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Observation of the Crab Nebula with the Single-Mirror Small-Size Telescope stereoscopic system at low altitude

T0 review · 3 major / 7 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read The two SST-1M telescopes, at 510 m altitude, detect the Crab Nebula and reproduce its TeV spectrum, validating the full Monte Carlo model of the low-altitude array.

desk verdict Solid commissioning paper: real Crab detection and unusually thorough systematics, but the 'MC validation' is partly a consistency check because the MC is tuned to the data and the aerosol model is borrowed from a site 45 km away. read the letter →

arxiv 2506.01733 v2 pith:ZKMQWG62 submitted 2025-06-02 astro-ph.IM astro-ph.HE

classification astro-ph.IMastro-ph.HE
keywords SST-1MimagingatmosphericCherenkovtelescopesCrabNebulasiliconphotomultipliersstereoscopicobservationsMonteCarlovalidationmulti-TeVgamma-rayastronomylow-altitudeobservatory
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

Two 4-meter Imaging Atmospheric Cherenkov Telescopes with silicon-photomultiplier cameras, installed at the low altitude of 510 meters above sea level, have detected the Crab Nebula in both single-telescope and stereoscopic modes. The paper's central claim is that the measured very-high-energy spectrum of the Crab matches the results of established TeV observatories within uncertainties, and that a carefully tuned Monte Carlo model of the atmosphere, optics, camera, and electronics describes the real data from trigger level up to reconstructed gamma-ray images. If true, the SST-1M array works as a multi-TeV gamma-ray instrument despite the extra atmospheric attenuation at low altitude, with an analysis-level energy threshold of 1 TeV in mono and 1.3 TeV in stereo, stereo energy resolution around 10%, and an acceptance that stays nearly flat out to 2.5 degrees off axis. The Crab observation is used as a standard-candle validation: agreement between data and simulation is shown in event rates, shower-image parameters, angular distributions, and the derived spectral energy distribution.

What carries the argument

The load-bearing mechanism is a full end-to-end Monte Carlo chain, calibrated to the two specific telescopes: CORSIKA generates the air showers, sim_telarray ray-traces the Cherenkov light through a Davies-Cotton 4-meter mirror and the SiPM camera, and the atmospheric model combines ERA5 molecular density profiles with MODTRAN aerosol transmission using a vertical aerosol optical depth of 0.05 taken from a daytime sun photometer 45 km away. The camera model is tuned against dark-run photoelectron spectra (Borel-distributed crosstalk), muon-ring images for optical efficiency, and a measured voltage-drop model for SiPM behavior under night-sky background. The tuned simulations produce instrument response functions and train random-forest (machine-learning) regressors and a gamma-hadron classifier; the Crab Nebula data then serve as the independent check that the whole chain holds.

What would settle it

Put an on-site lidar or sun/moon photometer at Ondrejov during a repeat Crab campaign and measure the vertical aerosol optical depth on the same nights the telescopes observe. If the true $V_{\rm AOD}$ differs from 0.05 by 0.1, the reconstructed flux normalization would shift by about 18–19%, comparable to or larger than the quoted total systematics; a repeat measurement that refuses to reproduce the Crab SED under the assumed atmosphere would falsify the energy-scale calibration, while agreement under measured $V_{\rm AOD}$ would confirm it.

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Extended reading notes

Core claim

The discovery claimed is that a stereoscopic pair of small-size IACTs operating at 510 m above sea level can observe the Crab Nebula and reconstruct its multi-TeV spectrum, and that the instrument's complete simulation—including the SiPM camera response, Davies-Cotton optics, atmospheric transmission, and machine-learning energy and direction reconstruction—reproduces the measured Crab signal without renormalization. Using 33 hours of stereo data (25 hours after quality cuts) and mono data from both telescopes, the fit of a power law $\mathrm{d}\phi/\mathrm{d}E = \phi_0 (E/E_0)^{-\Gamma}$ over 2.5–50 TeV gives flux normalizations at $E_0 = 7$ TeV of $(1.76–2.02)\times 10^{-13}\,\mathrm{cm}^{-2}\mathrm{s}^{-1}\mathrm{TeV}^{-1}$ and spectral indices $\Gamma = 2.68–2.78$ for the three datasets, consistent within uncertainties with published results from major TeV observatories. The same comparison validates the energy and angular resolutions, the background model, and the off-axis acceptance predicted by Monte Carlo.

