PhysicsarXiv
Heuristic editor, no API keyVerdict: NotableProbing turbulence in the ionized interstellar medium using young pulsars. I. Dispersion measure variations
Temporal variations in the dispersion measure (DM) of pulsars probe fluctuations in the free-electron density of the ionized interstellar medium (IISM).
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Abstract
Temporal variations in the dispersion measure (DM) of pulsars probe fluctuations in the free-electron density of the ionized interstellar medium (IISM). While DM variations have been studied extensively in millisecond pulsars, young pulsars provide a complementary probe due to their lines of sight (LoSs) intersecting supernova remnants, pulsar wind nebulae, and other turbulent environments. However, systematic studies of DM variability in young pulsars remain limited. In this paper, We characterize the temporal DM variations of a large population of young pulsars to constrain the turbulence of the IISM along their LoSs and to investigate the physical origins of the observed variability. We analyzed 18 years of timing observations of 364 young pulsars obtained with the Murriyang/Parkes radio telescope, combining legacy data from the 21 cm Multibeam receiver with recent observations from the ultra-wideband low-frequency (UWL) receiver. Epoch-wise DM measurements were derived from sub-banded times of arrival, and the variability was characterized using linear trends and DM structure functions, which were compared with expectations for a Kolmogorov turbulence. Significant DM variations are detected in 89 pulsars in the UWL data and in 23 pulsars in the multibeam data, with 16 in the combined dataset showing significant trends. This represents one of the largest long-baseline studies of DM variability in pulsars. We find tentative evidence that the observed DM variations are predominantly consistent with Kolmogorov turbulence. PSRs J1105-6107 and J1829-1751 show estimated DM variations driven by periodic profile variability. We also identify 21 bright, slow pulsars exhibiting short-term DM variations that exceed expectations from the IISM.
The editor's rubric
| Dimension | Level | Weight | What that level means |
|---|---|---|---|
| Leverage | ███░░ 3 | 18% | A method or resource many groups across the field will adopt within a year. |
| Magnitude | ███░░ 3 | 20% | Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem. |
| Evidence | ███░░ 3 | 22% | Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data. |
| Novelty | ███░░ 3 | 22% | A genuinely new approach to an open problem. |
| Trajectory | ██░░░ 2 | 10% | Some room to improve with obvious engineering. |
| Stakes | ██░░░ 2 | 8% | Benefits a professional community (practitioners, clinicians, engineers). |
Editor’s rationale
Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: method (we report); gains (outperforms); novelty (open problem); verification (error bars).
How the score was computed
- Merit
- 5.6 / 10
- Adjusted merit
- 4.6 / 10
- Attention
- 4%
- Freshness
- 93%
- Citations1 (reference 20, via openalex, Oct 7, 2026, 07:29 UTC)