| --- |
| 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} |
| } |
| ``` |