Load-bearing premise

The load-bearing premise is that the daytime aerosol measurement taken at a site 45 km away, averaged to a single value of 0.05 for the whole campaign, faithfully represents the vertical aerosol profile over Ondrejov on the actual observation nights; if that column or its height distribution is wrong, the energy scale shifts by about 10% per 0.1 of optical depth and the entire Monte Carlo validation moves with it.

Editorial extensions

If this is right

  • If the Monte Carlo model is right, the quoted instrument response functions can be trusted for future science: mono energy threshold 1 TeV, stereo 1.3 TeV, energy resolution ~20% mono and ~10% stereo, and angular resolution 0.18° mono and 0.10° stereo.
  • Stereo observation improves flux sensitivity by about a factor of two over mono, reaching roughly 7% of the Crab flux in 50 hours above the energy threshold.
  • The acceptance stays within about 10% of flat out to 2.5° off axis, so extended sources and poorly localized transients can be observed without a strong loss of performance.
  • The validated pipeline can produce spectra and sky maps of other sources in the multi-TeV range from this low-altitude site, using the MC-derived response functions directly.
  • The current systematic budget—under 10% in energy scale, about 22–23% in flux normalization, and 3–6% in spectral index—sets the precision of the instrument, with the dominant terms being the aerosol assumption and night-sky-background variability.

Reading between the lines

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

  • Beyond the paper: a dedicated on-site nocturnal aerosol monitor (lidar or photometer) would directly test the strongest assumption; if it confirms $V_{\rm AOD} \approx 0.05$, the energy-scale systematics would be frozen, and if it does not, the 18–19% flux-normalization uncertainty would need to be revised upward.
  • Beyond the paper: the same dark-run and muon-ring tuning methodology could be transferred to other SiPM-based IACT cameras, potentially providing a uniform calibration strategy for next-generation arrays.
  • Beyond the paper: the flat off-axis acceptance suggests the SST-1M pair could serve as a survey instrument for extended Galactic sources, but a dedicated pointed campaign would be needed to demonstrate that capability.
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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 / 7 minor

Summary. The paper presents the first Crab Nebula observations with the two SST-1M telescopes at Ondřejov, 510 m a.s.l., using 46/52 h of mono data and 33 h of stereo data collected between September 2023 and March 2024. The authors calibrate the SiPM cameras from dark runs and pedestals, tune the optical efficiency with muon rings, adopt a fixed V_AOD = 0.05 atmosphere from a daytime sun-photometer 45 km away, and produce a large CORSIKA + sim_telarray MC production with per-telescope NSB levels. Random-forest regressors and classifiers are used for energy, direction, and gamma/hadron separation; IRFs are derived and applied in gammapy to fit a power-law Crab spectrum over 2.5-50 TeV and to create a significance skymap. The claimed results are analysis-level energy thresholds of 1 TeV (mono) and 1.3 TeV (stereo), energy resolutions of about 20% and 10%, angular resolutions of 0.18° and 0.10°, a factor ~2 stereo sensitivity improvement, and a Crab SED in good agreement with previous instruments within the quoted systematics. The systematic budget is reported as <10% in energy scale, 22-23% in flux normalization, and 3-6% in spectral index.

Significance. The paper has real strengths: an unusually detailed calibration chain (dark-run photoelectron spectra, NSB-induced voltage-drop model, muon-ring optical-efficiency monitoring), a very large MC production, an open-source analysis pipeline (sst1mpipe) with GADF-compliant outputs, MC-data comparisons at several analysis levels, and a dedicated off-axis performance study. If the performance claims hold, the paper is a valuable demonstration that a compact, low-altitude, SiPM-based stereo IACT can operate in the multi-TeV band with controlled systematics. The main reservation is that the external validation and the energy scale rest on the untested transfer of daytime V_AOD from Košetice, 45 km away; the paper's own sensitivity analysis shows this term dominates the flux-normalization budget. The claim of agreement with other observatories is also qualitative and needs a quantitative compatibility measure.

