juliensimon/vlass-radio-sources

---
license: cc-by-4.0
pretty_name: "VLASS Radio Sources (Epoch 1)"
language:
- en
description: "Very Large Array Sky Survey (VLASS) Epoch 1 Quick Look component catalog with 3,381,277 radio source detections at 2-4 GHz (S-band)."
task_categories:
- tabular-classification
- tabular-regression
tags:
- space
- radio
- vlass
- vla
- nrao
- astronomy
- open-data
- tabular-data
size_categories:
- 1M<n<10M
configs:
- config_name: default
data_files:
- split: train
path: data/vlass_radio_sources.parquet
default: true
---

# VLASS Radio Sources (Epoch 1)

*Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) collection on Hugging Face.*

The Very Large Array Sky Survey (VLASS) Epoch 1 Quick Look component catalog from CIRADA,
containing **3,381,277** radio source detections at S-band (2-4 GHz) with ~2.5 arcsecond
resolution, covering the sky north of declination -40 degrees. VLASS is the modern successor
to NVSS and FIRST, offering higher resolution and multi-epoch coverage.

## Dataset description

VLASS is a synoptic all-sky radio survey using the Karl G. Jansky Very Large Array (VLA) in
its B-configuration at S-band (2-4 GHz). The survey covers the entire sky visible to the VLA
(declination > -40 deg, ~33,885 sq. deg.) in three epochs. This catalog contains Quick Look
component detections from Epoch 1, processed by the Canadian Initiative for Radio Astronomy
Data Analysis (CIRADA). Each row is a Gaussian component fitted to a radio detection using PyBDSF.

Of the 3,381,277 total detections, **1,880,195** are in the curated main sample
(duplicate-free, quality-filtered) and **1,826,680** are resolved sources.

## Key columns

| Column | Type | Description |
|--------|------|-------------|
| `component_name` | string | IAU component name (VLASS1QLCIR JHHMMSS.ss+DDMMSS.s) |
| `ra_deg` | float64 | Right ascension J2000 (degrees) |
| `dec_deg` | float64 | Declination J2000 (degrees) |
| `total_flux_mjy` | float64 | Integrated flux density at S-band (mJy) |
| `peak_flux_mjy_beam` | float64 | Peak brightness at S-band (mJy/beam) |
| `major_axis_arcsec` | float64 | Fitted major axis FWHM (arcsec) |
| `minor_axis_arcsec` | float64 | Fitted minor axis FWHM (arcsec) |
| `position_angle_deg` | float64 | Fitted position angle (degrees) |
| `deconv_major_arcsec` | float64 | Deconvolved major axis (arcsec) |
| `deconv_minor_arcsec` | float64 | Deconvolved minor axis (arcsec) |
| `island_rms_mjy_beam` | float64 | Local rms noise (mJy/beam) |
| `source_code` | string | Component type: S(ingle), C(omplex), M(ultiple), E(xtended) |
| `nvss_distance_arcsec` | float64 | Angular separation from nearest NVSS source (arcsec) |
| `first_distance_arcsec` | float64 | Angular separation from nearest FIRST source (arcsec) |
| `duplicate_flag` | Int32 | Duplicate detection flag (0=unique) |
| `quality_flag` | Int32 | Quality flag (0=good) |
| `main_sample` | Int32 | Main sample membership (1=curated subset) |
| `is_resolved` | bool | True if deconvolved major axis > 0 |

Full schema includes 70 columns with uncertainties, beam properties, and image-plane measurements.

## Quick stats

- **3,381,277** total component detections
- **1,880,195** main sample sources (quality-filtered, duplicate-free)
- **1,826,680** resolved sources (54.0%)
- Median peak flux: 1238.00 mJy/beam
- Declination range: -40.0 to 89.8 degrees
- Frequency: S-band (2-4 GHz), ~2.5 arcsec resolution

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/vlass-radio-sources", split="train")
df = ds.to_pandas()

# Main sample only (quality-filtered)
main = df[df["main_sample"] == 1]
print(f"Main sample: {len(main):,} sources")

# Flux distribution
import matplotlib.pyplot as plt
df["peak_flux_mjy_beam"].clip(upper=100).hist(bins=200, log=True)
plt.xlabel("Peak flux (mJy/beam)")
plt.ylabel("Count")
plt.title("VLASS Source Flux Distribution")
plt.show()

# Sky density map
plt.hexbin(df["ra_deg"], df["dec_deg"], gridsize=100, mincnt=1)
plt.colorbar(label="Source count")
plt.xlabel("RA (deg)")
plt.ylabel("Dec (deg)")
plt.title("VLASS Epoch 1 Sky Density")
plt.show()

# Cross-match proximity to NVSS/FIRST
has_nvss = df["nvss_distance_arcsec"] < 10
print(f"Within 10 arcsec of NVSS source: {has_nvss.sum():,}")
```

## Data source

Gordon, Y.A., et al. (2021), *A Catalog of Very Large Array Sky Survey (VLASS) Epoch 1
Quick Look Components, Version 2.* Astrophysical Journal Supplement Series, 255, 30.
Processed by CIRADA. Via VizieR CDS (J/ApJS/255/30).

## Related datasets

- [NVSS Radio Source Catalog](https://huggingface.co/datasets/juliensimon/nvss-radio-catalog) — predecessor 1.4 GHz survey, 1.8M sources
- [FIRST Radio Survey Catalog](https://huggingface.co/datasets/juliensimon/first-radio-catalog) — predecessor high-resolution 1.4 GHz survey

## Pipeline

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

## Citation

```bibtex
@dataset{vlass_radio_sources,
author = {Simon, Julien},
title = {VLASS Radio Sources (Epoch 1)},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/vlass-radio-sources},
note = {Based on Gordon et al. (2021) via VizieR CDS}
}
```

## License

[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)