Hunting for Radio Emission from the Intermittent Pulsar J1107-5907 at Low Frequencies
Bibliographic record
Abstract
Abstract Rare intermittent pulsars pose some of the most challenging questions surrounding the pulsar emission mechanism, but typically have relatively minimal low-frequency (≲300 MHz) coverage. We present the first low-frequency detection of the intermittent pulsar J1107–5907 with the Murchison Widefield Array (MWA) at 154 MHz and the simultaneous detection from the recently upgraded Molonglo Observatory Synthesis Telescope (UTMOST) at 835 MHz, as part of an ongoing observing campaign. During a 30 minute simultaneous observation, we detected the pulsar in its bright emission state for approximately 15 minutes, where 86 and 283 pulses were detected above a signal-to-noise threshold of 6 with the MWA and UTMOST, respectively. Of the detected pulses, 51 had counterparts at both frequencies and exhibited steep spectral indices for both the bright main pulse component and the precursor component. We find that the bright state pulse energy distribution is best parameterized by a log-normal distribution at both frequencies, contrary to previous results that suggested a power law distribution. Further low-frequency observations are required in order to explore in detail aspects such as pulse-to-pulse variability and intensity modulations, as well as to better constrain the signal propagation effects due to the interstellar medium and intermittency characteristics at these frequencies. The spectral index, extended profile emission covering a large fraction of pulse longitude, and the broadband intermittency of PSR J1107–5907 suggest that future low-frequency pulsar searches—for instance, those planned with SKA-Low—will be in an excellent position to find and investigate new pulsars of this type.
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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".