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PS1-STRM is a neural network source classification and photometric redshift catalog created from the PanSTARRS1 (PS1) 3π DR1. Neural networks have been trained on a compilation of spectroscopic measurements, cross-matched with PS1. Based on PS1 forced mean photometry, a source is classified as galaxy, star, quasar, or unsure. For galaxies, photometric redshift estimation is performed, also yielding an estimate of redshift error via Monte-Carlo sampling. Sources lying outside the parameter coverage of the training set (i.e. extrapolated sources) are identified using self-organizing maps. Classification and photo-z results are provided for every source in the PS1 3π DR1 ForcedMeanObject table, a total of 2,902,054,648 objects. See the README file and the primary reference paper for a detailed description of the catalog metadata.
Will be big addition - no urgency, for Sherlock 3.0 !
The text was updated successfully, but these errors were encountered:
https://archive.stsci.edu/hlsp/ps1-strm
PS1-STRM is a neural network source classification and photometric redshift catalog created from the PanSTARRS1 (PS1) 3π DR1. Neural networks have been trained on a compilation of spectroscopic measurements, cross-matched with PS1. Based on PS1 forced mean photometry, a source is classified as galaxy, star, quasar, or unsure. For galaxies, photometric redshift estimation is performed, also yielding an estimate of redshift error via Monte-Carlo sampling. Sources lying outside the parameter coverage of the training set (i.e. extrapolated sources) are identified using self-organizing maps. Classification and photo-z results are provided for every source in the PS1 3π DR1 ForcedMeanObject table, a total of 2,902,054,648 objects. See the README file and the primary reference paper for a detailed description of the catalog metadata.
Will be big addition - no urgency, for Sherlock 3.0 !
The text was updated successfully, but these errors were encountered: