CTAO LST–1 observations of magnetar SGR 1935+2154: Deep limits on sub-second bursts and persistent tera-electronvolt emission
Bibliographic record
Abstract
Context. The Galactic magnetar SGR 1935+2154 has exhibited prolific high-energy (HE) bursting activity in recent years. Aims. Investigating its potential tera-electronvolt counterpart could provide insights into the underlying mechanisms of magnetar emission and very high-energy (VHE) processes in extreme astrophysical environments. We aim to search for a possible tera-electronvolt counterpart to both its persistent and sub-second-scale burst emission. Methods. We analysed over 25 hour of observations from the Large-Sized Telescope prototype (LST−1) of the Cherenkov Telescope Array Observatory (CTAO) during periods of HE activity from SGR 1935+2154 in 2021 and 2022 to search for persistent emission. For bursting emission, we selected and analysed nine 0.1 s time windows centred around known short X-ray bursts, targeting potential sub-second-scale tera-electronvolt counterparts in a low-photon-statistics regime. Results. While no persistent or bursting emission was detected in our search, we establish upper limits for the tera-electronvolt emission of a short magnetar burst simultaneous to its soft gamma-ray flux. Specifically, for the brightest burst in our sample, the ratio between tera-electronvolt and X-ray flux is ≲10 −3 . Conclusions. The non-detection of either persistent or bursting tera-electronvolt emission from SGR 1935+2154 suggests that if such components exist, they may occur under specific conditions not covered by our observations. This aligns with theoretical predictions of VHE components in magnetar-powered fast radio bursts and the detection of MeV–GeV emission in giant magnetar flares. These findings underscore the potential of magnetars, fast radio bursts, and other fast transients as promising candidates for future observations in the low-photon-statistics regime with Imaging Atmospheric Cherenkov Telescopes, particularly with the CTAO.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".