Datasets:

UniverseTBD
/

mmu_hsc_pdr3_dud_22.5

_healpix_29 int64	image dict	a_g float32	a_r float32	a_i float32	a_z float32	a_y float32	g_extendedness_value float32	r_extendedness_value float32	i_extendedness_value float32	z_extendedness_value float32	y_extendedness_value float32	g_cmodel_mag float32	g_cmodel_magerr float32	r_cmodel_mag float32	r_cmodel_magerr float32	i_cmodel_mag float32	i_cmodel_magerr float32	z_cmodel_mag float32	z_cmodel_magerr float32	y_cmodel_mag float32	y_cmodel_magerr float32	g_sdssshape_psf_shape11 float32	g_sdssshape_psf_shape22 float32	g_sdssshape_psf_shape12 float32	r_sdssshape_psf_shape11 float32	r_sdssshape_psf_shape22 float32	r_sdssshape_psf_shape12 float32	i_sdssshape_psf_shape11 float32	i_sdssshape_psf_shape22 float32	i_sdssshape_psf_shape12 float32	z_sdssshape_psf_shape11 float32	z_sdssshape_psf_shape22 float32	z_sdssshape_psf_shape12 float32	y_sdssshape_psf_shape11 float32	y_sdssshape_psf_shape22 float32	y_sdssshape_psf_shape12 float32	g_sdssshape_shape11 float32	g_sdssshape_shape22 float32	g_sdssshape_shape12 float32	r_sdssshape_shape11 float32	r_sdssshape_shape22 float32	r_sdssshape_shape12 float32	i_sdssshape_shape11 float32	i_sdssshape_shape22 float32	i_sdssshape_shape12 float32	z_sdssshape_shape11 float32	z_sdssshape_shape22 float32	z_sdssshape_shape12 float32	y_sdssshape_shape11 float32	y_sdssshape_shape22 float32	y_sdssshape_shape12 float32	ra float64	dec float64	object_id string
713,959,823,852,017,300	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.004768545739352703,0.07777589559555054(...TRUNCATED)	0.036729	0.025801	0.018512	0.014318	0.012186	1	1	1	1	1	23.57872	0.029127	22.923664	0.02545	22.470736	0.022609	21.760159	0.019431	21.286701	0.041115	0.062797	0.071179	0.00936	0.096748	0.104854	-0.00434	0.058418	0.052981	0.001566	0.058197	0.058688	-0.001253	0.122316	0.100335	0.002139	0.127188	0.148077	0.015777	0.164383	0.246544	0.009033	0.110296	0.175241	0.014096	0.18076	0.212457	0.022566	0.290117	0.299273	0.040846	244.007026	53.391454	74701399811696099
713,959,824,164,611,500	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[-0.03560321778059006,0.01697284355759620(...TRUNCATED)	0.036702	0.025782	0.018498	0.014307	0.012177	0	0	1	0	0	19.799095	0.002044	18.972315	0.001137	18.639973	0.000836	18.484402	0.00109	18.352669	0.001785	0.062252	0.070131	0.008805	0.096829	0.104667	-0.004462	0.058778	0.053084	0.001721	0.059648	0.060093	-0.001306	0.122432	0.10033	0.0023	0.06416	0.070366	0.00928	0.099937	0.10538	-0.004613	0.062761	0.054885	0.001823	0.064622	0.061695	-0.000486	0.141971	0.10474	0.000755	244.003898	53.392136	74701399811696093
713,959,881,389,582,500	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.012548841536045074,-0.0677550733089447(...TRUNCATED)	0.037391	0.026266	0.018846	0.014576	0.012406	1	1	1	1	1	23.004745	0.012078	21.436321	0.00579	20.609243	0.003281	20.2827	0.004373	20.085938	0.009088	0.046404	0.057148	0.002023	0.094854	0.102729	-0.004892	0.060869	0.052841	0.00266	0.060289	0.060774	-0.001411	0.127594	0.098393	0.002176	0.11979	0.108471	-0.018824	0.18149	0.160688	-0.036278	0.12945	0.103194	-0.021512	0.130943	0.111509	-0.025472	0.214092	0.162958	-0.027316	244.002942	53.405185	74701399811696385
713,959,881,442,108,900	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[-0.037616658955812454,-0.060279320925474(...TRUNCATED)	0.037473	0.026323	0.018887	0.014607	0.012433	1	1	1	1	1	23.571358	0.020171	22.286388	0.011699	21.699238	0.007876	21.391399	0.011267	21.087294	0.023667	0.046432	0.05727	0.002077	0.094867	0.102785	-0.004874	0.060806	0.052811	0.00262	0.060289	0.060764	-0.001399	0.127753	0.098486	0.002153	0.217078	0.093209	-0.002397	0.305312	0.13767	-0.009245	0.255664	0.07895	0.000176	0.224331	0.088719	-0.01216	0.348067	0.149513	-0.004985	244.005094	53.406044	74701399811687669
