Cluster string | N_Core int64 | N_Bkg int64 | Expected_Bkg float64 | SNR float64 |
|---|---|---|---|---|
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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