Paper
18 August 2016 DESI systems engineering: throughput and signal-to-noise
Author Affiliations +
Abstract
The Dark Energy Spectroscopic Instrument (DESI) is a fiber-fed multi-object spectroscopic instrument under construction to measure the expansion history of the Universe using the Baryon Acoustic Oscillation technique.

Management of light throughput and noise in all elements of the instrument is key to achieving the high-level DESI science requirements over the planned survey area and depth within the planned survey duration. The DESI high-level science requirements flow down to instrument performance requirements on system throughput and operational efficiency. Signal-to-noise requirements directly affect minimum required exposure time per field, which dictates the pace and duration of the entire survey. The need to maximize signal (light throughput) and to minimize noise contributions and time overhead due to reconfigurations between exposures drives the instrument subsystem requirements and technical implementation.

Throughput losses, noise contributors, and interexposure reconfiguration time are budgeted, tracked, and managed as DESI Systems Engineering resources. Current best estimates of throughput losses and noise contributions from each individual element of the instrument are tracked together in a master budget to calculate overall margin on completing the survey within the allotted time. That budget is a spreadsheet accessible to the entire DESI project.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert W. Besuner and Michael J. Sholl "DESI systems engineering: throughput and signal-to-noise", Proc. SPIE 9911, Modeling, Systems Engineering, and Project Management for Astronomy VII, 99110J (18 August 2016); https://doi.org/10.1117/12.2234022
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Cited by 3 scholarly publications.
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KEYWORDS
Telescopes

Galactic astronomy

Signal to noise ratio

Spectrographs

Systems engineering

Point spread functions

Cameras

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