The APOGEE Data Release 16 Spectral Line List

Smith, Verne V.; Bizyaev, Dmitry; Cunha, Kátia; Shetrone, Matthew; Souto, Diogo; Prieto, C. Allende; Masseron, T.; Mészáros, Szabolcs; Jönsson, Henrik; Hasselquist, Sten; Osorio, Yeisson; García–Hernández, D. A.; Plez, B.; Beaton, Rachael L.; Holtzman, Jon A.; Majewski, Steven R.; Stringfellow, Guy S.; Sobeck, Jennifer

doi:10.3847/1538-3881/abefdc

Cited by 114 publications

(87 citation statements)

References 67 publications

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“…Spectral reductions and calibrations are performed by the APOGEE data processing pipeline (Nidever et al 2015), which provides input to the APOGEE Stellar Parameters and Chemical Abundances Pipeline (ASPCAP; Holtzman et al 2015;García Pérez et al 2016). ASP-CAP uses a grid of synthetic spectral models (Mészáros et al 2012;Zamora et al 2015) and H-band linelists (Shetrone et al 2015;Hasselquist et al 2016;Cunha et al 2017;Smith et al 2021) compiled from a variety of laboratory, theoretical, and astrophysical sources, fitting effective temperatures, surface gravities, and elemental abundances.…”

Section: Apogee Data Samplementioning

confidence: 99%

Chemical Cartography with APOGEE: Mapping Disk Populations with a Two-Process Model and Residual Abundances

Weinberg,

Holtzman,

Johnson

et al. 2021

Preprint

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We apply a novel statistical analysis to measurements of 16 elemental abundances in 34,410 Milky Way disk stars from the final data release (DR17) of APOGEE-2. Building on recent work, we fit median abundance ratio trends [X/Mg] vs. [Mg/H] with a 2-process model, which decomposes abundance patterns into a "prompt" component tracing core collapse supernovae and a "delayed" component tracing Type Ia supernovae. For each sample star, we fit the amplitudes of these two components, then compute the residuals ∆[X/H] from this two-parameter fit. The rms residuals range from ∼ 0.01 − 0.03 dex for the most precisely measured APOGEE abundances to ∼ 0.1 dex for Na, V, and Ce. The correlations of residuals reveal a complex underlying structure, including a correlated element group comprised of Ca, Na, Al, K, Cr, and Ce and a separate group comprised of Ni, V, Mn, and Co. Selecting stars poorly fit by the 2-process model reveals a rich variety of physical outliers and sometimes subtle measurement errors. Residual abundances allow comparison of populations controlled for differences in metallicity and [α/Fe]. Relative to the main disk (R = 3 − 13 kpc), we find nearly identical abundance patterns in the outer disk (R = 15 − 17 kpc), 0.05-0.2 dex depressions of multiple elements in LMC and Gaia Sausage/Enceladus stars, and wild deviations (0.4-1 dex) of multiple elements in ω Cen. Residual abundance analysis opens new opportunities for discovering chemically distinctive stars and stellar populations, for empirically constraining nucleosynthetic yields, and for testing chemical evolution models that include stochasticity in the production and redistribution of elements.

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Section: Apogee Data Samplementioning

confidence: 99%

Chemical Cartography with APOGEE: Mapping Disk Populations with a Two-Process Model and Residual Abundances

Weinberg,

Holtzman,

Johnson

et al. 2021

Preprint

Self Cite

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“…Recently, however, Souto et al (2017) was able to use APOGEE spectra to extract detailed chemical abundances that paved the way for adaptations in the ASPCAP methodologies that address the atmospheres of cool dwarfs. As a result, the DR16 ASPCAP pipeline included a multiyear effort for extensive expansion of the input linelist to improve the underlying spectral synthesis to expand the range of T eff with reliable ASPCAP results (these efforts are described in Jönsson et al 2020 andSmith et al 2021). At the same time, the works of Souto et al (2020) and Birky et al (2020) establish key calibrator data sets for late-type dwarfs, although the number of appropriate calibration stars is still small in number compared to the target sample for which they are needed.…”

