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OTTER TDE Catalog
Credit: NASA/ESA/Hubble
Part of a dataset collection on Hugging Face.
Dataset description
All known tidal disruption events (TDEs) from the Open TDE Catalog β stars torn apart by supermassive black holes.
A tidal disruption event (TDE) occurs when a star passes close enough to a supermassive black hole to be ripped apart by tidal forces, producing a luminous flare visible across the electromagnetic spectrum. The Open TDE Catalog aggregates all known TDE candidates with coordinates, redshifts, host galaxy identifications, and peak magnitudes.
Tidal disruption events provide a unique laboratory for studying supermassive black holes (SMBHs) that are otherwise quiescent and therefore undetectable. When a star on a low-angular-momentum orbit enters the tidal radius of an SMBH, the differential gravitational force across the star exceeds its self-gravity, shredding it into a stream of debris. Roughly half of this material becomes bound and accretes onto the black hole, producing a luminous flare that peaks in the UV/optical for lower-mass black holes (10^6--10^7 solar masses) and in the soft X-ray band for more massive ones. The light curve rise time, peak luminosity, and late-time decay rate (classically predicted to follow a t^(-5/3) power law) encode the black hole mass, the stellar mass and structure, and the orbital geometry.
The spectroscopic classification of TDEs into hydrogen-rich (TDE-H), helium-rich (TDE-He), and mixed subtypes reflects the composition of the disrupted star and the complex reprocessing of emission in the debris stream and outflows. Relativistic TDEs -- such as Swift J1644+57 -- launch powerful jets detectable at radio through hard X-ray wavelengths, providing probes of jet formation physics analogous to active galactic nuclei but in a time-resolved, 'clean' environment. The host galaxy properties (mass, morphology, nuclear activity) are critical for understanding the SMBH occupation fraction and the stellar dynamics that deliver stars to disruption orbits, with TDEs preferentially occurring in post-starburst ('E+A') galaxies for reasons that remain actively debated.
Schema
| Column | Type | Description | Sample | Null % |
|---|---|---|---|---|
name |
object | Primary TDE designation (e.g., 'ASASSN-14li', 'AT2019qiz', 'Swift J1644+57'); modern transients use AT prefix until spectroscopically confirmed | 2MASX J0249 | 0.0% |
aliases |
object | Comma-separated list of alternative designations from different surveys or reporting telegrams; null if no aliases recorded | 2XMMi J184725.1-631724 | 83.3% |
ra_hms |
object | Right ascension of the TDE / host nucleus in sexagesimal format (HH:MM:SS.ss) | 02:49:17.28 | 13.3% |
dec_dms |
object | Declination of the TDE / host nucleus in sexagesimal format (+DD:MM:SS.ss) | -04:12:54 | 13.3% |
ra |
float64 | Right ascension in decimal degrees (J2000.0 ICRS); range 0-360; null for ~10% of entries lacking coordinates | 42.322 | 14.4% |
dec |
float64 | Declination in decimal degrees (J2000.0 ICRS); range -90 to +90; null when ra is null | -4.215 | 13.3% |
redshift |
float64 | Host galaxy spectroscopic redshift; TDE surveys typically probe 0.01 < z < 1; null for ~40% of entries; range ~0.001 (very nearby) to ~1 | 0.0186 | 6.7% |
claimed_type |
object | Spectroscopic classification: 'TDE' (confirmed), 'TDE?' (candidate), 'TDE-H' (hydrogen-dominated spectrum), 'TDE-He' (helium-dominated), 'TDE-H+He' (mixed), 'TDE-featureless'; null for unclassified candidates | TDE | 58.9% |
host_galaxy |
object | Name of the host galaxy where the TDE occurred; TDEs preferentially occur in post-starburst ('E+A') galaxies; null for ~30% of entries | 2MASX J02491731-0412521 | 7.8% |
host_ra |
float64 | Host galaxy nucleus right ascension in decimal degrees; may differ slightly from TDE position for well-resolved hosts | 42.322167 | 8.9% |
host_dec |
float64 | Host galaxy nucleus declination in decimal degrees | -4.2145 | 7.8% |
host_offset_arcsec |
float64 | Angular offset between the TDE position and the host nucleus in arcseconds; genuine TDEs should be coincident with the nucleus (offset < 1 arcsec for high-z events); null for most entries | 1.897 | 20.0% |
peak_mag |
float64 | Peak apparent magnitude (filter unspecified, typically optical/UV); null for ~60% of entries | 15.6 | 52.2% |
peak_abs_mag |
float64 | Peak absolute magnitude; typical TDE: -17 to -21 mag; null for entries lacking redshift or peak apparent magnitude | -20.855 | 55.6% |
peak_date |
datetime64[ns] | UTC date of peak brightness; null for events where the light curve peak was not well-constrained | 2014-04-04 00:00:00 | 53.3% |
discovery_date |
datetime64[ns] | UTC date the transient was first reported; format YYYY-MM-DD | 2006-07-14 00:00:00 | 27.8% |
luminosity_distance_mpc |
float64 | Luminosity distance in megaparsecs, computed from redshift; null when redshift is unavailable | 83.5 | 6.7% |
velocity_km_s |
float64 | Host galaxy recession velocity in km/s (v = cz); null when redshift is unavailable | 5520.0 | 6.7% |
ebv |
float64 | Milky Way line-of-sight dust reddening E(B-V) in magnitudes from the Schlegel/Schlafly dust maps; used to correct observed magnitudes for extinction | 0.0267 | 14.4% |
instruments |
object | Instruments or facilities used for observations (e.g., 'ZTF', 'Swift-XRT', 'SDSS'); null for many entries | PN, PSPC, XRT | 18.9% |
discovery_year |
Int64 | Year of discovery; derived from discovery_date; null when discovery_date is unavailable | 2006 | 27.8% |
Quick stats
- 90 tidal disruption events (1990--2018)
- 77 with sky coordinates
- 84 with redshift measurements
- 37 with spectroscopic classification
- 83 with identified host galaxy
- 43 with peak magnitude
Classifications
| Type | Count |
|---|---|
| TDE? | 14 |
| MS + SMBH | 8 |
| TDE | 6 |
| AGN? | 3 |
| Candidate | 2 |
| WD + IMBH | 1 |
| Planet + WD | 1 |
| Low-mass TDE | 1 |
| SLSN-I? | 1 |
Usage
from datasets import load_dataset
import matplotlib.pyplot as plt
ds = load_dataset("juliensimon/otter-tde-catalog", split="train")
df = ds.to_pandas()
# All confirmed TDEs
confirmed = df[df["claimed_type"] == "TDE"]
# TDEs with redshift
with_z = df[df["redshift"].notna()].sort_values("redshift")
# Nearby TDEs (z < 0.05)
nearby = df[df["redshift"] < 0.05].sort_values("redshift")
# Discoveries per year
per_year = df["discovery_year"].dropna().value_counts().sort_index()
plt.figure(figsize=(10, 5))
plt.bar(per_year.index, per_year.values, color="steelblue")
plt.xlabel("Year")
plt.ylabel("Number of TDEs discovered")
plt.title("TDE Discoveries per Year")
plt.tight_layout()
plt.show()
Data source
https://github.com/astrocatalogs/tidaldisruptions
Related datasets
Citation
@dataset{otter_tde_catalog,
title = {OTTER TDE Catalog},
author = {juliensimon},
year = {2026},
url = {https://huggingface.co/datasets/juliensimon/otter-tde-catalog},
publisher = {Hugging Face}
}
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