major comments (3)
  1. [Section 2.4, Section 8.1, Table 2] The fixed V_AOD = 0.05 used for the entire campaign is derived from daytime Sun-photometer measurements at Košetice, 45 km from Ondřejov, with no on-site nighttime validation. Section 8.1 states that a 0.1 change in V_AOD shifts the light/energy scale by about 10%, and Table 2 converts the assumed 0.05 V_AOD uncertainty into 5% energy-scale and 18-19% flux-normalization systematics. An unquantified transfer error of order 0.1 would therefore move the Crab flux normalization by an amount comparable to the total 22-23% systematic budget and could invalidate the claimed agreement with other observatories. The limitation is acknowledged in the text, but no quantitative test of the transfer assumption is provided. I ask the authors to add a concrete cross-check, for example comparing the run-to-run event-rate stability (Figure 14) or a Cherenkov-transparency metric with the Košetice V_AOD time series, or repeating the Crab spectral fit with IRFs generated at V_AOD = 0.10 and 0.15 and reporting the resulting flux shift.
  2. [Section 6.2, Figure 16] The abstract and Section 9 conclude that the measured Crab SED is in good agreement with other observatories, but the evidence is a visual overlap of bands and points. Because the total flux-normalization uncertainty is 22-23% and the statistical errors are sizeable, the agreement could be trivially satisfied. Please provide a quantitative measure (e.g., chi2/ndof or pulls of the stereo flux points relative to a reference Crab spectrum, propagated with the systematic covariances) to support the claim. This is load-bearing because the SED comparison is the main external validation of the MC model.
  3. [Section 7, Figures 15, 18-20] The MC-data validation is partly a consistency check: the MC is tuned using dark-run spectra (Figure 1), pedestal NSB distributions (Figure 5), muon-ring light yield (Figure 3), and the intensity threshold is chosen from the data/MC rate comparison (Figure 15). Consequently those comparisons are internal consistency checks rather than independent predictions. The only external benchmarks are the Crab excess rates and the SED, whose interpretation depends on the V_AOD energy scale. Please state explicitly which comparisons are predictive rather than tuned, and give the statistical precision with which the Crab excess rate constrains the gamma-ray effective area and the energy scale.
minor comments (7)
  1. [Section 1] The phrase 'thus are copped for in the analysis' should read 'thus are accounted for in the analysis'.
  2. [Section 2.1.2] The sentence 'as it was observed after operation of SST-1M-1 that lowering R_bias would decrease the impact of their order to lower the effects of NSB' is garbled and should be rewritten.
  3. [Section 8.3, Eq. (4)] Equation (4) is missing a square root and has unbalanced parentheses; it should read ΔΓ = 2 sqrt((5%/SBR_LE)^2 + (5%/SBR_HE)^2) / log(E_max/E_min), or the equivalent with the intended parentheses.
  4. [Section 6.3] The line giving the best-fit coordinates has unbalanced parentheses: '((α2000 = 83.62°, δ2000 = 21.99°) ± 0.02°' needs an extra closing parenthesis.
  5. [References] Duplicate entries appear for Aleksić et al. (2016), Bose et al. (2022), and Heller et al. (2017); these should be consolidated.
  6. [Section 6.1/6.2] Please clarify the exact livetimes used in the spectral analysis: 46/52 h raw, 33/27 h mono, and 25 h stereo are quoted, but the text should state explicitly why the mono livetimes differ between telescopes and which livetime enters the flux normalization.
  7. [Section 5.4] The abbreviation 'C.U.' is used for Crab units; please define it at first use.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the MC is tuned to calibration data, and the Crab Nebula comparison is an external benchmark.