713,959,884,302,830,600	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.017568612471222878,0.0550166554749012,(...TRUNCATED)	0.03795	0.026659	0.019127	0.014793	0.012591	0	0	0	0	0	23.801575	0.017062	22.513254	0.011517	20.822948	0.002839	20.189978	0.0043	19.918825	0.006174	0.046765	0.058526	0.002564	0.0948	0.103236	-0.004794	0.060145	0.052492	0.002258	0.064217	0.062635	-0.003996	0.128769	0.099021	0.001719	0.049327	0.059932	0.005765	0.098566	0.103193	-0.002674	0.059261	0.052631	0.001742	0.062945	0.063225	-0.004068	0.127916	0.100915	0.003603	244.020035	53.410421	74701399811696631
713,959,884,588,131,700	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.06552830338478088,0.15365546941757202,(...TRUNCATED)	0.037987	0.026685	0.019146	0.014808	0.012604	1	1	1	1	1	22.687286	0.010265	21.990005	0.01008	21.675776	0.009391	21.392231	0.022175	21.677366	0.039741	0.046744	0.058472	0.002557	0.094834	0.103241	-0.004783	0.060179	0.052505	0.00227	0.064239	0.062676	-0.003988	0.128829	0.099079	0.001776	0.187987	0.209654	-0.012622	0.234209	0.242516	-0.017455	0.181689	0.157642	-0.005399	0.188006	0.174376	-0.043783	0.238836	0.198605	-0.003877	244.020593	53.411037	74701399811696632
1,246,371,216,093,014,800	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[-0.006217591464519501,0.0150287337601184(...TRUNCATED)	0.064179	0.045084	0.032347	0.025018	0.021294	1	1	1	1	1	23.387188	0.007592	22.909056	0.006869	22.212036	0.004777	21.825233	0.005646	21.642197	0.009622	0.126802	0.12287	-0.000841	0.11717	0.114707	-0.000289	0.102543	0.097221	-0.001325	0.100312	0.103667	-0.00039	0.093897	0.090913	-0.000354	0.553281	0.305913	0.06152	0.578342	0.279818	0.063684	0.556629	0.253293	0.064129	0.575477	0.256282	0.062117	0.540491	0.250072	0.059218	33.763531	-4.764866	37485400817699515
1,246,371,217,746,173,700	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[-0.015146964229643345,0.0028905812650918(...TRUNCATED)	0.064239	0.045126	0.032377	0.025041	0.021314	1	1	1	1	1	23.797316	0.008099	23.173149	0.006622	22.404144	0.004194	22.103615	0.005184	21.93758	0.009385	0.126576	0.122958	-0.000859	0.115531	0.112921	-0.000085	0.106032	0.100554	-0.001457	0.100422	0.103643	-0.000305	0.096358	0.09335	-0.000496	0.205893	0.223926	-0.010768	0.21118	0.21215	-0.013183	0.19527	0.190833	-0.007566	0.197647	0.19235	-0.009333	0.173845	0.185721	-0.008861	33.762322	-4.763767	37485400817699630
1,246,371,241,943,451,600	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.0007050562999211252,0.0064372806809842(...TRUNCATED)	0.065011	0.045668	0.032766	0.025342	0.02157	1	1	1	1	1	22.896957	0.004224	22.017654	0.002721	21.749552	0.00267	21.646358	0.003911	21.476128	0.006854	0.122855	0.120311	0.001082	0.112853	0.113586	-0.000153	0.104336	0.09954	-0.001383	0.097397	0.102459	-0.000271	0.097753	0.093764	-0.000901	0.160167	0.167304	0.00421	0.169655	0.175753	0.003921	0.169552	0.176218	0.004207	0.169993	0.178033	0.006561	0.156092	0.166905	0.001725	33.736125	-4.759764	37485538256638831
1,246,371,248,003,274,200	{"band":["hsc-g","hsc-r","hsc-i","hsc-z","hsc-y"],"flux":[[[0.01951472833752632,0.015398151241242886(...TRUNCATED)	0.065263	0.045845	0.032893	0.02544	0.021653	1	1	1	1	1	22.897827	0.008479	22.764585	0.009881	22.203926	0.007955	22.300585	0.014206	22.286444	0.027341	0.127959	0.124269	0.000463	0.118019	0.117514	-0.000462	0.103458	0.099292	-0.000789	0.092892	0.097564	0.000294	0.101396	0.097939	-0.001664	0.379984	0.394739	-0.00458	0.308734	0.381594	-0.068204	0.316097	0.404198	-0.079284	0.38408	0.734998	-0.150537	0.425109	0.569234	-0.142072	33.738486	-4.754046	37485538256639068

