Quantifying ionospheric effects on time-domain astrophysics with the Murchison Widefield Array
Bibliographic record
Abstract
Refraction and diffraction of incoming radio waves by the ionosphere induce time variability in the angular positions, peak amplitudes and shapes of radio sources, potentially complicating the automated cross-matching and identification of transient and variable radio sources. In this work, we empirically assess the effects of the ionosphere on data taken by the Murchison Widefield Array (MWA) radio telescope. We directly examine 51 h of data observed over 10 nights under quiet geomagnetic conditions (global storm index Kp < 2), analysing the behaviour of short-time-scale angular position and peak flux density variations of around ten thousand unresolved sources. We find that while much of the variation in angular position can be attributed to ionospheric refraction, the characteristic displacements (10–20 arcsec) at 154 MHz are small enough that search radii of 1–2 arcmin should be sufficient for cross-matching under typical conditions. By examining bulk trends in amplitude variability, we place upper limits on the modulation index associated with ionospheric scintillation of 1–3 per cent for the various nights. For sources fainter than ∼1 Jy, this variation is below the image noise at typical MWA sensitivities. Our results demonstrate that the ionosphere is not a significant impediment to the goals of time-domain science with the MWA at 154 MHz.
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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 | 0.001 | 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".