Fiber Assignment in Next-generation Wide-field Spectrographs

TL;DR

This paper introduces an optimized fiber assignment algorithm, the draining algorithm, for next-generation spectrographs, significantly improving target observation efficiency and addressing fiber collision issues.

Contribution

The paper presents the draining algorithm, a novel fiber assignment method that enhances target observation efficiency and solves fiber collision problems in multi-object spectrographs.

Findings

The draining algorithm can increase target observation efficiency by up to 2%.

Focal plane rotation improves fiber positioning efficiency by 3.5-6%.

Optimizations can save hundreds of thousands of objects or reduce survey area.

Abstract

We present an optimized algorithm for assigning fibers to targets in next-generation fiber-fed multi-object spectrographs. The method, that we named draining algorithm, ensures that the maximum number of targets in a given target field is observed in the first few tiles. Using randomly distributed targets and mock galaxy catalogs we have estimated that the gain provided by the draining algorithm as compared to a random assignment can be as much as 2% for the first tiles. This would imply for a survey like BigBOSS saving for observation several hundred thousand objects or, alternatively, reducing the covered area in ~350 sq. deg. An important advantage of this method is that the fiber collision problem can be solved easily and in an optimal way. We also discuss additional optimizations of the fiber positioning process. In particular, we show that allowing for rotation of the focal plane can improve the efficiency of the process in ~3.5-4.5% even if only small adjustments are permitted (up to 2 deg). For instruments that allow large rotations of the focal plane the expected gain increases to ~5-6%. These results, therefore, strongly support focal plane rotation in future spectrographs, as far as the efficiency of the fiber positioning process is concerned. Finally, we discuss on the implications of our optimizations and provide some basic hints for an optimal survey strategy based on the number of targets per positioner.