full rationale

The paper's derivation chain is not circular. The MC model is explicitly tuned to independent calibration inputs: dark-run photoelectron spectra (Sec. 2.1.1), muon-ring optical efficiency (Sec. 2.2), and pedestal/NSB levels (Fig. 5). The paper does not present those comparisons as predictions; they are consistency checks after tuning. The central validation claim rests on the Crab Nebula excess: Sec. 7 compares background-subtracted theta^2, intensity, and gammaness distributions of the Crab excess to MC reweighted on an external Crab spectrum (Aleksic et al. 2015) with no normalization free parameter, and Sec. 6.2 fits the SED and compares it to MAGIC, VERITAS, HAWC, LHAASO, LST, and H.E.S.S. measurements. None of these external data are used to adjust the physics or instrument model. The transferred daytime V_AOD from Kosetice (Sec. 2.4) is an external atmospheric input, and its 0.05 uncertainty is propagated into the energy-scale and flux-normalization systematics (Sec. 8.1); this is a sensitivity study, not a definitional identity. Self-citations to Alispach et al. 2025 and Nagai et al. 2019 supply the prior instrument model and SiPM voltage-drop behavior, but they are not load-bearing in a circular way because the present work re-establishes the needed response against muon and pedestal data and because the central performance claim is benchmarked on the Crab Nebula, an external standard candle. Score 1 reflects the presence of normal self-citations without any reduction of the central claim to its inputs.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

No new particles, forces, or physical entities are introduced; the paper is an instrument characterization. The free parameters listed are MC inputs and analysis cuts that the reported performance depends on, the most consequential being the atmospheric aerosol value and the optical efficiency normalization.

free parameters (6)
  • MC NSB rate per pixel = SST-1M-1: 94 MHz; SST-1M-2: 120 MHz
    Set to reproduce baseline standard deviations and pedestal charge distributions in data (Section 3, Fig. 5).
  • MC optical efficiency scale = Tuned to muon-ring charge vs radius, about 185-215 p.e. at 1.2 deg; about 2% decline over campaign
    Effective optical throughput in sim_telarray is adjusted per telescope to match muon light measurements (Section 2.2, Figs. 3-4).
  • Atmospheric V_AOD constant = 0.05
    Fixed period-wide value from Košetice photometer, 45 km away, daytime mean; energy scale sensitivity about 10% per 0.1 V_AOD (Sections 2.4, 8.1).
  • Analysis intensity threshold = 45 p.e.
    Post-hoc cut chosen to put data and MC on the same analysis threshold after comparing run intensity distributions (Section 6.1).
  • Signal-region theta cut = 0.20 deg mono; 0.12 deg stereo
    Independent of energy, optimized on MC for best detection significance; used in the spectral analysis (Section 6.2).
  • Energy-dependent gammaness cut = 60% gamma efficiency
    Optimized on MC to keep a fixed gamma fraction in all energy bins; used for IRFs and Crab analysis (Sections 5, 6.2).
assumptions (5)
  • domain assumption Crab Nebula is a stable VHE standard candle with known position and spectrum.
    Used as the external benchmark for energy scale, pointing, and MC validation; position taken from H.E.S.S. 2020 and spectrum weighting from MAGIC 2016 (Sections 1, 6.2).
  • domain assumption CORSIKA, sim_telarray, and MODTRAN correctly model air showers, Cherenkov propagation, optics, and SiPM response.
    All performance numbers and IRFs are derived from these simulations; the paper validates them indirectly through dark runs, muon rings, and Crab observations (Sections 2-5).
  • domain assumption Atmospheric conditions at Ondrejov during the campaign are represented by a constant V_AOD of 0.05 and a single ERA5 seasonal profile.
    No onsite aerosol monitor; values borrowed from a site 45 km away and daytime measurements, with acknowledged energy-scale systematics (Section 2.4).
  • domain assumption Reflected-region and ring background methods assume radially symmetric acceptance and correct background modeling.
    Used for spectral and skymap analyses (Sections 6.2, 6.3); tests of OFF-region homogeneity are limited by statistics.
  • domain assumption SiPM gain, PDE, and crosstalk voltage-drop behavior measured for SST-1M-1 (Nagai et al. 2019) applies to both cameras with their different bias resistors.
    The NSB correction relies on this model, validated with muon data under different NSB conditions (Section 2.1.2).

