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SDSS-IV MaNGA: Modeling the Spectral Line Spread Function to Sub-Percent Accuracy

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 Added by David R. Law
 Publication date 2020
  fields Physics
and research's language is English




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The SDSS-IV Mapping Nearby Galaxies at APO (MaNGA) program has been operating from 2014-2020, and has now observed a sample of 9,269 galaxies in the low redshift universe (z ~ 0.05) with integral-field spectroscopy. With rest-optical (lambdalambda 0.36 - 1.0 um) spectral resolution R ~ 2000 the instrumental spectral line-spread function (LSF) typically has 1sigma width of about 70 km/s, which poses a challenge for the study of the typically 20-30 km/s 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., undersampling, 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 line spread function sufficiently accurately (<= 0.6% systematic, 2% random around the wavelength of Halpha) that it enables reliable measurements of astrophysical velocity dispersions sigma_Halpha ~ 20 km/s for spaxels with emission lines detected at SNR > 50. Velocity dispersions derived from [O II], Hbeta, [O III], [N II], and [S II] are consistent with those derived from Halpha to within about 2% at sigma_Halpha > 30 km/s. Although the impact of these changes to the estimated LSF will be minimal at velocity dispersions greater than about 100 km/s, scientific results from previous data releases that are based on dispersions far below the instrumental resolution should be reevaulated.



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Mapping Nearby Galaxies at Apache Point Observatory (MaNGA), one of three core programs in the Sloan Digital Sky Survey-IV (SDSS-IV), is an integral-field spectroscopic (IFS) survey of roughly 10,000 nearby galaxies. It employs dithered observations using 17 hexagonal bundles of 2 arcsec fibers to obtain resolved spectroscopy over a wide wavelength range of 3,600-10,300A. To map the internal variations within each galaxy, we need to perform accurate {it spectral surface photometry}, which is to calibrate the specific intensity at every spatial location sampled by each individual aperture element of the integral field unit. The calibration must correct only for the flux loss due to atmospheric throughput and the instrument response, but not for losses due to the finite geometry of the fiber aperture. This requires the use of standard star measurements to strictly separate these two flux loss factors (throughput versus geometry), a difficult challenge with standard single-fiber spectroscopy techniques due to various practical limitations. Therefore, we developed a technique for spectral surface photometry using multiple small fiber-bundles targeting standard stars simultaneously with galaxy observations. We discuss the principles of our approach and how they compare to previous efforts, and we demonstrate the precision and accuracy achieved. MaNGAs relative calibration between the wavelengths of H$alpha$ and H$beta$ has a root-mean-square (RMS) of 1.7%, while that between [NII] $lambda$6583A and [OII] $lambda$3727A has an RMS of 4.7%. Using extinction-corrected star formation rates and gas-phase metallicities as an illustration, this level of precision guarantees that flux calibration errors will be sub-dominant when estimating these quantities. The absolute calibration is better than 5% for more than 89% of MaNGAs wavelength range.
MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is an integral-field spectroscopic survey of 10,000 nearby galaxies that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). MaNGAs 17 pluggable optical fiber-bundle integral field units (IFUs) are deployed across a 3 deg field, they yield spectral coverage 3600-10,300 Ang at a typical resolution R ~ 2000, and sample the sky with 2 diameter fiber apertures with a total bundle fill factor of 56%. Observing over such a large field and range of wavelengths is particularly challenging for obtaining uniform and integral spatial coverage and resolution at all wavelengths and across each entire fiber array. Data quality is affected by the IFU construction technique, chromatic and field differential refraction, the adopted dithering strategy, and many other effects. We use numerical simulations to constrain the hardware design and observing strategy for the survey with the aim of ensuring consistent data quality that meets the survey science requirements while permitting maximum observational flexibility. We find that MaNGA science goals are best achieved with IFUs composed of a regular hexagonal grid of optical fibers with rms displacement of 5 microns or less from their nominal packing position, this goal is met by the MaNGA hardware, which achieves 3 microns rms fiber placement. We further show that MaNGA observations are best obtained in sets of three 15-minute exposures dithered along the vertices of a 1.44 arcsec equilateral triangle, these sets form the minimum observational unit, and are repeated as needed to achieve a combined signal-to-noise ratio of 5 per Angstrom per fiber in the r-band continuum at a surface brightness of 23 AB/arcsec^2. (abbrev.)
SDSS-IV MaNGA (Mapping Nearby Galaxies at Apache Point Observatory) is the largest integral-field spectroscopy survey to date, aiming to observe a statistically representative sample of 10,000 low-redshift galaxies. In this paper we study the reliability of the emission-line fluxes and kinematic properties derived by the MaNGA Data Analysis Pipeline (DAP). We describe the algorithmic choices made in the DAP with regards to measuring emission-line properties, and the effect of our adopted strategy of simultaneously fitting the continuum and line emission. The effect of random errors are quantified by studying various fit-quality metrics, idealized recovery simulations and repeat observations. This analysis demonstrates that the emission lines are well-fit in the vast majority of the MaNGA dataset and the derived fluxes and errors are statistically robust. The systematic uncertainty on emission-line properties introduced by the choice of continuum templates is also discussed. In particular, we test the effect of using different stellar libraries and simple stellar-population models on the derived emission-line fluxes and the effect of introducing different tying prescriptions for the emission-line kinematics. We show that these effects can generate large ($>$ 0.2 dex) discrepancies at low signal-to-noise and for lines with low equivalent width (EW); however, the combined effect is noticeable even for H$alpha$ EW $>$ 6~AA. We provide suggestions for optimal use of the data provided by SDSS data release 15 and propose refinements on the DAP for future MaNGA data releases.
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We introduce a new software package for modeling the point-spread function (PSF) of astronomical images, called Piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by Piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modeling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modeling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to Piff that we expect to further reduce the modeling errors in future analyses.
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