Section: Calibrations Clusters For Main-sequence Starsmentioning

confidence: 99%

Final Targeting Strategy for the Sloan Digital Sky Survey IV Apache Point Observatory Galactic Evolution Experiment 2 North Survey

Beaton

Oelkers

Hayes

et al. 2021

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The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is a dual-hemisphere, near-infrared (NIR), spectroscopic survey with the goal of producing a chemodynamical mapping of the Milky Way. The targeting for APOGEE-2 is complex and has evolved with time. In this paper, we present the updates and additions to the initial targeting strategy for APOGEE-2N presented in Zasowski et al. (2017). These modifications come in two implementation modes: (i) “Ancillary Science Programs” competitively awarded to Sloan Digital Sky Survey IV PIs through proposal calls in 2015 and 2017 for the pursuit of new scientific avenues outside the main survey, and (ii) an effective 1.5 yr expansion of the survey, known as the Bright Time Extension (BTX), made possible through accrued efficiency gains over the first years of the APOGEE-2N project. For the 23 distinct ancillary programs, we provide descriptions of the scientific aims, target selection, and how to identify these targets within the APOGEE-2 sample. The BTX permitted changes to the main survey strategy, the inclusion of new programs in response to scientific discoveries or to exploit major new data sets not available at the outset of the survey design, and expansions of existing programs to enhance their scientific success and reach. After describing the motivations, implementation, and assessment of these programs, we also leave a summary of lessons learned from nearly a decade of APOGEE-1 and APOGEE-2 survey operations. A companion paper, F. Santana et al. (submitted; AAS29036), provides a complementary presentation of targeting modifications relevant to APOGEE-2 operations in the Southern Hemisphere.

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“…Most of the calibrator stars fall within the range 4000 < T ef f < 7000 and log g>1. The metallicity ([F e/H]) is uncalibrated, but atomic line data used to construct the synthetic spectral libraries that were fit to the data were adjusted to match high resolution spectra of the Sun and Arcturus (Smith et al 2021). Additional details are provided in Holtzman et al (2021 in prep.…”

Section: Apogee-mastar Overlap Samplementioning

confidence: 99%

SDSS-IV MaStar: Data-driven Parameter Derivation for the MaStar Stellar Library

Imig,

Holtzman,

Yan

et al. 2021

Preprint

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The MaNGA Stellar Library (MaStar) is a large collection of high-quality empirical stellar spectra designed to cover all spectral types and ideal for use in the stellar population analysis of galaxies observed in the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. The library contains 59,266 spectra of 24,130 unique stars with spectral resolution R ∼ 1800 and covering a wavelength range of 3, 622 − 10, 354 Å. In this work, we derive five physical parameters for each spectrum in the library: effective temperature (T ef f ), surface gravity (log g), metalicity ([F e/H]), micro-turbulent velocity (log(v micro )), and alpha-element abundance ([α/F e]). These parameters are derived with a flexible data-driven algorithm that uses a neural network model. We train a neural network using the subset of 1,675 MaStar targets that have also been observed in the Apache Point Observatory Galactic Evolution Experiment (APOGEE), adopting the independently-derived APOGEE Stellar Parameter and Chemical Abundance Pipeline (ASPCAP) parameters for this reference set. For the regions of parameter space not well represented by the APOGEE training set (7, 000 ≤ T ≤ 30, 000 K), we supplement with theoretical model spectra. We present our derived parameters along with an analysis of the uncertainties and comparisons to other analyses from the literature.

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The APOGEE Data Release 16 Spectral Line List

Cited by 114 publications

References 67 publications

Chemical Cartography with APOGEE: Mapping Disk Populations with a Two-Process Model and Residual Abundances

Chemical Cartography with APOGEE: Mapping Disk Populations with a Two-Process Model and Residual Abundances

Final Targeting Strategy for the Sloan Digital Sky Survey IV Apache Point Observatory Galactic Evolution Experiment 2 North Survey

SDSS-IV MaStar: Data-driven Parameter Derivation for the MaStar Stellar Library

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