Origin

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ORIGIN is a software to perform blind detection of faint emitters in MUSE datacubes.

The algorithm is tuned to efficiently detects faint spatial-spectral emission signatures, while allowing for a stable false detection rate over the data cube and providing in the same time an automated and reliable estimation of the purity.

The algorithm implements :

1. A nuisance removal part based on a continuum subtraction combining a Discrete Cosine Transform and an iterative Principal Component Analysis,

2. A detection part based on the local maxima of Generalized Likelihood Ratio test statistics obtained for a set of spatial-spectral profiles of emission line emitters,

3. A purity estimation part, where the proportion of true emission lines is estimated from the data itself: the distribution of the local maxima in the noise only configuration is estimated from that of the local minima.

Citation

ORIGIN is presented in the following paper: Mary et al., A&A, 2020 <https://doi.org/10.1051/0004-6361/201937001>_

Links

• Documentation <https://muse-origin.readthedocs.io/>_
• PyPI <https://pypi.org/project/muse-origin/>_
• Github <https://github.com/musevlt/origin>_