NuSTAR broad-band X-ray observational campaign of energetic pulsar wind nebulae in synergy with VERITAS, HAWC and Fermi gamma-ray telescopes
Bibliographic record
Abstract
We report recent progress on the ongoing NuSTAR observational campaign of 8 TeV-detected pulsar wind nebulae (PWNe). This campaign constitutes a major part of our NuSTAR study of some of the most energetic TeV sources in our galaxy detected by VERITAS and HAWC. NuSTAR is the first focusing X-ray telescope operating above 10 keV in space with sub-arcminute angular resolution. Broad-band X-ray imaging and spectroscopy data, obtained by NuSTAR, allow us to probe sub-PeV electron populations through detecting synchrotron X-ray radiation. Our targets include PeVatron candidates detected by HAWC, the Boomerang nebula, PWNe crushed by supernova remnant shocks (or relic PWNe), and G0.9+0.1 in the Galactic Center. Using Fermi-LAT data and available TeV data, we aim to provide a complete, multi-wavelength view of a diverse class of middle-aged (~10-100 kyrs old) PWNe. Our NuSTAR analysis detected hard X-ray emission from the Eel and Boomerang PWNe and characterized their broad-band X-ray spectra most accurately. We plan to apply both time-evolution and multi-zone PWN models to multi-wavelength spectral energy distribution (SED) data over the radio, X-ray, GeV, and TeV bands. In this proceeding, we will review our observational campaign and discuss the preliminary results for some PWNe.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.001 |
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".