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Cite this review

Pith. "Pith review of Observation of the Crab Nebula with the Single-Mirror Small-Size Telescope stereoscopic system at low altitude." pith.science (2026). https://pith.science/paper/ZKMQWG62

@misc{pith2026250601733,
  author       = {Pith},
  title        = {Pith review of: Observation of the Crab Nebula with the Single-Mirror Small-Size Telescope stereoscopic system at low altitude},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ZKMQWG62}},
  note         = {Machine review of arXiv:2506.01733}
}
abstract

The Single-Mirror Small-Size Telescope (SST-1M) stereoscopic system is composed of two Imaging Atmospheric Cherenkov Telescopes (IACTs) designed for optimal performance for gamma-ray astronomy in the multi-TeV energy range. It features a 4-meter-diameter tessellated mirror dish and an innovative SiPM-based camera. Its optical system features a 4-m diameter spherical mirror dish based on the Davies-Cotton design, maintaining a good image quality over a large FoV while minimizing optical aberrations. In 2022, two SST-1M telescopes were installed at the Ond\v{r}ejov Observatory, Czech Republic, at an altitude of 510 meters above sea level, and have been collecting data for commissioning and astronomical observations since then. We present the first SST-1M observations of the Crab Nebula, conducted between September 2023 and March 2024 in both mono and stereoscopic modes. During this observation period, 46 hours for the SST-1M-1 and 52 hours for the SST-1M-2 were collected for which 33 hours are in stereoscopic mode. We use the Crab Nebula observation to validate the expected performance of the instrument, as evaluated by Monte Carlo simulations carefully tuned to account for instrumental and atmospheric effects. We determined that the energy threshold at the analysis level for the zenith angles below $30^\circ$ is 1 TeV for mono mode and 1.3 TeV for stereo mode. The energy and angular resolutions are approximately 20% and $0.18^\circ$ for mono mode and 10% and $0.10^\circ$ for stereo mode, respectively. We present the off-axis performance of the instrument and a detailed study of systematic uncertainties. The results of a full simulation of the telescope and its camera is compared to the data for the first time, allowing a deep understanding of the SST-1M array performance.

Figures

Figures reproduced from arXiv: 2506.01733 by the authors.

