparing the boundaries of the particle regions at 1% and 100% yield for the same geometry.
  2. [Section 4.4.1, Figure 25] In the spherical isotropic scenario, the proton and alpha regions overlap substantially, as acknowledged by the 'dolphin shape' and the dense vertical section in Figure 26, yet the conclusion states that electrons, protons, and alpha particles separate into distinct regions. The separation is assessed only by eye; no quantitative metric is provided, such as the fraction of events in an overlap region, a confusion matrix, or a classification efficiency. Please add a quantitative measure of separation, particularly for the isotropic scenarios, to support the claim that ΔE-E is a valid identification method in the detector's actual operating environment.
  3. [Section 4 (introductory paragraph)] The energy-deposition plots are described as 'perfect information' with no quantum efficiency, electronic noise, gain variations, or detection thresholds, and Section 3.2 states that the PMT and SiPM voltages are directly proportional to the photon count. The conclusion about the real detector therefore rests on an idealized readout model. This is a legitimate simplifying assumption for a first simulation, but it should be stated explicitly as an upper-bound idealization, and its potential impact on the separation claim should be discussed; otherwise the conclusion overreaches the evidence presented.
minor comments (6)
  1. [Table 1] The energy range for 56Fe is listed as '56 MeV - 1.58 MeV'; the upper bound is presumably 1.58 GeV, given the text elsewhere states that solar energetic particles can reach 'hundreds of MeV or a couple of GeV.' Please correct this typo.
  2. [Section 1] The word 'CubSsat' should be 'CubeSat'.
  3. [Section 4.1] The sentence 'Silicon is not show shown' should read 'Silicon is not shown,' and the preceding clause about Nitrogen, Oxygen, and Neon is missing a word; it should state that these are 'not shown' because they are similar to Figure 6a.
  4. [References [2] and [11]] References [2] and [11] are web pages rather than peer-reviewed sources; for a journal version, consider citing the underlying literature (e.g., for the ΔE-E method and the ROOT analysis framework).
  5. [Section 3.3] The statement that the simulation assigns energies on a logarithmic distribution that favors lower energies but 'is not the same as observation' is useful; please specify how the sampling distribution affects the interpretation of the density of points in the ΔE-E plots.
  6. [Section 4.3.2] The 'V shape' in the photon-count plots is mentioned but not explained; a brief explanation of which detector geometry or energy-loss path causes this feature would help the reader.

Circularity Check

0 steps flagged · score 2.0 of 10

No circular derivation: the ΔE-E separation result emerges from forward GEANT4 outputs rather than from fitted inputs; minor in-group citations and an unpublished validation report are context, not load-bearing circularity.

full rationale

The paper's derivation chain is a forward GEANT4 simulation. The particle species and energy ranges are taken from external references [3,8,9,10] and are not tuned to produce the observed separation bands. The central ΔE-E plots are direct simulation outputs, so no fitted parameter is renamed as a prediction and no output quantity is used to define an input. The inherited GEANT4 detector model [5] and the cited Smith validation report [12] originate from the same research group, but the paper's separation claim is displayed in the simulation figures rather than derived from those citations; the citations provide geometry, prior context, and an unshown validation, not the logical reduction of the result to its own inputs. The 1% scintillation-yield approximation (Section 3.2) and the use of idealized GEANT4 energy deposition as a cross-check (Section 4) are correctness and robustness concerns: if the yield reduction changes the shapes or if readout nonlinearities compress the bands, the conclusion could fail, but this is an unsupported modeling assumption, not a circular definition. No equation in the paper relates a fitted quantity to the claimed prediction, and no alternative-eliminating uniqueness theorem is invoked. Therefore no specific circular step can be exhibited, and the score reflects only the mild self-reliance of the underlying model and validation source.

