Needle in a Haystack: Finding Supermassive Black Hole-Related Flares in the Zwicky Transient Facility Public Survey
Bibliographic record
Abstract
Transient accretion events onto supermassive black holes (SMBHs), such as tidal disruption events (TDEs), Bowen Fluorescence Flares (BFFs), and active galactic nuclei (AGNs), which are accompanied by sudden increases of activity, offer a new window onto the SMBH population, accretion physics, and stellar dynamics in galaxy centers. However, such transients are rare and finding them in wide-field transient surveys is challenging. Here we present the results of a systematic real-time search for SMBH-related transients in Zwicky Transient Facility (ZTF) public alerts, using various search queries. We examined 345 rising events coincident with a galaxy nucleus, with no history of previous activity, of which 223 were spectroscopically classified. Of those, five (2.2%) were TDEs, one (0.5%) was a BFF, and two (0.9%) were AGN flares. Limiting the search to blue events, the fraction of TDEs nearly doubles to 4.1%, and no TDEs are missed. Limiting the search further to candidate post-starburst galaxies increases the relative number of TDEs to 16.7%, but the absolute numbers in such a search are small. The main contamination source is supernovae (95.1% of classified events), of which the majority (82.2% of supernovae) are of Type Ia. In a comparison set of 39 events with limited photometric history, the AGN contamination increases to ~30%. Host galaxy offset is not a significant discriminant of TDEs in current ZTF data, but might be useful in higher-resolution data. Our results can be used to quantify the efficiency of various SMBH-related transient search strategies in optical surveys such as ZTF and the Legacy Survey of Space and Time.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".