The Tractor: Probabilistic astronomical source detection and measurement

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Ada Coda
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The Tractor: Probabilistic astronomical source detection and measurement

Post by Ada Coda » Fri Apr 29, 2016 9:40 pm

[c]The Tractor: Probabilistic astronomical source detection and measurement[/c][/b]
Abstract: 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 doesn’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.

Credit: Lang, Dustin; Hogg, David W.; Mykytyn, David

Site: https://github.com/dstndstn/tractor
http://adsabs.harvard.edu/abs/2016AJ....151...44D

Bibcode: 2016ascl.soft04008L

ID: ascl:1604.008

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