GCRCatalogsUpdated June 15, 2022: The most up-to-date version for the public DC2 data sets is v4. Previous versions have been deprecated.
The DC2 Simulated Sky Survey is a 300-sq-deq simulated survey in six optical bands with observations following a reference LSST observing cadence.
To learn more about the DC2 Simulated Sky Survey, you can read:
Two kinds of datasets are provided: Tables (including object and truth tables) and intermediate data products. Follow the instructions below for the data sets you wish to download.
If you use the DC2 Simulated Sky Survey in your work, we ask that you cite both publications above.
Follow these instructions to download “Object DPDD”, “Truth Match”, and/or “Unmerged Truth” data files from the DC2 Simulated Sky Survey. You can find the description and table schema of these data sets in the Data Release Note. You can download the full data set or, if space is at a premium, a recommended subset of files.
For “Object DPDD” and “Truth Match” data sets, the files are in Parquet format and are partitioned into sky regions called “tracts” (see Sec. 4.1 of the Release Note for details).
For “Unmerged Truth Star” and “Unmerged Truth SN” data sets, you can choose to download in Parquet format or in SQLite. The latter is larger in size but have better running performance if you are matching across tables.
For “Unmerged Truth Galaxy”, the files are in Parquet format and are partitioned into healpixels.
You can access all Parquet files by any standard tools that read Parquet format.
We additionally provide a high-level Python package GCRCatalogs to facilitate easy access (see below).
Note that on some very old (e.g., older than 10 years) machines, reading Parquet files may be difficult.
If that is a problem for you, please let us know.
GCRCatalogsSee these instructions to install and configure GCRCatalogs.
If you use GCRCatalogs to access the data, please also cite
Mao et al. (LSST DESC), ApJS, 234, 36 (2018).
For the DC2 Object and Truth tables specifically, you can use the following code to print out the tracts that you have downloaded.
import GCRCatalogs
print(GCRCatalogs.load_catalog('desc_dc2_run2.2i_dr6_object').available_tracts)
print(GCRCatalogs.load_catalog('desc_dc2_run2.2i_dr6_truth').available_tracts)
You can find examples of using GCRCatalogs in our tutorial notebooks.
If you’re planning to run the example notebooks and don’t already have JupyterLab on your laptop, see these instructions.
We provide a subset of intermediate data products from the LSST Science Pipelines, including raw images, calibrated exposures, and coadded images. Unlike the Table datasets, it is not possible to choose a even smaller subset of the intermediate data products that we provided. For a detailed description of these data products and associated files included, please see Section 3.4 of the Data Release Note. To see how these intermediate data products are organized, please see Appendix C of the Data Release Note.