A Millisecond Pulsar Discovery in a Survey of Unidentified Fermi γ-Ray Sources with LOFAR
Bibliographic record
Abstract
Abstract Using LOFAR, we have performed a very-low-frequency (115−155 MHz) radio survey for millisecond pulsars (MSPs). The survey targeted 52 unidentified Fermi γ-ray sources. Employing a combination of coherent and incoherent dedispersion, we have mitigated the dispersive effects of the interstellar medium while maintaining sensitivity to fast-spinning pulsars. Toward 3FGL J1553.1+5437 we have found PSR J1552+5437, the first MSP to be discovered (through its pulsations) at a radio frequency <200 MHz. PSR J1552+5437 is an isolated MSP with a 2.43 ms spin period and a dispersion measure of 22.9 pc cm−3. The pulsar has a very steep radio spectral index ( 2.8 ± 0.4). We obtain a phase-connected timing solution combining the 0.74 years of radio observations with γ-ray photon arrival times covering 7.5 years of Fermi observations. We find that the radio and γ-ray pulse profiles of PSR J1552+5437 appear to be nearly aligned. The very steep spectrum of PSR J1552+5437, along with other recent discoveries, hints at a population of radio MSPs that have been missed in surveys using higher observing frequencies. Detecting such steep spectrum sources is important for mapping the population of MSPs down to the shortest spin periods, understanding their emission in comparison to slow pulsars, and quantifying the prospects for future surveys with low-frequency radio telescopes like SKA-Low and its precursors.
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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 | 0.001 | 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) | 0.001 | 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".