ROHSA (Regularized Optimization for Hyper-Spectral Analysis) was developped by the Hyperstars collaboration at Paris-Saclay University (IAS/CEA) to study the statistical properties of interstellar gas through atomic and molecular lines.
This code is a Gaussian decomposition algorithm designed to decompose any kind of hyper-spectral observations into a sum of coherent Gaussian. It is written in Fortran 90 and can be run on a single CPU. A user-friendly ROHSApy python interface can be used to run the code easily.
Marchal et al., A&A 626, A101 (2019) Please cite this publication if you are using ROHSA.
Replicating the results
All codes used in this work are available here
A google colab notebook is available here! It shows how to install, compile, run and read ROHSA's output.
Please note that if you do not use ROHSA to separate the phases of the 21 cm line (ex:CO, Lym-alpha, dust..), the hyper-parameters
lambda_var_sig should be set to 0.
If you have any queries or questions related to ROHSA, please do not hesitate to contact us here. Your feedback is welcome and important to us.