FIELD: An automated emission-line detection software for Subaru/FMOS near-infrared spectroscopy
Motonari Tonegawa, Tomonori Totani, Fumihide Iwamuro, Masayuki, Akiyama, Gavin Dalton, Karl Glazebrook, Kouji Ohta, Hiroyuki Okada, and, Kiyoto Yabe

TL;DR
This paper introduces FIELD, an automated software for detecting emission lines in Subaru/FMOS near-infrared spectra, enhancing the efficiency and reliability of galaxy surveys like FastSound by reducing false detections.
Contribution
The paper presents a novel automated emission line detection algorithm tailored for FMOS data, incorporating noise suppression, bad pixel removal, and validation methods to improve detection accuracy.
Findings
False detection rate below 1% at S/N > 5
Effective noise suppression using flat-field images and masks
Reliable detection at line flux levels of ~1.0 x 10^-16 erg/cm^2/s
Abstract
We describe the development of automated emission line detection software for the Fiber Multi-Object Spectrograph (FMOS), which is a near-infrared spectrograph fed by fibers from the deg prime focus field of view of the Subaru Telescope. The software, FIELD (FMOS software for Image-based Emission Line Detection), is developed and tested mainly for the FastSound survey, which is targeting H emitting galaxies at to measure the redshift space distortion as a test of general relativity beyond . The basic algorithm is to calculate the line signal-to-noise ratio () along the wavelength direction, given by a 2-D convolution of the spectral image and a detection kernel representing a typical emission line profile. A unique feature of FMOS is its use of OH airglow suppression masks, requiring the use of flat-field images to suppress noise…
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