Create README.md

README.md

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+---
+task_categories:
+- feature-extraction
+tags:
+- astro
+size_categories:
+- 1M<n<10M
+---
+
+# Astronomical Time-Series Dataset
+
+ This is the full dataset of astronomical time-series from the 2018 Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC) Kaggle competition. There are 18 types of astronomical sources represented, including transient phenomena (e.g. supernovae, kilonovae) and variable objects (e.g. active galactic nuclei, Mira variables).
+
+ The original Kaggle competition can be found [here](https://www.kaggle.com/c/PLAsTiCC-2018). [This note](https://arxiv.org/abs/1810.00001) from the competition describes the dataset in detail. Astronomers may be interested in [this paper](https://arxiv.org/abs/1903.11756) describing the simulations used to generate the data.
+
+## Dataset Structure
+
+### Data Fields
+
+- **object_id**: unique object identifier
+- **times_wv**: 2D array of shape (N, 2) containing the observation times (modified Julian days, MJD) and filter (wavelength) for each observation, N=number of observations\
+- **target**: 2D array of shape (N, 2) containing the flux (arbitrary units) and flux error for each observation\
+- **label**: integer representing the class of the object (see below)\
+- **redshift**: true redshift of the object\
+- **ddf**: 1 if the object was in the deep drilling fields (DDF) survey area of LSST,  0 if wide-fast-deep (WFD)\
+- **hostgal_specz**: spectroscopic redshift of the host galaxy\
+- **hostgal_photoz**: photometric redshift of the host galaxy\
+- **hostgal_photoz_err**: uncertainty on the photometric redshift
+
+### Data Splits
+
+The original PLAsTiCC challenge had a training set that was biased to be lower redshift, brighter, and higher signal-to-noise than the test set. This was created to emulate a spectroscopically confirmed subset of observations that typically would be used to train a machine learning classifier. The test set represents a realistic simulation of all LSST observations -- fainter and noisier than the training set. In this dataset, the original PLAsTiCC training set was split into 90/10 training/validation and the original test set was uploaded unchanged.
+
+- **train**: 90% of the PLAsTiCC training set
+- **validation**: 10% of the PLAsTiCC training set
+- **test**: full PLAsTiCC test set
+
+## Additional Information
+
+### Class Descriptions
+```
+ 6: microlens-single
+ 15: tidal disruption event (TDE)
+ 16: eclipsing binary (EB)
+ 42: type II supernova (SNII)
+ 52: peculiar type Ia supernova (SNIax)
+ 53: Mira variable
+ 62: type Ibc supernova(SNIbc)
+ 64: kilonova (KN)
+ 65: M-dwarf
+ 67: peculiar type Ia supernova (SNIa-91bg)
+ 88: active galactic nuclei (AGN)
+ 90: type Ia supernova (SNIa)
+ 92: RR-Lyrae (RRL)
+ 95: superluminous supernova (SLSN-I)
+ 991: microlens-binary
+ 992: intermediate luminosity optical transient (ILOT)
+ 993: calcium-rich transient (CaRT)
+ 994: pair instability supernova (PISN)
+ 995: microlens-string
+```
+
+### Citation Information
+```
+@ARTICLE{2018arXiv181000001T,
+        author = {{The PLAsTiCC team} and {Allam}, Tarek, Jr. and {Bahmanyar}, Anita  and {Biswas}, Rahul and {Dai}, Mi and {Galbany}, Llu{\'\i}s and {Hlo{\v{z}}ek},      Ren{\'e}e and {Ishida}, Emille E.~O. and {Jha}, Saurabh W. and {Jones}, David O.     and {Kessler}, Richard and {Lochner}, Michelle and {Mahabal}, Ashish A. and {Malz},  Alex I. and {Mandel}, Kaisey S. and {Mart{\'\i}nez-Galarza}, Juan Rafael and         {McEwen}, Jason D. and {Muthukrishna}, Daniel and {Narayan}, Gautham and {Peiris},   Hiranya and {Peters}, Christina M. and {Ponder}, Kara and {Setzer}, Christian N.     and {The LSST Dark Energy Science Collaboration} and {LSST Transients}, The and      {Variable Stars Science Collaboration}},
+         title = "{The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set}",
+       journal = {arXiv e-prints},
+      keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
+          year = 2018,
+         month = sep,
+           eid = {arXiv:1810.00001},
+         pages = {arXiv:1810.00001},
+           doi = {10.48550/arXiv.1810.00001},
+ archivePrefix = {arXiv},
+        eprint = {1810.00001},
+  primaryClass = {astro-ph.IM},
+        adsurl = {https://ui.adsabs.harvard.edu/abs/2018arXiv181000001T},
+       adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+ }
+```