Pipelines

Astra includes a suite of analysis pipelines for processing SDSS-V Milky Way Mapper spectra. Each pipeline targets specific science cases – from stellar parameter estimation and chemical abundance measurement to radial velocity determination and spectral classification.

Available pipelines

Pipeline	Description
APOGEENet	Neural network stellar parameters for APOGEE spectra
ASPCAP	ASPCAP pipeline using FERRE grid fitting (stellar parameters and chemical abundances)
AstroNN	AstroNN neural network for stellar parameters from APOGEE
AstroNN Dist	AstroNN with distance estimation
Best	Selects best results from multiple pipelines per source
BOSSNet	Neural network stellar parameters for BOSS spectra
CLAM	Constrained Linear Absorption Model for fitting stellar spectra
Corv	Radial velocity and parameters for DA white dwarfs
FERRE	Grid-based spectral fitting backend (used by ASPCAP)
Grok	Stellar parameters and vsini from high-resolution grid fitting
Line Forest	Spectral line strength measurements
MDwarfType	M dwarf spectral classification via template matching
NMF Rectify	NMF continuum rectification
SLAM	M dwarf stellar parameters via machine learning
Snow White	White dwarf classification and DA-type fitting
The Cannon	Label-transfer spectroscopy (The Cannon)
The Payne	Neural network spectral fitting (The Payne)