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Cluster
string
N_Core
int64
N_Bkg
int64
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AI-1
10
62
15.5
-1.397001
AI-2
38
127
31.75
1.109196
AI-3
6
29
7.25
-0.464238
AI-4
63
319
79.75
-1.87564
AI-5
18
35
8.75
3.127071
AI-6
5
11
2.75
1.356801
AI-7
43
154
38.5
0.725241
AI-8
373
1,574
393.5
-1.033431
AI-9
61
156
39
3.522819
AI-10
37
111
27.75
1.755942
AI-11
126
440
110
1.52554
AI-12
8
15
3.75
2.194691
AI-13
29
107
26.75
0.435031
AI-14
21
154
38.5
-2.82038
AI-15
27
86
21.5
1.186161
AI-16
46
200
50
-0.565685
AI-17
127
459
114.75
1.143562
AI-18
31
133
33.25
-0.390199
AI-19
55
197
49.25
0.819341
AI-20
59
227
56.75
0.298675

NARIT GHOSTS Halo Catalogs

Dataset Description

This dataset contains reduced stellar catalogs, combined FITS images, and candidate substructure catalogs from the GHOSTS (Galaxy Halos, Outer disks, Substructure, Thick disks, and Star clusters) Survey observed by the Hubble Space Telescope (HST).

It serves as the primary data lake for the automated astronomical pipeline designed to detect faint stellar substructures (like Ultra-Faint Dwarfs and stellar streams) in the galactic halos of nearby galaxies.

Galaxies Included

  • M82 (Starburst Galaxy): Features highly asymmetrical background structures (the "Abyss"). Contains 6 HST fields, combined maps, and multiple ultra-faint candidate catalogs extracted via Watershed and Machine Learning pipelines.
  • NGC 2403 (Normal Spiral): Features a clean exponential disk profile successfully modeled and subtracted using Freeman's Law. Contains 7 HST fields and extracted substructure catalogs.
  • M81: Contains raw FITS files from the HST ACS/WFC fields.

Directory Structure

The dataset strictly mirrors the local workspace architecture of the analysis pipeline:

  • [galaxy]_workspace/data/*.fits: Raw FITS files and GHOSTS survey catalogs.
  • [galaxy]_workspace/*combined*.fits: Unified astrometrically-matched coordinate maps.
  • [galaxy]_workspace/**/*.csv: Scientific outputs including extracted clusters, candidate properties, and cross-matched validations.

Usage

You can download the entire dataset programmatically using the huggingface_hub Python library to seamlessly inject the data into the analytical workspaces:

from huggingface_hub import snapshot_download

# Download all workspaces while preserving the directory structure
snapshot_download(
    repo_id="appleboiy/narit-ghosts-halo-catalogs", 
    repo_type="dataset",
    local_dir=".",
    local_dir_use_symlinks=False 
)

Acknowledgements

The raw FITS data originates from the GHOSTS survey (Radburn-Smith et al. 2011). This repository and its substructure detection catalogs were generated as part of a localized astrophysical data pipeline.

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