juliensimon/cosmicflows-galaxy-distances

---
license: cc-by-4.0
pretty_name: "Cosmicflows-4 Galaxy Distances"
language:
- en
description: "The Cosmicflows-4 catalog of galaxy distances: 55,877 distance measurements from 8 methods (Tully-Fisher, SNe Ia, fundamental plane, TRGB, Cepheids, masers, SNe II, SBF). Sourced via VizieR CDS Strasbourg."
task_categories:
- tabular-classification
tags:
- space
- galaxies
- distances
- cosmology
- astronomy
- open-data
- tabular-data
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/cosmicflows_galaxy_distances.parquet
default: true
---

# Cosmicflows-4 Galaxy Distances

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

The Cosmicflows-4 (CF4) catalog is the most comprehensive compilation of galaxy distances
ever assembled. Published by Tully et al. (2023), it contains **55,877** distance
measurements derived from eight independent methods, enabling studies of the cosmic
distance ladder, large-scale structure, and peculiar velocities of galaxies.

## Dataset description

Galaxy distances are fundamental to cosmology. Unlike redshifts, which mix Hubble flow
with peculiar velocities, direct distance measurements let us map the true 3D distribution
of matter. CF4 consolidates distances from Type Ia supernovae, the Tully-Fisher relation,
the fundamental plane, tip of the red giant branch (TRGB), Cepheid period-luminosity,
surface brightness fluctuations (SBF), Type II supernovae, and maser observations.

Each entry includes the PGC galaxy identifier, coordinates (equatorial, galactic,
supergalactic), CMB-frame velocity, a best-estimate distance modulus, and individual
distance moduli from each method where available.

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `pgc` | int | PGC galaxy number |
| `pgc_primary` | int | Primary PGC number (for grouped galaxies) |
| `morphological_type` | float | Morphological type code (de Vaucouleurs T) |
| `velocity_cmb` | float | Velocity in CMB frame (km/s) |
| `distance_modulus` | float | Best-estimate distance modulus (mag) |
| `distance_modulus_err` | float | Uncertainty on distance modulus (mag) |
| `distance_mpc` | float | Distance in Mpc (derived from distance modulus) |
| `dm_sn_ia` | float | Distance modulus from Type Ia supernovae |
| `dm_sn_ia_err` | float | Uncertainty on SNe Ia distance modulus |
| `dm_tully_fisher` | float | Distance modulus from Tully-Fisher relation |
| `dm_tully_fisher_err` | float | Uncertainty on Tully-Fisher distance modulus |
| `dm_fundamental_plane` | float | Distance modulus from fundamental plane |
| `dm_fundamental_plane_err` | float | Uncertainty on fundamental plane DM |
| `dm_surface_brightness` | float | Distance modulus from surface brightness fluctuations |
| `dm_surface_brightness_err` | float | Uncertainty on SBF distance modulus |
| `dm_sn_ii` | float | Distance modulus from Type II supernovae |
| `dm_sn_ii_err` | float | Uncertainty on SNe II distance modulus |
| `dm_trgb` | float | Distance modulus from tip of red giant branch |
| `dm_trgb_err` | float | Uncertainty on TRGB distance modulus |
| `dm_cepheid` | float | Distance modulus from Cepheid variables |
| `dm_cepheid_err` | float | Uncertainty on Cepheid distance modulus |
| `dm_maser` | float | Distance modulus from maser observations |
| `dm_maser_err` | float | Uncertainty on maser distance modulus |
| `ra_deg` | float | Right ascension J2000 (degrees) |
| `dec_deg` | float | Declination J2000 (degrees) |
| `glon_deg` | float | Galactic longitude (degrees) |
| `glat_deg` | float | Galactic latitude (degrees) |
| `sgl_deg` | float | Supergalactic longitude (degrees) |
| `sgb_deg` | float | Supergalactic latitude (degrees) |
| `in_cf3` | bool | Present in Cosmicflows-3 catalog |

## Quick stats

- **55,877** galaxy distance measurements
- **12,222** with Tully-Fisher distances
- **42,223** with fundamental plane distances
- **1,004** with Type Ia supernova distances
- **446** with TRGB distances
- **69** with Cepheid distances
- **15,839** also in Cosmicflows-3
- Median distance: **203.8 Mpc**

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/cosmicflows-galaxy-distances", split="train")
df = ds.to_pandas()

# Galaxies within 100 Mpc (local universe)
local = df[df["distance_mpc"] <= 100]
print(f"{len(local):,} galaxies within 100 Mpc")

# Galaxies with Cepheid-calibrated distances
cepheids = df[df["dm_cepheid"].notna()]
print(f"{len(cepheids):,} with Cepheid distances")

# Sky distribution in supergalactic coordinates
import matplotlib.pyplot as plt
plt.scatter(df["sgl_deg"], df["sgb_deg"], s=0.2, alpha=0.3, c=df["distance_mpc"],
cmap="viridis", vmax=200)
plt.colorbar(label="Distance (Mpc)")
plt.xlabel("Supergalactic Longitude")
plt.ylabel("Supergalactic Latitude")
plt.title("Cosmicflows-4: Galaxy Distance Map")
```

## Data source

[Cosmicflows-4](https://vizier.cds.unistra.fr/viz-bin/VizieR?-source=J/ApJ/944/94)
(Tully R.B., Kourkchi E., Courtois H.M., et al., 2023, ApJ, 944, 94),
accessed via [VizieR](https://vizier.cds.unistra.fr/), CDS Strasbourg.

## Update schedule

Static dataset (fixed catalog release). No scheduled updates.

## Related datasets

- [messier-catalog](https://huggingface.co/datasets/juliensimon/messier-catalog) -- Messier deep-sky objects
- [ngc-ic-catalog](https://huggingface.co/datasets/juliensimon/ngc-ic-catalog) -- NGC/IC deep-sky catalog
- [exoplanet-catalog](https://huggingface.co/datasets/juliensimon/exoplanet-catalog) -- NASA Exoplanet Archive

## Pipeline

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

## Citation

```bibtex
@dataset{cosmicflows_galaxy_distances,
author = {Simon, Julien},
title = {Cosmicflows-4 Galaxy Distances},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/cosmicflows-galaxy-distances},
note = {Based on Cosmicflows-4 (Tully et al. 2023, ApJ, 944, 94) via VizieR CDS Strasbourg}
}
```

## License

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