Breakthrough listen: A technosignature search around 27 eclipsing exoplanets selected from the <i>Transiting Exoplanet Survey Satellite</i> catalogue
Bibliographic record
Abstract
Abstract Here we analyse the archival data for a set of 27 Transiting Exoplanet Survey Satellite Targets of Interest in search for artificially generated radio signals, or ‘technosignatures’, interrupted by occultation. Exoplanetary eclipses are notable events to observe in the search for technosignatures, as they mark the geometrical alignment of the target, its host star, and Earth. During an eclipse event, any signal emanating from the target of interest should cease for the duration of the eclipse and resume after the line-of-sight has been restored. Target observations were made by Breakthrough Listen using Murriyang, the CSIRO Parkes 64-m radio telescope, coupled with the ultra-wide low frequency receiver covering a continuous range of frequencies spanning 704–4 032 MHz inclusive. Each target was observed in a pattern consisting of six back-to-back 5-min source and reference sky positions for comparison during data analysis. We performed a Doppler search for narrowband signals with a minimum signal-to-noise ratio of 10, a minimum drift rate of $\pm\,0.1$ Hz/s, and a maximum drift rate of $\pm\,4.0$ Hz/s using the turboseti pipeline. In the analysis of 1 954 880 signals, 14 639 passed automated radio interference filters where each event was presented as a set of stacked dynamic spectra. Despite manually inspecting each diagram for a signal of interest, all events were attributed to terrestrial radio frequency interference.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 0.001 |
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".