Figure 1
Figure 1. Comparison between data and MC of the normalized (to [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Left: Relation between muon ring radius and ADC counts under various NSB conditions for SST-1M-1. Right: Behavior of measured muon ring charge as a function of the baseline shift induced by the NSB. Blue dotted and orange dashed lines represent the expected behavior given in Nagai et al. (2019) for SST-1M-1 and SST-1M-2, respectively. Filled blue (SST-1M-1) and empty orange (SST-1M-2) markers represent the fitted es… view at source ↗
Figure 3
Figure 3. Charge of muon images as a function of the fitted ring ra [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figures from the paper (15 more)
Figure 5
Figure 5. Figure 5: Left: Distribution of the averaged standard deviation of the baselines for SST-1M-1 (dashed line) and SST-1M-2 (solid line). The vertical lines represent the value assumed in the MC model of SST-1M-1 (94 MHz/pixel) and SST-1M-2 (120 MHz/pixel). The vertical axis repres…
Figure 6
Figure 6. Figure 6: Gini importance for different RFs for the SST-1M-1. The features used for the reconstruction: log of the intensity, width, length, width/length ratio (wl), timing slope, skewness, kurtosis, leakage, and coordinates of the shower center of gravity in the FoV (x,y). Heig…
Figure 7
Figure 7. Figure 7: ROC curve of the RF gamma-hadron classifier for 30 [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]
Figure 8
Figure 8. Figure 8: Left: Differential rate of point-like gamma rays with Crab Nebula spectrum in mono and stereo for 20◦ zenith angle. Event rates for different stages of the analysis are shown: All triggered events (solid line), all events that survived cleaning (dashed line), events th…
Figure 9
Figure 9. Figure 9: Energy resolution (left) and energy bias (right) for 30◦ (solid line) and 50◦ (dotted line) zenith angles evaluated using on￾axis point-like gammas for testing. Line colors represent different regimes of observations. For the sake of clarity, only results for SST-1M-1 …
Figure 10
Figure 10. Figure 10: Angular resolution for 30◦ (solid line) and 50◦ (dotted line) zenith angles evaluated on testing on-axis point-like gam￾mas. Line colors represent different regimes of observations. For the sake of clarity, only results for SST-1M-1 are shown in mono, as both telescop…
Figure 12
Figure 12. Figure 12: Simulated gamma-ray rate from the Crab Nebula and [PITH_FULL_IMAGE:figures/full_fig_p013_12.png]
Figure 13
Figure 13. Figure 13: Integral sensitivity for 50 hours of observation ( [PITH_FULL_IMAGE:figures/full_fig_p014_13.png]
Figure 14
Figure 14. Figure 14: Left: Run-averaged rate of mono events with intensity above 200 p.e., corrected for cos(zenith angle). Center: Run-averaged fraction of pedestal events that survived the tailcut cleaning. Right: Run-averaged fraction of pixels with increased tailcuts. The solid blue l…
Figure 15
Figure 15. Figure 15: Per-run rates of the event intensities (i.e., only events which survived cleaning contribute to the distributions) for SST-1M [PITH_FULL_IMAGE:figures/full_fig_p015_15.png]
Figure 16
Figure 16. Figure 16: Left: SED of the Crab Nebula measured with SST-1M telescopes. Different color bands represent the best-fitting spectra for the SST-1M-1 mono (blue), SST-1M-2 mono (yellow), and SST-1M stereo (green) datasets. Right: Stereo flux points derived from the PL spectral mode…
Figure 17
Figure 17. Figure 17: Left: Excess map of the Crab Nebula region within a region of 1.5◦ ×1.5 ◦ . The best-fit position of the excess is marked with a “+" symbol, and the expected position of the Crab Nebula, as measured in H. E. S. S. Collaboration (2020), is indicated by the green “×". T…
Figure 18
Figure 18. Figure 18: θ 2 distributions for Crab Nebula excess event rates compared with point-like gamma MC in different bins of Hillas intensi￾ties. Top row: SST-1M-1 mono, Bottom row: stereo. attenuation medium for emitted Cherenkov photons. Using MC simulated with a fixed model of the …
Figure 19
Figure 19. Figure 19: Excess event rates binned in Hillas intensity for SST-1M-1 ( [PITH_FULL_IMAGE:figures/full_fig_p018_19.png]
Figure 20
Figure 20. Figure 20: Comparison of gammaness distribution for MC simulations and Crab Nebula excess events in di [PITH_FULL_IMAGE:figures/full_fig_p018_20.png]

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Reference graph

Works this paper leans on

48 extracted references · 39 canonical work pages · cited by 2 Pith papers

  1. [1]

    A., Ackermann, M., Ajello, M., et al

    Abdo, A. A., Ackermann, M., Ajello, M., et al. 2011, Science, 331, 739

  2. [2]

    U., Albert, A., Alfaro, R., et al

    Abeysekara, A. U., Albert, A., Alfaro, R., et al. 2019, The Astrophysical Journal, 881, 134

  3. [3]

    2024, A&A, 686, A308 Aleksi´c, J., Ansoldi, S., Antonelli, L

    Aharonian, F., Ait Benkhali, F., Aschersleben, J., et al. 2024, A&A, 686, A308 Aleksi´c, J., Ansoldi, S., Antonelli, L. A., et al. 2016, Astroparticle Physics, 72, 76 Aleksi´c, J., Ansoldi, S., Antonelli, L. A., et al. 2015, Journal of High Energy Astrophysics, 5, 30 Aleksi´c, J. et al. 2016, Astroparticle Physics, 72, 76

  4. [4]

    2024, Phys

    Alemanno, F., Altomare, C., An, Q., et al. 2024, Phys. Rev. D, 109, L121101

  5. [5]

    2025, Journal of Cosmology and Astroparticle Physics, 2025, 047

    Alispach, C., Araudo, A., Balbo, M., et al. 2025, Journal of Cosmology and Astroparticle Physics, 2025, 047

  6. [6]

    R., et al

    Alispach, C., Borkowski, J., Cadoux, F. R., et al. 2020, Journal of Instrumenta- tion, 15, P11010

  7. [7]

    2013, Journal of Instrumentation, 8, P06008

    Anderhub, H., Backes, M., Biland, A., et al. 2013, Journal of Instrumentation, 8, P06008

  8. [8]

    B., Abdo, A

    Atwood, W. B., Abdo, A. A., Ackermann, M., et al. 2009, ApJ, 697, 1071

Show all 48 references
  1. [9]

    2007, A&A, 466, 1219

    Berge, D., Funk, S., & Hinton, J. 2007, A&A, 466, 1219

  2. [10]

    2014, in 2014 6th Workshop on Hyper- spectral Image and Signal Processing: Evolution in Remote Sensing (WHIS- PERS), 1–4 Bernlöhr, K

    Berk, A., Conforti, P., Kennett, R., et al. 2014, in 2014 6th Workshop on Hyper- spectral Image and Signal Processing: Evolution in Remote Sensing (WHIS- PERS), 1–4 Bernlöhr, K. 2000, Astroparticle Physics, 12, 255 Bernlöhr, K. 2008, Astroparticle Physics, 30, 149

  3. [11]

    1997, Theoretical and Applied Climatology, 57, 95

    Blumthaler, M., Ambach, W., & Blasbichler, A. 1997, Theoretical and Applied Climatology, 57, 95

  4. [12]

    R., Majumdar, P., & Acharya, B

    Bose, D., Chitnis, V . R., Majumdar, P., & Acharya, B. S. 2022, European Physi- cal Journal Special Topics, 231, 3

  5. [13]

    R., Majumdar, P., & Shukla, A

    Bose, D., Chitnis, V . R., Majumdar, P., & Shukla, A. 2022, Eur. Phys. J. Spec. Top., 231, 27

  6. [14]

    2001, Mach

    Breiman, L. 2001, Mach. Learn., 45, 5–32

  7. [15]

    2024, ApJS, 271, 25

    Cao, Z., Aharonian, F., An, Q., et al. 2024, ApJS, 271, 25

  8. [16]

    Davies, J. M. & Cotton, E. S. 1957, Solar Energy, 1, 16 de Naurois, M. & Mazin, D. 2015, Comptes Rendus Physique, 16, 610 de Oña Wilhelmi, E., López-Coto, R., Aharonian, F., et al. 2024, Nature Astron- omy, 8, 425

  9. [17]

    M., Linhoff, M., & Sitarek, J

    Dominik, R. M., Linhoff, M., & Sitarek, J. 2023, arXiv e-prints, arXiv:2309.16488

  10. [18]

    Donath, A. et al. 2021, gammapy/gammapy: v.0.19

  11. [19]

    Fegan, D. J. 1997, Journal of Physics G: Nuclear and Particle Physics, 23, 1013

  12. [20]

    & Artemis-Whipple Collaboration

    Fleury, P. & Artemis-Whipple Collaboration. 1991, International Cosmic Ray Conference, 2, 595, conference Name: International Cosmic Ray Conference ADS Bibcode: 1991ICRC....2..595F

  13. [21]

    P., Stepanian, A

    Fomin, V . P., Stepanian, A. A., Lamb, R. C., et al. 1994, Astroparticle Physics, 2, 137

  14. [22]

    2019, International Journal of Modern Physics D, 28, 1930022

    Gabici, S., Evoli, C., Gaggero, D., et al. 2019, International Journal of Modern Physics D, 28, 1930022

  15. [23]

    2017, in European Physical Journal Web of Conferences, V ol

    Gaug, M. 2017, in European Physical Journal Web of Conferences, V ol. 144, European Physical Journal Web of Conferences, 01003

  16. [24]

    Gaug, M., Fegan, S., Mitchell, A. M. W., et al. 2019, The Astrophysical Journal Supplement Series, 243, 11, publisher: The American Astronomical Society H. E. S. S. Collaboration. 2020, Nature Astronomy, 4, 167 H. E. S. S. Collaboration, Abramowski, A., Aharonian, F., et al. 2...

