Datasets:
metadata
license: other
license_name: vizier-scientific-use
license_link: https://cds.unistra.fr/vizier-org/licences_vizier.html
pretty_name: Ultracool and Brown Dwarf Catalog (40 pc)
language:
- en
description: >-
Ultracool and brown dwarf catalog within 40 pc. JWST-relevant. Sourced via
VizieR CDS Strasbourg.
task_categories:
- tabular-classification
tags:
- space
- brown-dwarf
- ultracool
- jwst
- stellar
- astronomy
- open-data
size_categories:
- 10K<n<100K
Ultracool and Brown Dwarf Catalog (40 pc)
Comprehensive catalog of 14,168 ultracool and brown dwarfs within 40 parsecs, highly relevant for JWST atmospheric characterization studies.
Dataset description
Brown dwarfs are substellar objects too low in mass to sustain hydrogen fusion. Ultracool dwarfs (spectral types M7 and later) bridge the gap between the lowest-mass stars and giant planets. This volume-complete 40 pc sample from Sebastian et al. (2021) provides the most comprehensive census of the solar neighborhood's ultracool population, including L, T, and Y dwarfs ideal for JWST follow-up.
Quick stats
- 14,168 ultracool dwarfs within 40 pc
- 14,168 with spectral type classification
- 14,168 with distance estimates
Usage
from datasets import load_dataset
ds = load_dataset("juliensimon/brown-dwarf-catalog", split="train")
df = ds.to_pandas()
# T and Y dwarfs (coldest brown dwarfs)
if "spectral_type" in df.columns:
cold = df[df["spectral_type"].str.startswith(("T", "Y"), na=False)]
print(f"{len(cold):,} T/Y dwarfs")
# Nearest brown dwarfs
if "distance_pc" in df.columns:
nearby = df.dropna(subset=["distance_pc"]).sort_values("distance_pc").head(20)
print(nearby[["ra_deg", "dec_deg", "distance_pc"]].to_string())
Data source
Sebastian, D. et al. (2021), "The census of the solar neighbourhood ultracool dwarf volume-complete 40 pc sample", A&A, 645, A100. Accessed via VizieR, CDS Strasbourg.
Pipeline
Source code: juliensimon/space-datasets