Observation of the Crab Nebula with the Single-Mirror Small-Size Telescope stereoscopic system at low altitude
Bibliographic record
Abstract
The Single-Mirror Small-Size Telescope (SST-1M) stereoscopic system is composed of two Imaging Atmospheric Cherenkov Telescopes (IACTs) designed to deliver optimal performance for gamma-ray astronomy in the multi-TeV energy range. It features a 4-m 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 field of view (FoV), while minimizing optical aberrations. In 2022, two SST-1M telescopes were installed at the Ondřejov Observatory, Czech Republic at an altitude of 510 meters above sea level, 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 (of which 33 hours were in stereoscopic mode). In this work, we used the Crab Nebula observation to validate the expected performance of the instrument, as evaluated by Monte Carlo (MC) simulations that were 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° is 1 TeV for mono mode and 1.3 TeV for stereo mode. The energy and angular resolutions were approximately 20% and 0.18° for mono mode and 10% and 0.10° for stereo mode, respectively. We present an off-axis performance assessment of the instrument and a detailed study of the systematic uncertainties. The full simulation results for the telescope and its camera are compared to the data for the first time, enabling a deeper understanding of the SST-1M array performance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".