Redmonster Redshift Measurement and Spectral Classification

The redmonster software is a sophisticated and flexible set of Python utilities for redshift measurement, physical parameter measurement, and classification of one-dimensional astronomical spectra. A full description of the software is given in Hutchinson et al. (2016). These redshifts were used in the clustering measurements of the eBOSS LRG sample in Data Release 14 (Bautista et al. 2018).

Starting from Data Release 16, the redshift algorithm has changed and the redmonster redshift values are therefore no longer included in the data releases (but still available in Data Release 14, see below).


The software used is called redmonster and is publicly available in a GitHub repository.

The strategy for redshift fitting is to perform, at each potential redshift, a least-squares fit to each spectrum given the uncertainties, using a fairly general set of theoretical models for galaxies, stars, and quasars. The best fit model and redshift is chosen and reported for the object. The fits are applied without regard to the target category of the object (so that if, for example, an object targeted as a galaxy turns out to be a star, we can identify it as such).

The software is able to provide a 90.5% completeness while maintaining a sub-1% catastrophic failure for the LRG target sample.

Redshift & Classification

The redmonster software approaches redshift measurement and classification as a χ2 minimization problem by cross-correlating the observed spectrum with each spectral template within a template class over a discretely sampled redshift interval. The spectrum is then fit with an error-weighted least-squares linear combination of a single template and a low-order polynomial across the range of trial redshifts. The minimum χ2 is selected as the redshift and classification, subject to statistical constraints (detailed in Hutchinson et al., 2016).

Data Access

Location on SAS (DR14 only):


The “redmonsterAll” file is the primary output of the software. This file contains all redshift and parameter measurements, spectral classifications, and the best fit model for each object. This output is an uncompressed FITS file with all relevant information in the primary HDU header and first BIN table. The contents of the BIN table are detailed in Table 6 of Hutchinson et al. (2016). It has the naming scheme redmonsterAll-vvvvvv.fits, where vvvvvv is the version of the reduction used. This file is the parallel to the spAll file produced by spectro1d in BOSS and eBOSS.


Bautistaet al. (2018), ApJ, 863, 110

Hutchinson et al. (2016), AJ, 152, 205