ZTF-observed late-time signals of pre-ZTF transients
Bibliographic record
Abstract
With large-scale surveys such as the Zwicky Transient Facility (ZTF), it has become possible to obtain a well-sampled light curve spanning the full length of the survey for any discovery within the survey footprint. Similarly, any transient within the footprint that was first detected before the start of the survey will likely have a large number of post-transient observations, making such transients excellent targets to search for the presence of late-time signals, particularly those due to interaction with circumstellar material (CSM). We searched for late-time signals in a sample of 7718 transients, mainly supernovae (SNe), that were first detected during the 10 years before the start of ZTF, aiming to find objects showing signs of late-time interaction with CSM. We found one candidate whose late-time signal is best explained by late-time CSM interaction, with the signal being around 300 days after transient discovery. A thin, distant shell containing ≲5 M⊙ of material could explain the recovered signal. We also found five objects whose late-time signal is best explained by faint nuclear transients occurring in host nuclei close to the pre-ZTF transient locations. Finally, we found two objects where it is difficult to determine whether the signal is from a nuclear transient or due to late-time CSM interaction occurring over 5 years after the SN. This study demonstrates the ability of large-scale surveys to find faint transient signals for a variety of objects and uncover a population of previously unknown sources. However, the large number of non-detections shows that strong late-time CSM interaction occurring years after the SN explosion is extremely rare.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".