---
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

```python
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](https://vizier.cds.unistra.fr/), CDS Strasbourg.

## Pipeline

Source code: [juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## License


[VizieR Scientific-Use Terms](https://cds.unistra.fr/vizier-org/licences_vizier.html)