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Digital Assets for "Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey"

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NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://zenodo.org/record/8067381
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资源简介:
These are morphological catalogs and trained GaMPEN models for Hyper Suprime-Cam galaxies. Please refer to https://gampen.readthedocs.io/en/latest/Public_data.html and https://arxiv.org/abs/2212.00051 for more details about this data release.    Catalog Files g_0_025_preds_summary.csv --> Structural parameter catalog for z < 0.25 HSC g-band galaxies  r_025_050_preds_summary.csv --> Structural parameter catalog for 0.25 < z < 0.50 HSC r-band galaxies  i_050_075_preds_summary.csv --> Structural parameter catalog for 0.50 < z < 0.75 HSC i-band galaxies    Trained PyTorch Model Files g_0_025_real_data.pt --> Trained Model for z < 0.25 HSC g-band galaxies  r_025_050_real_data.pt --> Trained Model for 0.25 < z < 0.50 HSC r-band galaxies  i_050_075_real_data.pt --> Trained Model for 0.50 < z < 0.75 HSC i-band galaxies  sim_g_0_025.pt --> Trained Model for Simulated z < 0.25 HSC g-band galaxies  sim_r_025_050.pt --> Trained Model for Simulated 0.25 < z < 0.50 HSC r-band galaxies  sim_i_050_075.pt --> Trained Model for Simulated 0.50 < z < 0.75 HSC i-band galaxies
创建时间:
2023-06-25
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