ROHSA: Separation of diffuse sources in hyper-spectral data

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Ada Coda
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ROHSA: Separation of diffuse sources in hyper-spectral data

Post by Ada Coda » Sun Jul 28, 2019 11:36 pm

ROHSA: Separation of diffuse sources in hyper-spectral data

Abstract: ROHSA (Regularized Optimization for Hyper-Spectral Analysis) reveals the statistical properties of interstellar gas through atomic and molecular lines. It uses a Gaussian decomposition algorithm based on a multi-resolution process from coarse to fine grid to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. Optimization is performed on the whole data cube at once to obtain a solution with spatially smooth parameters.

Credit: Marchal, Antoine

Site: https://github.com/antoinemarchal/ROHSA
https://ui.adsabs.harvard.edu/abs/2019A%26A...626A.101M

Bibcode: 2019ascl.soft07028M

ID: ascl:1907.028

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