Redshift Measurement and Spectral Classification for eBOSS Galaxies with
  the Redmonster Software
  We describe the redmonster automated redshift measurement and spectral
classification software designed for the extended Baryon Oscillation
Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV). We
describe the algorithms, the template standard and requirements, and the newly
developed galaxy templates to be used on eBOSS spectra. We present results from
testing on early data from eBOSS, where we have found a 90.5% automated
redshift and spectral classification success rate for the luminous red galaxy
sample (redshifts 0.6$\lesssim z \lesssim$1.0). The redmonster performance
meets the eBOSS cosmology requirements for redshift classification and
catastrophic failures, and represents a significant improvement over the
previous pipeline. We describe the empirical processes used to determine the
optimum number of additive polynomial terms in our models and an acceptable
$\Delta\chi_r^2$ threshold for declaring statistical confidence. Statistical
errors on redshift measurement due to photon shot noise are assessed, and we
find typical values of a few tens of km s$^{-1}$. An investigation of redshift
differences in repeat observations scaled by error estimates yields a
distribution with a Gaussian mean and standard deviation of $\mu\sim$0.01 and
$\sigma\sim$0.65, respectively, suggesting the reported statistical redshift
uncertainties are over-estimated by $\sim$54%. We assess the effects of object
magnitude, signal-to-noise ratio, fiber number, and fiber head location on the
pipeline's redshift success rate. Finally, we describe directions of ongoing
development.