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

The simulation's conclusions rest on modeled detector geometry from prior work, a 1% scintillation-yield shortcut, literature-based energy cuts, and a simplified readout assumption; none are independently validated in this paper, so the paper contributes a feasibility indication rather than a calibrated instrument response.

free parameters (4)
  • scintillation_yield_scale = 0.01 (1% of true value)
    Set in Section 3.2 to reduce runtime. The authors claim this does not change the shape of the photon-count graphs, but no test is shown, and all photon-count based separation plots depend on it.
  • minimum_kinetic_energy_per_nucleon = 1 MeV/nucleon
    Chosen in Section 3.3 for coding ease. This excludes the thermal solar wind and sub-MeV SEP populations that the detector would actually encounter, so conclusions are restricted to energetic particles above this floor.
  • differential_flux_threshold = 1e-4 particles/(cm^2 s sr)
    Used in Section 3.3 to derive upper energy bounds from literature spectra. It is a selection cut chosen by the authors and determines which high-energy particles enter the simulation.
  • energy_sampling_distribution = log-uniform favoring lower energies
    Section 3.3 states this approximation is 'good' but 'not the same as observation'; it controls the density of events across the DeltaE-E plots and could affect visual separation.
assumptions (4)
  • domain assumption GEANT4 accurately simulates the physics and the inherited detector geometry [5] is correct for this study.
    Section 3 states simulations were done in GEANT4 'to ensure realistic results' and the geometry is a modified version of an already built model [5]; no comparison to measured detector response is provided.
  • ad hoc to paper The photomultiplier and SiPM voltages are directly proportional to the number of scintillation photons, and running at 1% scintillation yield preserves plot shape.
    Section 3.2: simulation uses exactly 1% of true yield and asserts shape is unchanged; real readout involves quantum efficiency, gain, noise and thresholds that are not modeled.
  • domain assumption Literature-derived SEP particle species and energy ranges, digitized by PlotDigitizer and cut at a flux of 1e-4 particles/(cm^2 s sr), represent the particles the CubeSat will encounter.
    Section 3.3: energy ranges are reconstructed from plots in [3], [8], [9], [10] using pixel counting; the log-uniform energy distribution favoring lower energies is admitted to differ from observation.
  • domain assumption Particles that do not deposit energy in both the veto and GAGG in the pencil-beam scenario will not deposit in both in any other scenario.
    Section 4.1: used to generalize from the ideal shortest-path scenario to all scenarios; assumes the pencil beam is the best-case penetration path and ignores any angle-dependent scattering that could produce GAGG hits.

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Cite this review

Pith. "Pith review of Simulation of Solar Wind Charged Particle Energy Deposited and Particle Identification by $\Delta$E-E Discrimination in the SNAPPY Cubesat Detector." pith.science (2026). https://pith.science/paper/QZUSUCCW

@misc{pith2026241108170,
  author       = {Pith},
  title        = {Pith review of: Simulation of Solar Wind Charged Particle Energy Deposited and Particle Identification by $\Delta$E-E Discrimination in the SNAPPY Cubesat Detector},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/QZUSUCCW}},
  note         = {Machine review of arXiv:2411.08170}
}
abstract

The Solar Neutrino and Astro-Particle PhYsics (SNAPPY) Cubesat is expected to launch in 2025 and it will carry into a polar orbit a prototype test detector for solar neutrino background studies while over the Earth's poles for the neutrino Solar Orbiting Laboratory future project ($\nu$SOL). During this flight it is possible to do other science measurements. One of these is an improved study of the solar wind particles through better particle identification and energy measurements. This study aimed to understand how well could the solar wind particles be identified using the planned detector but instead of using the veto array as an anti-coincidence it would be used as a $\Delta$E energy sampling of a phoswich particle ID system.

Figures

Figures reproduced from arXiv: 2411.08170 by the authors.

