The LOFAR Tied-Array All-Sky Survey (LOTAAS): Survey overview and initial pulsar discoveries
Bibliographic record
Abstract
We present an overview of the LOFAR Tied-Array All-Sky Survey (LOTAAS) for radio pulsars and fast transients. The survey uses the high-band antennas of the LOFAR Superterp, the dense inner part of the LOFAR core, to survey the northern sky ( δ > 0°) at a central observing frequency of 135 MHz. A total of 219 tied-array beams (coherent summation of station signals, covering 12 square degrees), as well as three incoherent beams (covering 67 square degrees) are formed in each survey pointing. For each of the 222 beams, total intensity is recorded at 491.52 μ s time resolution. Each observation integrates for 1 hr and covers 2592 channels from 119 to 151 MHz. This instrumental setup allows LOTAAS to reach a detection threshold of 1–5 mJy for periodic emission. Thus far, the LOTAAS survey has resulted in the discovery of 73 radio pulsars. Among these are two mildly recycled binary millisecond pulsars ( P = 13 and 33 ms), as well as the slowest-spinning radio pulsar currently known ( P = 23.5 s). The survey has thus far detected 311 known pulsars, with spin periods ranging from 4 ms to 5.0 s and dispersion measures from 3.0 to 217 pc cm −3 . Known pulsars are detected at flux densities consistent with literature values. We find that the LOTAAS pulsar discoveries have, on average, longer spin periods than the known pulsar population. This may reflect different selection biases between LOTAAS and previous surveys, though it is also possible that slower-spinning pulsars preferentially have steeper radio spectra. LOTAAS is the deepest all-sky pulsar survey using a digital aperture array; we discuss some of the lessons learned that can inform the approach for similar surveys using future radio telescopes such as the Square Kilometre Array.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".