Tidal Disruption Event Host Galaxies in the Context of the Local Galaxy Population
Bibliographic record
Abstract
Abstract We study the properties of tidal disruption event (TDE) host galaxies in the context of a catalog of ∼500,000 galaxies from the Sloan Digital Sky Survey. We explore whether selection effects can account for the overrepresentation of TDEs in E+A/post-starburst galaxies by creating matched galaxy samples. Accounting for possible selection effects due to black hole (BH) mass, redshift completeness, strong active galactic nucleus presence, bulge colors, and surface brightness can reduce the apparent overrepresentation of TDEs in E+A host galaxies by a factor of ∼4 (from ∼×100–190 to ∼×25–48), but cannot fully explain the preference. We find that TDE host galaxies have atypical photometric properties compared to similar, “typical” galaxies. In particular, TDE host galaxies tend to live in or near the “green valley” between star-forming and passive galaxies, and have bluer bulge colors ( Δ ( g − r ) ≈ 0.3 mag), lower half-light surface brightnesses (by ∼1 mag/arcsec2), higher Sérsic indices ( Δ n g ≈ 3 ), and higher bulge-to-total-light ratios ( Δ B / T ≈ 0.5 ) than galaxies with matched BH masses. We find that TDE host galaxies appear more centrally concentrated and that all have high galaxy Sérsic indices and B/T fractions—on average in the top 10% of galaxies of the same BH mass—suggesting a higher nuclear stellar density. We identify a region in the Sérsic index and BH mass parameter space that contains ∼2% of our reference catalog galaxies but ≥ 60 % of TDE host galaxies. The unique photometric properties of TDE host galaxies may be useful for selecting candidate TDEs for spectroscopic follow-up observations in large transient surveys.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".