spender 0.1

Spectrum encoder and decoder

Spender

Neural spectrum encoder and decoder

From a data-driven side, galaxy spectra have two fundamental degrees of freedom: their instrinsic spectral properties (or type, if you believe in such a thing) and their redshift. The latter makes them awkward to ingest because it stretches everything, which means spectral features don't appear at the same places. This is why most analyses of the intrinsic properties are done by transforming the observed spectrum to restframe.

We decided to do the opposite. We build a custom architecture, which describes the restframe spectrum by an autoencoder and transforms the restframe model to the observed redshift. While we're at it we also match the spectral resolution and line spread function of the instrument:

Doing so clearly separates the responsibilities in the architecture. Spender establishes a restframe that has higher resolution and larger wavelength range than the spectra from which it is trained. The model can be trained from spectra at different redshifts or even from different instruments without the need to standardize the observations. Spender also has an explicit, differentiable redshift dependence, which can be coupled with a redshift estimator for a fully data-driven spectrum analysis pipeline.

Installation

The easiest way is pip install spender. When installing from the code repo, run pip install -e ..