On-sky characterisation of the VISTA NB118 narrow-band filters at 1.19 micron

TL;DR

This paper characterizes the VISTA NB118 narrow-band filters at 1.19 microns, assessing their performance, sky brightness, and red-leak issues, and identifies candidate emission-line objects for high-redshift galaxy studies.

Contribution

It provides a detailed on-sky calibration and characterization of the VISTA NB118 filters, including passband shifts and performance metrics, enabling improved high-redshift galaxy observations.

Findings

Sky-brightness levels and depths for each filter set are provided.

Some filters exhibit red-leak contamination.

The filters' passbands are shifted by 3.5-4 nm to the red.

Abstract

Observations of the high redshift Universe through narrow-band filters have proven very successful in the last decade. The 4-meter VISTA telescope, equipped with the wide-field camera VIRCAM, offers a major step forward in wide-field near-infrared imaging, and in order to utilise VISTA's large field-of-view and sensitivity, the Dark Cosmology Centre provided a set of 16 narrow-band filters for VIRCAM. These NB118 filters are centered at a wavelength near 1.19 micron in a region with few airglow emission lines. The filters allow the detection of Halpha emitters at z = 0.8, Hbeta and [OIII] emitters at z ~ 1.4, [OII] emitters at z = 2.2, and Ly-alpha emitters at z = 8.8. Based on guaranteed time observations of the COSMOS field we here present a detailed description and characterization of the filters and their performance. In particular we provide sky-brightness levels and depths for each of the 16 detector/filter sets and find that some of the filters show signs of some red-leak. We identify a sample of 2 x 10^3 candidate emission-line objects in the data. Cross-correlating this sample with a large set of galaxies with known spectroscopic redshifts we determine the "in situ" passbands of the filters and find that they are shifted by about 3.5-4 nm (corresponding to 30% of the filter width) to the red compared to the expectation based on the laboratory measurements. Finally, we present an algorithm to mask out persistence in VIRCAM data. Scientific results extracted from the data will be presented separately.