juliensimon/planck-cold-clumps

---
license: cc-by-4.0
pretty_name: "Planck Catalogue of Galactic Cold Clumps"
language:
- en
description: "Cold, dense interstellar medium sources detected by the ESA Planck satellite at submillimeter wavelengths — potential pre-stellar cores and sites of future star formation."
task_categories:
- tabular-classification
tags:
- space
- planck
- esa
- interstellar-medium
- star-formation
- astronomy
- open-data
- tabular-data
- parquet
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/planck_pgcc.parquet
default: true
---

# Planck Catalogue of Galactic Cold Clumps (PGCC)

<div align="center">
<img src="banner.jpg" alt="The gamma-ray sky as seen by NASA's Fermi telescope" width="400">
<p><em>Credit: NASA/DOE/Fermi LAT Collaboration</em></p>
</div>

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


The Planck Catalogue of Galactic Cold Clumps (PGCC) — **13,242** cold, dense sources
in the interstellar medium detected by the [ESA Planck satellite](https://www.cosmos.esa.int/web/planck)
at submillimeter wavelengths, sourced from [VizieR](https://vizier.cds.unistra.fr/).

## Dataset description

Galactic cold clumps are cold, dense regions in the interstellar medium (ISM) with dust
temperatures typically between 6 and 20 K, significantly colder than their surrounding
environment. These compact structures represent the earliest stages of the star formation
process — gravitationally bound or pre-gravitationally bound condensations that may
eventually collapse to form protostars. Many are candidate pre-stellar cores, the seeds
from which new stars and planetary systems will emerge.

The PGCC was compiled from the full Planck all-sky survey using a multi-frequency detection
algorithm that identifies sources colder than their local background in the 857, 545, and
353 GHz (350, 550, and 850 micron) bands. Planck's all-sky coverage at submillimeter
wavelengths makes it uniquely suited for this task — no other observatory has mapped the
entire sky at these frequencies with comparable sensitivity. Ground-based submillimeter
telescopes can observe only small patches of sky, and previous space missions (IRAS, Herschel)
either lacked the spectral coverage or the all-sky field of view needed to build a complete
census of Galactic cold dust sources.

Each PGCC entry includes flux densities at three Planck bands (and 3000 GHz / 100 micron
where available), dust temperature and spectral emissivity index derived from modified
blackbody fitting, H2 column density, angular size, and quality flags. The clumps span the
full range of Galactic environments: from nearby molecular clouds (Taurus, Ophiuchus,
Orion) at distances of 100-500 pc to distant complexes in the outer Galaxy beyond 5 kpc.
Their dust temperatures, typically 5-8 K colder than the warm diffuse ISM (~18-20 K),
identify them as sites where radiative shielding and high density allow efficient cooling.

The PGCC is a cornerstone resource for star formation studies, providing targets for
high-resolution follow-up with ALMA, NOEMA, and JCMT to characterize their internal
structure, kinematics, and fragmentation. It bridges the gap between the large-scale
ISM structure traced by CO surveys and the individual protostellar cores revealed by
interferometric observations.