Figure 2
Figure 2. The CubeSat detector side view. To accurately simulate the true shielding density, the GEANT4 program incorporates the epoxy-to-tungsten powder ratio based on the materials’ known densities (ρ) and masses (m) used to create the shielding. The density calculation utilizes the well know formula: ρshielding = mTotal VTotal = mW + mE VW + VE = mW + mE mW ρW + mE ρE The hope of outlining the CubeSat detector is to visual… view at source ↗
Figure 3
Figure 3. Positive directions as specified by the coordinate axis system in GEANT4. [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. The seven simulation scenarios that are implemented in GEANT4. [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figures from the paper (30 more)
Figure 5
Figure 5. Figure 5: Electrons show chaos while protons and alphas exhibit discontinuities. [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]
Figure 6
Figure 6. Figure 6: Carbon shows no discontinuities, while Magnesium has no GAGG signal. [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: Veto vs GAGG energy deposition particle plot for the Pencil Beam scenario. [PITH_FULL_IMAGE:figures/full_fig_p011_7.png]
Figure 8
Figure 8. Figure 8: Veto vs GAGG energy deposition histogram for the Pencil Beam scenario. [PITH_FULL_IMAGE:figures/full_fig_p012_8.png]
Figure 9
Figure 9. Figure 9: Veto vs GAGG photon count particle plot for the Pencil Beam scenario. [PITH_FULL_IMAGE:figures/full_fig_p012_9.png]
Figure 10
Figure 10. Figure 10: Veto vs GAGG photon count histogram for the Pencil Beam scenario. [PITH_FULL_IMAGE:figures/full_fig_p013_10.png]
Figure 11
Figure 11. Figure 11: Veto vs GAGG energy deposition particle plot for the xyFace scenario. [PITH_FULL_IMAGE:figures/full_fig_p014_11.png]
Figure 12
Figure 12. Figure 12: Veto vs GAGG energy deposition histogram for the xyFace scenario. [PITH_FULL_IMAGE:figures/full_fig_p014_12.png]
Figure 13
Figure 13. Figure 13: Veto vs GAGG photon count particle plot for the xyFace scenario. [PITH_FULL_IMAGE:figures/full_fig_p015_13.png]
Figure 14
Figure 14. Figure 14: Veto vs GAGG photon count histogram for the xyFace scenario. [PITH_FULL_IMAGE:figures/full_fig_p015_14.png]
Figure 15
Figure 15. Figure 15: Veto vs GAGG energy deposition particle plot for the z+Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p016_15.png]
Figure 16
Figure 16. Figure 16: Veto vs GAGG energy deposition histogram for the z+Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p017_16.png]
Figure 17
Figure 17. Figure 17: Veto vs GAGG photon count particle plot for the z+Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p017_17.png]
Figure 18
Figure 18. Figure 18: Veto vs GAGG photon count histogram for the z+Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p018_18.png]
Figure 19
Figure 19. Figure 19: Veto vs GAGG energy deposition particle plot for the z-Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p019_19.png]
Figure 20
Figure 20. Figure 20: Veto vs GAGG energy deposition histogram for the z-Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p019_20.png]
Figure 21
Figure 21. Figure 21: Veto vs GAGG photon count particle plot for the z-Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p020_21.png]
Figure 22
Figure 22. Figure 22: Veto vs GAGG photon count histogram for the z-Face scenario. [PITH_FULL_IMAGE:figures/full_fig_p020_22.png]
Figure 23
Figure 23. Figure 23: Veto vs GAGG energy deposition particle plot for the iso scenario. [PITH_FULL_IMAGE:figures/full_fig_p021_23.png]
Figure 24
Figure 24. Figure 24: Veto vs GAGG energy deposition histogram for the iso scenario. [PITH_FULL_IMAGE:figures/full_fig_p022_24.png]
Figure 25
Figure 25. Figure 25: Veto vs GAGG photon count particle plot for the iso scenario. [PITH_FULL_IMAGE:figures/full_fig_p022_25.png]
Figure 26
Figure 26. Figure 26: Veto vs GAGG photon count histogram for the iso scenario. [PITH_FULL_IMAGE:figures/full_fig_p023_26.png]
Figure 27
Figure 27. Figure 27: Veto vs GAGG energy deposition particle plot for hemisphereIsoZ+Face. [PITH_FULL_IMAGE:figures/full_fig_p024_27.png]
Figure 28
Figure 28. Figure 28: Veto vs GAGG energy deposition histogram for hemisphereIsoZ+Face. [PITH_FULL_IMAGE:figures/full_fig_p024_28.png]
Figure 29
Figure 29. Figure 29: Veto vs GAGG photon count particle plot for hemisphereIsoZ+Face. [PITH_FULL_IMAGE:figures/full_fig_p025_29.png]
Figure 30
Figure 30. Figure 30: Veto vs GAGG photon count histogram for hemisphereIsoZ+Face. [PITH_FULL_IMAGE:figures/full_fig_p025_30.png]
Figure 31
Figure 31. Figure 31: Veto vs GAGG energy deposition particle plot for hemisphereIsoZ-Face. [PITH_FULL_IMAGE:figures/full_fig_p026_31.png]
Figure 32
Figure 32. Figure 32: Veto vs GAGG energy deposition histogram for hemisphereIsoZ-Face. [PITH_FULL_IMAGE:figures/full_fig_p026_32.png]
Figure 33
Figure 33. Figure 33: Veto vs GAGG photon count particle plot for hemisphereIsoZ-Face. [PITH_FULL_IMAGE:figures/full_fig_p027_33.png]
Figure 34
Figure 34. Figure 34: Veto vs GAGG photon count histogram for hemisphereIsoZ-Face. [PITH_FULL_IMAGE:figures/full_fig_p027_34.png]