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mmu_hsc_pdr3_dud_22.5 HATS Catalog Collection

This is the collection of HATS catalogs representing mmu_hsc_pdr3_dud_22.5.

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_hsc_pdr3_dud_22.5")
# One-degree cone.
catalog = lsdb.open_catalog(
    "https://huggingface.co/datasets/UniverseTBD/mmu_hsc_pdr3_dud_22.5",
    search_filter=lsdb.ConeSearch(ra=242.0, dec=55.0, 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_hsc_pdr3_dud_22.5 � 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_hsc_pdr3_dud_22.5_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
474,954	54	156	335.6 GiB	hats-import v0.7.3, hats v0.7.3

Catalog columns

The main HATS catalog contains the following columns:

Name	`_healpix_29`	`image.band`	`image.flux`	`image.ivar`	`image.mask`	`image.psf_fwhm`	`image.scale`	`a_g`	`a_r`	`a_i`	`a_z`	`a_y`	`g_extendedness_value`	`r_extendedness_value`	`i_extendedness_value`	`z_extendedness_value`	`y_extendedness_value`	`g_cmodel_mag`	`g_cmodel_magerr`	`r_cmodel_mag`	`r_cmodel_magerr`	`i_cmodel_mag`	`i_cmodel_magerr`	`z_cmodel_mag`	`z_cmodel_magerr`	`y_cmodel_mag`	`y_cmodel_magerr`	`g_sdssshape_psf_shape11`	`g_sdssshape_psf_shape22`	`g_sdssshape_psf_shape12`	`r_sdssshape_psf_shape11`	`r_sdssshape_psf_shape22`	`r_sdssshape_psf_shape12`	`i_sdssshape_psf_shape11`	`i_sdssshape_psf_shape22`	`i_sdssshape_psf_shape12`	`z_sdssshape_psf_shape11`	`z_sdssshape_psf_shape22`	`z_sdssshape_psf_shape12`	`y_sdssshape_psf_shape11`	`y_sdssshape_psf_shape22`	`y_sdssshape_psf_shape12`	`g_sdssshape_shape11`	`g_sdssshape_shape22`	`g_sdssshape_shape12`	`r_sdssshape_shape11`	`r_sdssshape_shape22`	`r_sdssshape_shape12`	`i_sdssshape_shape11`	`i_sdssshape_shape22`	`i_sdssshape_shape12`	`z_sdssshape_shape11`	`z_sdssshape_shape22`	`z_sdssshape_shape12`	`y_sdssshape_shape11`	`y_sdssshape_shape22`	`y_sdssshape_shape12`	`ra`	`dec`	`object_id`
Data Type	int64	list[string]	list[list<element: list<element: float>>]	list[list<element: list<element: float>>]	list[list<element: list<element: bool>>]	list[float]	list[float]	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	float	double	double	string
Nested?	�	image	image	image	image	image	image	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�	�
Value count	474,954	2,374,770	N/A	N/A	N/A	2,374,770	2,374,770	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954	474,954
Example row	714608920907664824	[hsc-g, hsc-r, hsc-i, hsc-z, hsc-y]	[[[0.01553, 0.01353, 0.04066, � (160 total)], � (160 total)], � (5 to�	[[[6186, 6202, 6196, 6281, 6295, � (160 total)], � (160 total)], � (5�	[[[True, True, True, True, True, � (160 total)], � (160 total)], � (5�	[0.6551, 0.7859, 0.584, 0.6869, � (5 total)]	[0.168, 0.168, 0.168, 0.168, 0.168]	0.02099	0.01475	0.01058	0.008184	0.006966	1	1	1	1	1	22.12	0.002044	21.82	0.002492	21.62	0.002321	21.52	0.004113	21.45	0.009543	0.07804	0.07675	-0.001801	0.1104	0.1124	-0.0007987	0.06518	0.05811	0.002674	0.08575	0.08443	-0.001878	0.09401	0.09101	0.004777	0.1922	0.204	0.05422	0.2435	0.2615	0.05549	0.1893	0.196	0.0582	0.2264	0.2352	0.05529	0.2284	0.2484	0.05748	242.2	54.85	75339253994786944
Minimum value	713959823852017263	hsc-g	N/A	N/A	N/A	-0.0	0.1679999977350235	0.014865555800497532	0.010442594066262245	0.007492423988878727	0.005794813856482506	0.004932244773954153	-0.0	-0.0	-0.0	-0.0	-0.0	13.40178108215332	5.988774501020089e-05	15.156841278076172	4.929747592541389e-05	12.742855072021484	3.227664274163544e-05	14.046401977539062	3.8605219742748886e-05	11.048727035522461	5.5523487390019e-05	0.002351417439058423	0.0023516854271292686	-1.1424497365951538	0.03563915193080902	0.007416512351483107	-0.3677349090576172	0.026111777871847153	0.031780991703271866	-0.4359694719314575	0.020980196073651314	0.03532128408551216	-0.4710213541984558	0.03327632322907448	0.03366565331816673	-0.02028796635568142	0.0015113428235054016	0.000953439564909786	-27798.8203125	0.0003241318336222321	0.0019716571550816298	-6958.20068359375	-0.3635726273059845	0.002350886119529605	-10027.140625	-8.943077087402344	0.00019998368225060403	-4239.42626953125	-0.002925257198512554	0.0018239404307678342	-13199.34375	33.606262488492874	-6.082362086730274	36429191050166698
Maximum value	1924448822636503838	hsc-z	N/A	N/A	N/A	4.95881462097168	0.1679999977350235	0.20999060571193695	0.14751191437244415	0.1058378592133522	0.08185745030641556	0.06967281550168991	1.0	1.0	1.0	1.0	1.0	inf	inf	inf	inf	22.499998092651367	inf	inf	inf	inf	inf	1.708125114440918	1.8359121084213257	0.08827947825193405	1.164284586906433	0.4658052623271942	0.7985565066337585	4.0367865562438965	4.870001316070557	0.03867558762431145	1.1716283559799194	1.332167387008667	0.059275317937135696	0.29171323776245117	0.32067495584487915	0.13825233280658722	28392.671875	37255.6015625	2947.21435546875	12577.33984375	16102.716796875	2831.651123046875	21279.3046875	15267.2314453125	3927.672607421875	1384974.125	243522.625	917168.0	16140.8369140625	13590.5048828125	6681.443359375	353.9145417236136	56.82558416535321	76557903720361081