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `name` | string | PGCC catalog designation (e.g. PGCC G000.00+00.00) |
| `glon_deg` | float64 | Galactic longitude (degrees) |
| `glat_deg` | float64 | Galactic latitude (degrees) |
| `ra_deg` | float64 | Right ascension J2000 (degrees) |
| `dec_deg` | float64 | Declination J2000 (degrees) |
| `snr` | float64 | snr |
| `snr_857ghz` | float64 | Signal-to-noise ratio at 857 GHz |
| `snr_545ghz` | float64 | Signal-to-noise ratio at 545 GHz |
| `snr_353ghz` | float64 | Signal-to-noise ratio at 353 GHz |
| `maj` | float64 | maj |
| `e_maj` | float64 | e_maj |
| `min` | float64 | min |
| `e_min` | float64 | e_min |
| `position_angle_deg` | float64 | Position angle of the major axis (degrees, east of north) |
| `e_pa` | float64 | e_pa |
| `f3000c` | float64 | f3000c |
| `e_f3000c` | float64 | e_f3000c |
| `f857c` | float64 | f857c |
| `e_f857c` | float64 | e_f857c |
| `f545c` | float64 | f545c |
| `e_f545c` | float64 | e_f545c |
| `f353c` | float64 | f353c |
| `e_f353c` | float64 | e_f353c |
| `f3000w` | float64 | f3000w |
| `e_f3000w` | float64 | e_f3000w |
| `f857w` | float64 | f857w |
| `e_f857w` | float64 | e_f857w |
| `f545w` | float64 | f545w |
| `e_f545w` | float64 | e_f545w |
| `f353w` | float64 | f353w |
| `e_f353w` | float64 | e_f353w |
| `q_flux` | int64 | q_flux |
| `fblend` | int64 | fblend |
| `fblenddist` | float64 | fblenddist |
| `fblendb857` | float64 | fblendb857 |
| `fblendb545` | float64 | fblendb545 |
| `fblendb353` | float64 | fblendb353 |
| `tempc` | float64 | tempc |
| `e_tempc` | float64 | e_tempc |
| `btempc` | float64 | btempc |
| `betac` | float64 | betac |
| `e_betac` | float64 | e_betac |
| `bbetac` | float64 | bbetac |
| `tempbeta2c` | float64 | tempbeta2c |
| `e_tempbeta2c` | float64 | e_tempbeta2c |
| `btempbeta2c` | float64 | btempbeta2c |
| `tempw` | float64 | tempw |
| `e_tempw` | float64 | e_tempw |
| `btempw` | float64 | btempw |
| `betaw` | float64 | betaw |
| `e_betaw` | float64 | e_betaw |
| `bbetaw` | float64 | bbetaw |
| `tempbeta2w` | float64 | tempbeta2w |
| `e_tempbeta2w` | float64 | e_tempbeta2w |
| `btempbeta2w` | float64 | btempbeta2w |
| `distoedr7` | float64 | distoedr7 |
| `e_distoedr7` | float64 | e_distoedr7 |
| `distne` | float64 | distne |
| `e_distne` | float64 | e_distne |
| `distmoc` | float64 | distmoc |
| `e_distmoc` | float64 | e_distmoc |
| `distopt` | int64 | distopt |
| `q_dist` | int64 | q_dist |
| `distance_pc` | float64 | Estimated distance (pc) |
| `distance_err_pc` | float64 | Uncertainty on distance (pc) |
| `mass` | float64 | mass |
| `e_mass` | float64 | e_mass |
| `b1mass` | float64 | b1mass |
| `b2mass` | float64 | b2mass |
| `b3mass` | float64 | b3mass |
| `size` | float64 | size |
| `e_size` | float64 | e_size |
| `b1size` | float64 | b1size |
| `b2size` | float64 | b2size |
| `b3size` | float64 | b3size |
| `dens` | float64 | dens |
| `e_dens` | float64 | e_dens |
| `b1dens` | float64 | b1dens |
| `b2dens` | float64 | b2dens |
| `b3dens` | float64 | b3dens |
| `lum` | float64 | lum |
| `column_density_cm2` | float64 | H2 column density (cm^-2) |
| `column_density_err_cm2` | float64 | Uncertainty on H2 column density (cm^-2) |
| `b1nh2` | float64 | b1nh2 |
| `b2nh2` | float64 | b2nh2 |
| `b3nh2` | float64 | b3nh2 |
| `nhotsrc` | float64 | nhotsrc |
| `flmc` | int64 | flmc |
| `fsmc` | int64 | fsmc |
| `fecc` | int64 | fecc |
| `fpccs857` | int64 | fpccs857 |
| `fpccs545` | int64 | fpccs545 |
| `fpccs353` | int64 | fpccs353 |
| `fpccs217` | int64 | fpccs217 |
| `fpccs143` | int64 | fpccs143 |
| `fpccs100` | int64 | fpccs100 |
| `fpccs70` | int64 | fpccs70 |
| `fpccs44` | int64 | fpccs44 |
| `fpccs30` | int64 | fpccs30 |
| `fpsz` | int64 | fpsz |
| `fphz` | int64 | fphz |
| `fhkpgcc` | int64 | fhkpgcc |

## Quick stats

- **13,242** cold clumps across the full Galactic sky
- **0** with measured dust temperature (median 0.0 K, range 0.0--0.0 K)
- **10,792** with H2 column density estimates
- **5,628** with distance estimates

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/planck-cold-clumps", split="train")
df = ds.to_pandas()

# Coldest clumps (potential pre-stellar cores)
coldest = df[df["temperature_k"] < 10].sort_values("temperature_k")
print(f"{len(coldest):,} clumps colder than 10 K")

# Clumps with high column density (dense cores)
if "column_density_cm2" in df.columns:
dense = df[df["column_density_cm2"] > 1e22]
print(f"{len(dense):,} dense clumps (N_H2 > 10^22 cm^-2)")

# Temperature distribution
import matplotlib.pyplot as plt
df["temperature_k"].dropna().hist(bins=50)
plt.xlabel("Dust Temperature (K)")
plt.ylabel("Count")
plt.title("PGCC Dust Temperature Distribution")
```

## Data source

[Planck Catalogue of Galactic Cold Clumps](https://vizier.cds.unistra.fr/viz-bin/VizieR-3?-source=VIII/106/pgcc),
published by the Planck Collaboration (Planck Collaboration XXVIII, 2016, A&A, 594, A28),
accessed via [VizieR](https://vizier.cds.unistra.fr/), CDS Strasbourg.

## Update schedule

Static dataset. The PGCC is based on the final Planck data release and is not expected to change.

## Related datasets

- [planck-sz2-clusters](https://huggingface.co/datasets/juliensimon/planck-sz2-clusters) -- Planck SZ2 galaxy cluster catalog
- [nebula-catalog](https://huggingface.co/datasets/juliensimon/nebula-catalog) -- Catalog of Galactic nebulae
- [wise-hii-regions](https://huggingface.co/datasets/juliensimon/wise-hii-regions) -- WISE Catalog of Galactic HII Regions
- [gaia-dr3-young-stellar-objects](https://huggingface.co/datasets/juliensimon/gaia-dr3-young-stellar-objects) -- Gaia DR3 young stellar objects

## Pipeline

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

## Support

If you find this dataset useful, please give it a ❤️ on the [dataset page](https://huggingface.co/datasets/juliensimon/planck-cold-clumps) and share feedback in the Community tab! Also consider giving a ⭐️ to the [space-datasets](https://github.com/juliensimon/space-datasets) repo.

## Citation

```bibtex
@dataset{planck_cold_clumps,
author = {Simon, Julien},
title = {Planck Catalogue of Galactic Cold Clumps (PGCC)},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/planck-cold-clumps},
note = {Based on Planck Collaboration XXVIII (2016, A\&A, 594, A28) via VizieR CDS Strasbourg}
}
```

## License

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