Datasets:
flux_norm
sequencelengths 1.02k
4.78k
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sequencelengths 1.02k
4.78k
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"quarter": "Q9",
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"flux_median": 242625.09375
} |
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Kepler Flare Dataset
Dataset Description
The Kepler Flare Dataset is a comprehensive collection of stellar flare events observed by the Kepler Space Telescope. This dataset is constructed based on the flare event catalog presented in Yang & Liu (2019), which provides a systematic study of stellar flares in the Kepler mission. All light curves are the long cadence (about 29.4 minutes) data.
Dataset Features & Content
The dataset consists of high-quality photometric measurements from the Kepler Space Telescope, including:
- Light curves (flux measurements) normalized by their median values
- Binary classification labels for each time step (0: no flare, 1: flare event)
- Variable-length time series data
- Complete metadata for each observation
Dataset Structure
Each sample contains the following fields:
{
'flux_norm': List[float], # Normalized flux values sequence
'label': List[bool], # Corresponding labels (True for flare events)
'metadata': {
'kic_id': str, # Kepler Input Catalog ID
'quarter': str, # Observation quarter
'file_name': str, # Original file name
'flux_median': float, # Median flux used for normalization
}
}
Dataset Splits
The dataset is split into:
- Training set: 80%
- Validation set: 5%
- Test set: 15%
Usage
You can load the dataset directly using the Hugging Face datasets library:
from datasets import load_dataset
dataset = load_dataset("Maxwell-Jia/kepler-flare")
Applications
This dataset is particularly useful for:
- Stellar flare detection and analysis
- Astronomical event detection
- Deep learning applications in astronomical time series
Citation
If you use this dataset, please cite the following papers:
@article{yang2019flare,
title={The flare catalog and the flare activity in the Kepler mission},
author={Yang, Huiqin and Liu, Jifeng},
journal={The Astrophysical Journal Supplement Series},
volume={241},
number={2},
pages={29},
year={2019},
publisher={IOP Publishing}
}
@article{jia2024fcn4flare,
title={FCN4Flare: Fully Convolution Neural Networks for Flare Detection},
author={Jia, Ming-Hui and Luo, A-Li and Qiu, Bo},
journal={arXiv preprint arXiv:2407.21240},
year={2024}
}
License
This dataset is released under the MIT License.
Version
Current version: 1.0.0
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