Automated Author ProfileGhosh, Aritra
Yale University0000-0002-2525-9647
Ghosh, Aritra
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
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
Authors
- Ghosh, Aritra ;
- Urry, C. Megan ;
- Mishra, Aayush ;
- Perreault-Levasseur, Laurence ;
- Natarajan, Priyamvada ;
- Sanders, David B. ;
- Nagai, Daisuke ;
- Tian, Chuan ;
- Cappelluti, Nico ;
- Kartaltepe, Jeyhan S. ;
- Powell, Meredith C. ;
- Treister, Ezequiel
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
Authors
- Ghosh, Aritra ;
- Urry, C. Megan ;
- Mishra, Aayush ;
- Perreault-Levasseur, Laurence ;
- Natarajan, Priyamvada ;
- Sanders, David B. ;
- Nagai, Daisuke ;
- Tian, Chuan ;
- Cappelluti, Nico ;
- Kartaltepe, Jeyhan S. ;
- Powell, Meredith C. ;
- Treister, Ezequiel