Searches for TeV emission from Northern Hemisphere pulsars with VERITAS
Bibliographic record
Abstract
The discovery of VHE emission from the Crab pulsar and, more recently, multi-TeV emission from the Vela pulsar have challenged our current understanding of the emission mechanisms of these sources. Studying pulsar emission at TeV energies allows us to understand the engines that power some of the most extreme accelerators in the Galaxy. We present recent highlights from the VERITAS pulsar program using nearly two decades of VERITAS data and novel high energy analysis techniques optimized for emission up to 100 TeV. This work begins to characterize how the emerging population of multi-TeV pulsars can be predicted from existing multi-wavelength observations. In particular, we highlight a search for VHE emission above 1 TeV using over 17 years of Crab pulsar data, which extends the high energy end of the existing VERITAS spectrum. Additionally, we search for both optical and multi-TeV emission from bright Vela-like pulsars, including analysis of over 200 hours of data on PSR J2229+6114, which powers the Boomerang pulsar wind nebula and is putatively associated with the ultra-high-energy source 1LHAASO J2229+5927u. We discuss these results in the context of the broader pulsar population and their impacts on the prospects of new pulsar discoveries with next-generation VHE instruments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".