## The Tractor

swMATH ID: | 32980 |

Software Authors: | Lang, Dustin; Hogg, David W.; Mykytyn, David |

Description: | The Tractor: Probabilistic astronomical source detection and measurement. The Tractor optimizes or samples from models of astronomical objects. The approach is generative: given astronomical sources and a description of the image properties, the code produces pixel-space estimates or predictions of what will be observed in the images. This estimate can be used to produce a likelihood for the observed data given the model: assuming the model space actually includes the truth (it doesnâ€™t, in detail), then if we had the optimal model parameters, the predicted image would differ from the actually observed image only by noise. Given a noise model of the instrument and assuming pixelwise independent noise, the log-likelihood is the negative chi-squared difference: (image - model) / noise. |

Homepage: | https://thetractor.readthedocs.io/en/latest/ |

Source Code: | https://github.com/dstndstn/tractor |

Cited in: | 1 Publication |

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### Cited by 6 Authors

1 | Adams, Ryan Prescott |

1 | Mcauliffe, Jon D. |

1 | Miller, Andrew C. |

1 | Prabhat, A. K. |

1 | Regier, Jeffrey C. |

1 | Schlegel, David |

### Cited in 1 Serial

1 | The Annals of Applied Statistics |

### Cited in 3 Fields

1 | Statistics (62-XX) |

1 | Numerical analysis (65-XX) |

1 | Astronomy and astrophysics (85-XX) |