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Reference graph

Works this paper leans on

12 extracted references · 9 canonical work pages

  1. [12]

    Smith, D. (2024). Monte Carlo Simulations of Solar Wind Detection by a CubeSat [Report]. 27

    work page 2024

  2. [1]

    Solomey, N., Folkerts, J., Meyer, H., Gimar, C., Novak, J., Doty, B., English, T., Buchele, L., Nelsen, A., McTaggart, R., & Christl, M. (2023). Concept for a space-based near-solar neutrino detector. Nuclear Instruments and Methods in Physics Research Sec- tion a Accelerators Spectrometers Detectors and Associated Equipment, 1049, 168064. https://doi.org...

    arXiv 2023

  3. [2]

    (2019, December 14)

    Connor, N. (2019, December 14). What is Delta E - E Detector - Telescope - Definition. Radiation Dosimetr https://www.radiation-dosimetry.org/what-is-delta-e-e- detector-telescope-definition/

    work page 2019

  4. [3]

    Reames, D. V. (2021). Solar Energetic Particles. In Lecture notes in physics. https://doi.org/10.1007/978-3-030-66402-2

    doi:10.1007/978-3-030-66402-2 2021

  5. [4]

    et al., Geant4 - A Simulation Toolkit, Nucl

    Agostinelli, S. et al., Geant4 - A Simulation Toolkit, Nucl. Instrum. Meth. A 506 (2003) 250-303

    work page 2003

  6. [5]

    Doty, B., Solomey, N., Folkerts, J., Hartsock, B., Meyer, H., Christl, M., Rodriguez- Otero, M., Kuznetsov, E., Wichita State University, & Marshall Space Flight Center, NASA. (2024). Gamma Ray Detection Efficiency of GAGG Crystal Scintillator Using Three Tagged Gamma Ray Techniques. ABC

    work page 2024

  7. [6]

    Novak, J. C. (2023, April 10). Pourable and Destroyable Cosmic Ray Radiation Shield for Spacecraft. arXiv.org. https://arxiv.org/abs/2304.09177

    work page Pith review arXiv 2023

  8. [7]

    Design and Testing of a 3U CubeSat to Test the In-situ Vetoing for the $\nu$SOL Solar Neutrino Detector

    Folkerts, J. (2022, October 14). Design and Testing of a 3U CubeSat to Test the In-situ Vetoing for the νSOL Solar Neutrino Detector. arXiv.org. https://arxiv.org/abs/2210.07975

    work page Pith review arXiv 2022

Show all 12 references
  1. [8]

    Leske, R.A., Mewaldt, R.A., Cohen, C.M.S. et al. Solar Isotopic Composition as Determined Using Solar Energetic Particles. Space Sci Rev 130, 195–205 (2007). https://doi.org/10.1007/s11214-007-9185-3

    2007 doi

  2. [9]

    McGuire, R., & Von Rosenvinge, T. (1984). The energy spectra of solar energetic particles. Advances in Space Research, 4(2–3), 117–125. https://doi.org/10.1016/0273- 1177(84)90301-6

    1984 doi

  3. [10]

    Desai, M., & Giacalone, J. (2016). Large gradual solar energetic particle events. Living Reviews in Solar Physics, 13(1). https://doi.org/10.1007/s41116-016-0002-5

    2016 doi

  4. [11]

    Team, R. (n.d.). About ROOT. ROOT. https://root.cern/about/

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