"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_hsc_pdr3_dud_22.5 = lsdb.open_catalog("https://huggingface.co/datasets/UniverseTBD/mmu_hsc_pdr3_dud_22.5")
other = lsdb.open_catalog("https://huggingface.co/datasets/<org>/<other_catalog>")

crossmatched = mmu_hsc_pdr3_dud_22.5.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 Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), a wide-field imaging survey conducted with the Hyper Suprime-Cam on the Subaru Telescope. It uses data from the Deep and UltraDeep fields of the third Public Data Release (PDR3), which cover a smaller area of the sky but provide deeper (lower-noise) observations.

Data modality
The dataset consists of multi-band image cutouts (160 × 160 pixels) in five optical bands (g, r, i, z, y), extracted from larger survey images. Each cutout is centered on an object and is associated with measurements from the survey’s analysis pipeline. The dataset contains approximately 400,000 objects.

Typical use cases
This dataset can be used for machine learning applications on astronomical images, such as detecting rare objects, classifying sources, or characterizing galaxy properties.

Caveats
The dataset is restricted to the Deep/UltraDeep fields, which cover a relatively small area of the sky compared to the full survey, although with deeper (lower-noise) observations. In addition, the sample is constructed using selection criteria such as magnitude limits, requiring multiple observations across all bands, and removing objects affected by artifacts or unreliable measurements. As a result, the dataset may not fully represent the broader survey.

Citation
Data from the HSC-SSP can be used under the conditions specified by the survey. Users should include the credit “NAOJ / HSC Collaboration” and follow the usage terms.

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Collection including UniverseTBD/mmu_hsc_pdr3_dud_22.5

Multimodal Universe 🫶 LSDB/HATS 🎩 💫

Collection

Multimodal Universe Datasets in HATS format (https://hats.readthedocs.io/) • 36 items • Updated about 4 hours ago • 3

Papers for UniverseTBD/mmu_hsc_pdr3_dud_22.5

The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TB of Astronomical Scientific Data

Paper • 2412.02527 • Published Dec 3, 2024 • 13

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