Published August 22, 2024 | Version v1
Dataset Open

Measuring the Variability of Hydroxyl Emissions in Infrared Sky Spectra using SPIRou: Dataset

  • 1. ROR icon Space Telescope Science Institute

Contributors

  • 1. ROR icon Space Telescope Science Institute
  • 2. ROR icon Université de Montréal

Description

Abstract

Subtracting the changing sky contribution from the near-infrared (NIR) spectra of faint astronomical
objects is challenging and crucial to a wide range of science cases such as estimating the velocity
dispersions of dwarf galaxies, studying the gas dynamics in faint galaxies, and accurate redshifts, and
any spectroscopic studies of faint targets. Since the sky background varies with time and location, NIR
spectral observations, especially those employing fiber spectrometers and targeting extended sources,
require frequent sky-only observations for calibration. However, sky subtraction can be optimized
with sufficient a priori knowledge of the sky’s variability. In this work, we explore how to optimize sky
subtraction by analyzing 1075 high-resolution NIR spectra from the CFHT’s SPIRou on Maunakea,
and we estimate the variability of 481 hydroxyl (OH) lines. These spectra were collected during two
sets of three nights dedicated to obtaining sky observations every five and a half minutes. During
the first set, we observed how the Moon affects the NIR, which has not been accurately measured at
these wavelengths. We suggest that if one uses a principal component analysis reconstruction of the
sky spectrum and attempts to observe targets at Y JHK mags fainter than ∼15 and attempts a sky
subtraction better than 1%, then the Moon contribution must be accounted for at Moon separation
distances of at least 10◦. We also identified 126 spectral doublet, or OH lines that split into at least two
components, at SPIRou’s resolution. In addition, we used Lomb-Scargle Periodograms and Gaussian
process regression to estimate most OH lines vary on similar timescales, which provides a valuable
input for IR spectroscopic survey strategies. The data and code developed for this study are publicly
available here.

Dataset description

In total, we collected 1075 sky observations, which spanned from July 28th, 2018 to January 10th, 2022, or approximately 3.5 years. These observations included two sets of three days dedicated to sky measurement where each day, a sky spectrum was observed approximately every 5.5 minutes for 12 hours. These days occurred on December 14th, 15th, and 16th of 2019 and January 22nd, 23rd, and 25th 2020. These 1D extracted and flat fielded sky spectra have a wavelength range of 0.965 − 2.500μm containing 285,377 wavelength bins resampled on a uniform wavelength grid with a step of 1 km/s/pixel. Since the pixels were constant in velocity, the change in wavelength increased from 3x10^−6 − 8x10^−6 μm per pixel. All observations were affected by a steep black body curve starting at 2.1μm, which was caused by thermal emission.

We also present a table of doublets identified during this study with the transition, the measured singlet line from Rousselot 2000 (mu0), the doublet lines (mu1 and mu2), and if the line was identified as a doublet (Y/N).

Files

transition_doublet_table.txt

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Additional details

Software

Repository URL
https://github.com/FDauphin/spirou-sky-subtraction
Programming language
Python
Development Status
Active