mmu_chandra_spectra HATS Catalog Collection

This is the collection of HATS catalogs representing mmu_chandra_spectra.

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_chandra_spectra")
# One-degree cone.
catalog = lsdb.open_catalog(
    "https://huggingface.co/datasets/UniverseTBD/mmu_chandra_spectra",
    search_filter=lsdb.ConeSearch(ra=134.0, dec=14.0, 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_chandra_spectra � 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_chandra_spectra_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
128,900	13	2,257	276.5 MiB	hats-import v0.7.3, hats v0.7.3

Catalog columns

The main HATS catalog contains the following columns:

Name	_healpix_29	spectrum.ene_center_bin	spectrum.ene_high_bin	spectrum.ene_low_bin	spectrum.flux	spectrum.flux_error	flux_aper_b	flux_bb_aper_b	flux_significance_b	hard_hm	hard_hs	hard_ms	var_index_b	var_prob_b	name	object_id	ra	dec
Data Type	int64	list[float]	list[float]	list[float]	list[float]	list[float]	float	float	float	float	float	float	float	float	string	string	double	double
Nested?	�	spectrum	spectrum	spectrum	spectrum	spectrum	�	�	�	�	�	�	�	�	�	�	�	�
Value count	128,900	4,364,568	4,364,568	4,364,568	4,364,568	4,364,568	128,900	128,900	128,900	128,900	128,900	128,900	128,900	128,900	128,900	128,900	128,900	128,900
Example row	304334048313525994	[0.657, 0.9198, 1.102, 1.241, 1.372, � (17 total)]	[0.803, 1.037, 1.168, 1.314, 1.431, � (17 total)]	[0.511, 0.803, 1.037, 1.168, 1.314, � (17 total)]	[0.001425, 0.002141, 0.003167, � (17 total)]	[0.0009772, 0.001293, 0.002171, � (17 total)]	7.578e-14	7.276e-14	7.918	0.2598	0.1337	-0.1337	0	0.1263	2CXO J085446.9+140843	47877	133.7	14.15
Minimum value	55043007421035	0.5182999968528748	0.525600016117096	0.5109999775886536	-0.1565576046705246	1.8854531163015054e-06	-0.0	1.7774323594850266e-15	4.047618865966797	-0.9993754029273987	-0.9993754029273987	-0.9993754029273987	-0.0	-0.0	2CXO J000002.4+004444	0	0.01018931969673531	-86.63160308051602
Maximum value	3456929663501242754	7.978899955749512	7.986199855804443	7.97160005569458	8.14805793762207	0.8432331681251526	5.414789727709035e-10	2.89389456842315e-10	415.9320983886719	0.9993754029273987	0.9993754029273987	0.9993754029273987	10.0	1.0	2CXO J235953.4-093655	99999	359.9726737313183	89.37200563200145

"Nested" indicates whether the column is stored as a nested field inside another "struct" column.

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

crossmatched = mmu_chandra_spectra.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 Chandra X-ray Observatory, which studies X-ray emission from extreme environments in the Universe, such as black holes, supernova remnants, and active stars.

Data modality
The dataset consists of X-ray spectra (photon energy vs count rate) in the energy range 0.5–8 keV, derived from individual photon event data recorded by the telescope. Each sample includes energy bins, count rates, associated errors, and source identifiers and coordinates. In addition, the dataset provides derived features that characterize the sources, such as flux measurements, signal-to-noise ratio, spectral hardness ratios, and variability indicators over time.

Typical use cases
The dataset can be used to study X-ray emission from astrophysical sources and to analyze their physical properties. It has also been used in machine learning applications such as classification of X-ray sources.

Caveats
The dataset includes only sources with at least 40 total counts and a signal-to-noise ratio of 4 or higher. The spectra are derived from photon event data through the application of the instrument’s spectral response and processing pipelines.

Citation
This dataset uses data from the Chandra Source Catalog (CSC, version 2.1), which is publicly available. Users should follow the official guidelines from the Chandra X-ray Center (CXC) when acknowledging and citing the data.