sla 1.3.0

Non-parametric LOSVD analysis for galaxy spectra

Non-parametric LOSVD in sla package

A code of nonparametric LOSVD recover for galaxy spectra

Stellar LOSVD recovery from the observed galaxy spectra is equivalent to a deconvolution and can be solved as a linear inverse problem. To overcome its ill-posed nature we apply smoothing regularization. Searching for an optimal degree of smoothing regularization is a challenging part of this approach. Here we present a non-parametric fitting technique and show real-world application to MaNGA spectral data cubes and long-slit spectrum of stellar counter-rotating galaxies.

More information can be found here and examples here

Authors

• Damir Gasymov (SAI Moscow Lomonosov State University)
• Ivan Katkov (NYU Abu-Dhabi, SAI Moscow Lomonosov State University)

Needed pip packages

There is many popular packages, vorbin by Michele Cappellari and my pseudoslit simple package for obtaining 2D LOSVD from a 3D cube of IFU-LOSVD.

pip install vorbin lmfit matplotlib astropy numpy pseudoslit shutil os glob PyPDF2 tqdm scipy sla

Try it!

Run the command and download spectrum data:

bash ./data/download.sh

Test different use cases (with NBursts analysis or for clean IFU-spectrum MaNGA SDSS):

python3 ./example/example_MaNGA_without_template.py

python3 ./example/example_NBursts_with_template.py

python3 ./example/example_NBursts_without_template.py

The result is shown in fits format and ploted in pdf in the result folder.