Bibcode
Hutchinson, T. A.; Bolton, Adam S.; Dawson, Kyle S.; Allende Prieto, C.; Bailey, Stephen; Bautista, Julian E.; Brownstein, Joel R.; Conroy, Charlie; Guy, Julien; Myers, Adam D.; Newman, Jeffrey A.; Prakash, Abhishek; Carnero-Rosell, Aurelio; Seo, Hee-Jong; Tojeiro, Rita; Vivek, M.; Ben Zhu, Guangtun
Bibliographical reference
The Astronomical Journal, Volume 152, Issue 6, article id. 205, 17 pp. (2016).
Advertised on:
12
2016
Citations
36
Refereed citations
32
Description
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 ≲ z ≲ 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 {{Δ }}{χ }r2 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
μ ∼ 0.01 and σ ∼ 0.65, respectively, suggesting the
reported statistical redshift uncertainties are over-estimated by
∼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.