SDSS-IV MaNGA: Modeling the spectral line-spread function to subpercent accuracy

Journal article

The Sloan Digital Sky Survey IV Mapping Nearby Galaxies at APO (MaNGA) program has been operating from 2014 to 2020, and has now observed a sample of 9269 galaxies in the low redshift universe (z ∼ 0.05) with integral-field spectroscopy. With rest-optical (λλ0.36–1.0 μm) spectral resolution R ∼ 2000 the instrumental spectral line-spread function (LSF) typically has 1σ width of about 70 km s⁻¹, which poses a challenge for the study of the typically 20–30 km s⁻¹ velocity dispersion of the ionized gas in present-day disk galaxies. In this contribution, we present a major revision of the MaNGA data pipeline architecture, focusing particularly on a variety of factors impacting the effective LSF (e.g., under-sampling, spectral rectification, and data cube construction). Through comparison with external assessments of the MaNGA data provided by substantially higher-resolution R ∼ 10,000 instruments, we demonstrate that the revised MPL-10 pipeline measures the instrumental LSF sufficiently accurately (≤0.6% systematic, 2% random around the wavelength of Hα) that it enables reliable measurements of astrophysical velocity dispersions σ_Hα ∼ 20 km s⁻¹ for spaxels with emission lines detected at signal-to-noise ratio > 50. Velocity dispersions derived from [O II], Hβ, [O III], [N II], and [S II] are consistent with those derived from Hα to within about 2% at σ_Hα > 30 km s⁻¹. Although the impact of these changes to the estimated LSF will be minimal at velocity dispersions greater than about 100 km s⁻¹, scientific results from previous data releases that are based on dispersions far below the instrumental resolution should be reevaluated.

Authors: Law, DR; Westfall, KB; Bershady, MA; Cappellari, M; Yan, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: American Astronomical Society
• Journal: Astronomical Journal
• Volume: 161
• Issue: 2
• Article number: 52
• Publication date: 2021-01-06
• Acceptance date: 2020-11-13
• DOI: 10.3847/1538-3881/abcaa2
• EISSN: 1538-3881
• ISSN: 0004-6256
• Language: English
• Keywords: FFR