mmu_desi_provabgs HATS Catalog Collection

This is the collection of HATS catalogs representing mmu_desi_provabgs.

This dataset is part of the Multimodal Universe, a large-scale collection of multimodal astronomical data. For full details, see the paper: The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TBs of Astronomical Scientific Data.

Access the catalog

We recommend the use of the LSDB Python framework to access HATS catalogs. LSDB can be installed via pip install lsdb or conda install conda-forge::lsdb, see more details in the docs. The following code provides a minimal example of opening this catalog:

import lsdb

# Full sky coverage.
catalog = lsdb.open_catalog("https://huggingface.co/datasets/UniverseTBD/mmu_desi_provabgs")
# One-degree cone.
catalog = lsdb.open_catalog(
    "https://huggingface.co/datasets/UniverseTBD/mmu_desi_provabgs",
    search_filter=lsdb.ConeSearch(ra=239.0, dec=43.0, radius_arcsec=3600.0),
)

Each catalog in this collection is represented as a separate Apache Parquet dataset and can be accessed with a variety of tools, including pandas, pyarrow, dask, Spark, DuckDB.

File structure

This catalog is represented by the following files and directories:

• collection.properties � textual metadata file describing the HATS collection of catalogs
• mmu_desi_provabgs � main HATS catalog directory
  • dataset/ � Apache Parquet dataset directory for the main catalog
    • ... parquet metadata and data files in sub directories ...
  • hats.properties � textual metadata file describing the main HATS catalog
  • partition_info.csv � CSV file with a list of catalog HEALPix tiles (catalog partitions)
  • skymap.fits � HEALPix skymap FITS file with row-counts per HEALPix tile of fixed order 10
• mmu_desi_provabgs_10arcs/ � default margin catalog to ensure data completeness in cross-matching, the margin threshold is 10.0 arcseconds
  • ... margin catalog files and directories ...

Catalog metadata

Metadata of the main HATS catalog, excluding margins and indexes:

Number of rows	Number of columns	Number of partitions	Size on disk	HATS Builder
222,752	22	73	1.3 GiB	hats-import v0.7.3, hats v0.7.3

Catalog columns

The main HATS catalog contains the following columns:

Name	_healpix_29	ra	dec	PROVABGS_MCMC	PROVABGS_THETA_BF	LOG_MSTAR	Z_HP	Z_MW	TAGE_MW	AVG_SFR	ZERR	TSNR2_BGS	MAG_G	MAG_R	MAG_Z	MAG_W1	FIBMAG_R	HPIX_64	PROVABGS_Z_MAX	SCHLEGEL_COLOR	PROVABGS_W_ZFAIL	PROVABGS_W_FIBASSIGN	object_id
Data Type	int64	double	double	list<element: list<element: float>>	list<element: float>	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	string
Value count	222,752	222,752	222,752	N/A	2,895,776	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752	222,752
Example row	692306877918553052	239.2	43.23	[[11.93, 0.1643, 0.052, 0.2078, � (13 total)], � (100 total)]	[12.2, 0.241, 0.1054, 0.4592, � (13 total)]	11.95	0.3776	0.001392	8.849	14.35	1.459e-05	1514	21.37	20.23	19.48	18.88	21.04	9838	0.4418	0.4294	1.008	1	39633136480420008
Minimum value	643521053811880247	148.40325927734375	-2.3291468620300293	N/A	-2.0	6.238491058349609	1.4423111679207068e-05	4.4905984395882115e-05	0.014555543661117554	8.957725782920284e-14	2.9781909915982396e-07	223.89047241210938	12.553780555725098	12.053372383117676	11.390754699707031	11.869658470153809	14.953400611877441	9144.0	0.0008533737855032086	-23.969953536987305	1.0	1.0	39627733927462296
Maximum value	1981011982237869960	273.93377685546875	67.75138854980469	N/A	13.269999504089355	12.770240783691406	0.5997362732887268	0.04490434378385544	12.506219863891602	2095.118896484375	0.0006934804259799421	205831.9375	22.785625457763672	20.299989700317383	21.06035804748535	40.0	22.896602630615234	28151.0	0.6000000238418579	6.442105293273926	3.547720432281494	129.0	39633470523181151

"Value count" may be different from the total number of rows for nested columns: each nested element is counted as a single value.

Crossmatch with another catalog

HATS catalogs can be efficiently crossmatched using LSDB, which leverages the HEALPix partitioning to avoid loading the full datasets into memory:

import lsdb

mmu_desi_provabgs = lsdb.open_catalog("https://huggingface.co/datasets/UniverseTBD/mmu_desi_provabgs")
other = lsdb.open_catalog("https://huggingface.co/datasets/<org>/<other_catalog>")

crossmatched = mmu_desi_provabgs.crossmatch(other, radius_arcsec=1.0)
print(crossmatched)

See the LSDB documentation for more details on crossmatching and other operations.

Dataset-specific context

Original survey
This dataset is based on the DESI Bright Galaxy Survey (BGS), specifically using data from the Early Data Release (EDR). The PROVABGS catalog reports inferred galaxy properties for spectra in this sample.

Data modality
The dataset consists of tabular data containing galaxy physical properties derived from Spectral Energy Distribution (SED) modeling, such as log stellar mass, star formation rate, mass-weighted stellar metallicity, and mass-weighted stellar age. It also includes samples from the posterior distribution for each object.

Typical use cases
The dataset has been used for physical property estimation from both images and spectra in self-supervised and supervised learning contexts.

Caveats
The dataset is based on the DESI Early Data Release (EDR). The reported properties are inferred using Bayesian inference and SED modeling, rather than being directly observed quantities.

Citation
Users should acknowledge the PROVABGS dataset and the DESI collaboration. The data is publicly available.