An Efficient Targeting Strategy for Multiobject Spectrograph Surveys: the Sloan Digital Sky Survey “Tiling” Algorithm

Abstract

Large surveys using multiobject spectrographs require automated methods for deciding how to efficiently point observations and how to assign targets to each pointing. The Sloan Digital Sky Survey (SDSS) will observe around 10 6 spectra from targets distributed over an area of about 10,000 deg 2 , using a multiobject fiber spectrograph that can simultaneously observe 640 objects in a circular field of view (referred to as a '' tile '') 1=49 in radius. No two fibers can be placed closer than 55 00 during the same observation; multiple targets closer than this distance are said to '' collide.'' We present here a method of allocating fibers to desired targets given a set of tile centers that includes the effects of collisions and that is nearly optimally efficient and uniform. Because of large-scale structure in the galaxy distribution (which form the bulk of the SDSS targets), a naive covering of the sky with equally spaced tiles does not yield uniform sampling. Thus, we present a heuristic for perturbing the centers of the tiles from the equally spaced distribution that provides more uniform completeness. For the SDSS sample, we can attain a sampling rate of greater than 92% for all targets, and greater than 99% for the set of targets that do not collide with each other, with an efficiency greater than 90% (defined as the fraction of available fibers assigned to targets). The methods used here may prove useful to those planning other large surveys.

Clustering of intermediate redshift quasars using the final SDSS III-BOSS sample

“…To cull areas of the survey that greatly affect the quasar density, we use veto masks developed to analyze BOSS galaxy clustering 12 (see, e.g., White et al 2011;Anderson et al 2012;Ross et al 2012a). The angular completeness of the survey is tracked in regions defined by a unique set of overlapping spectroscopic tiles (called a sector; see Blanton et al 2003). The angular completeness in each sector (called fcomp in this paper) is defined to be the ratio of the number of quasars for which good spectra are obtained to the number of all targets in the target list.…”

“…Quasar spectra in BOSS were obtained using a set of spectroscopic tiles that can be modeled as polygons using the MANGLE software (Blanton et al 2003;Tegmark et al 2004;Swanson et al 2008). The fraction of targets (quasars) in an area of the sky that has been covered by a unique set of these tiles (called a sector) is used to define the completeness of the sample.…”

“…Note that fiber collisions make it impossible to obtain spectra for quasar pairs closer than 62 ′′ except in overlapping regions (Blanton et al 2003;White et al 2012). At the mean redshift of our survey (z ≃ 2.43), 62 ′′ corresponds to a transverse comoving distance of 1.2 h −1 Mpc.…”

Constraints on cosmic hemispherical power anomalies from quasars

“…[48,49,50,51,52]. Bright galaxies [53], luminous red galaxies (LRGs) [54], and quasar candidates [55] are selected from the SDSS imaging data for spectroscopic follow-up [56]. The spectroscopic quasar sample used here was based on colour selection criteria described in Richards et al [55].…”

Correlating the CMB with luminous red galaxies: The integrated Sachs-Wolfe effect

“…The imaging is carried out by driftscanning the sky in photometric conditions [31], in five bands (ugriz) [32,33] using a specially designed widefield camera [34]. Using these data, objects are targeted for spectroscopy [35] and are observed with a 640-fiber spectrograph on the same telescope. All of these data are processed by completely automated pipelines that detect and measure photometric properties of objects, and astrometrically calibrate the data [36,37].…”