  17. [25]

    2014, Astroparticle Physics, 54, 25

    Hahn, J., de los Reyes, R., Bernlöhr, K., et al. 2014, Astroparticle Physics, 54, 25

  18. [26]

    N., Schatz, G., & Thouw, T

    Heck, D., Knapp, J., Capdevielle, J. N., Schatz, G., & Thouw, T. 1998, COR- SIKA: a Monte Carlo code to simulate extensive air showers., Report FZKA 6019, Forschungszentrum Karlsruhe

  19. [27]

    2017, European Physical Journal C, 77, 47

    Heller, M., Schioppa, E., J., Porcelli, A., et al. 2017, European Physical Journal C, 77, 47

  20. [28]

    Heller, M. et al. 2017, The European Physical Journal C, 77, 47 H.E.S.S. Collaboration, Abdalla, H., Abramowski, A., et al. 2018, Astron. As- trophys., 612, A1

  21. [29]

    Hillas, A. M. 1985, in International Cosmic Ray Conference, V ol. 3, 19th Inter- national Cosmic Ray Conference (ICRC19), V olume 3, 445

  22. [30]

    1999, Astropart

    Hofmann, W., Jung, I., Konopelko, A., et al. 1999, Astropart. Phys., 122, 135

  23. [31]

    Jurysek, J. et al. 2025, SST-1M-collaboration/sst1mpipe: v0.7.3

  24. [32]

    Kosack, K. et al. 2021, cta-observatory/ctapipe: v0.12.0

  25. [33]

    W., Buckley, J

    Lessard, R. W., Buckley, J. H., Connaughton, V ., & Le Bohec, S. 2001, Astropar- ticle Physics, 15, 1 LHAASO Collaboration, Cao, Z., Aharonian, F., et al. 2021, Science, 373, 425

  26. [34]

    Li, T. P. & Ma, Y . Q. 1983, ApJ, 272, 317

  27. [35]

    M., et al

    Linhoff, M., Peresano, M., Dominik, R. M., et al. 2024, cta-observatory/pyirf: v0.11.0 – 2024-05-14

  28. [36]

    Lopez-Coto, R. et al. 2022, cta-observatory/cta-lstchain: v0.9.4 MAGIC Collaboration, Acciari, V . A., Ansoldi, S., et al. 2020, A&A, 635, A158

  29. [37]

    & VERITAS Collaboration

    Meagher, K. & VERITAS Collaboration. 2015, in International Cosmic Ray

  30. [38]

    d., et al

    Nagai, A., Alispach, C., V olpe, D. d., et al. 2019, Journal of Instrumentation, 14, P12016

  31. [39]

    Nigro, C. et al. 2021, Universe, 7

  32. [40]

    2011, Journal of Machine Learning Research, 12, 2825

    Pedregosa, F., Varoquaux, G., Gramfort, A., et al. 2011, Journal of Machine Learning Research, 12, 2825

  33. [41]

    A., Connors, A., Kashyap, V

    Protassov, R., van Dyk, D. A., Connors, A., Kashyap, V . L., & Siemiginowska, A. 2002, ApJ, 571, 545 Pühlhofer, G., Bolz, O., Götting, N., et al. 2003, Astroparticle Physics, 20, 267

  34. [42]

    Serrano, J. et al. 2009, in ICALEPCS, Kobe, Japan, 12th International Confer- ence on Accelerator and Large Experimental Physics Control Systems

  35. [43]

    2022, Galaxies, 10, 21

    Sitarek, J. 2022, Galaxies, 10, 21

  36. [44]

    2019, As- troparticle Physics, 109, 12

    Stefanik, S., Nosek, D., de los Reyes, R., Gaug, M., & Travnicek, P. 2019, As- troparticle Physics, 109, 12

  37. [45]

    2011, Science, 331, 736

    Tavani, M., Bulgarelli, A., Vittorini, V ., et al. 2011, Science, 331, 736

  38. [46]

    2012, Nuclear Instruments and Methods in Physics Research A, 695, 247

    Vinogradov, S. 2012, Nuclear Instruments and Methods in Physics Research A, 695, 247

  39. [47]

    C., Cawley, M

    Weekes, T. C., Cawley, M. F., Fegan, D. J., et al. 1989, ApJ, 342, 379

  40. [48]

    Wilks, S. S. 1938, Annals Math. Statist., 9, 60 Article number, page 21 of 21

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