# Final Targeting Strategy for the SDSS-IV APOGEE-2S Survey

Felipe A. Santana Departamento de Astronomía, Universidad de Chile, Camino El
Observatorio 1515, Las Condes, Santiago  Rachael L. Beaton Much of this work
was completed while this author was a NASA Hubble Fellow at Princeton
University.  Carnegie-Princeton Fellow  Department of Astrophysical Sciences,
Princeton University, 4 Ivy Lane, Princeton, NJ 08544  The Observatories of
the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA
91101  Kevin R. Covey Department of Physics & Astronomy, Western Washington
University, Bellingham, WA, 98225, USA  Julia E. O’Connell Departamento de
Astronomía, Universidad de Concepción, Casilla 160-C, Concepción, Chile
Penélope Longa-Peña  Unidad de Astronomía, Universidad de Antofagasta, Avenida
Angamos 601, Antofagasta 1270300, Chile  Roger Cohen  Space Telescope Science
Institute, Baltimore, MD, 21218, USA  José G. Fernández-Trincado  Instituto de
Astronomía y Ciencias Planetarias, Universidad de Atacama, Copayapu 485,
Copiapó, Chile  Christian R. Hayes Department of Astronomy, University of
Washington, Seattle, WA, 98195, USA  Gail Zasowski  Department of Physics &
Astronomy, University of Utah, Salt Lake City, UT, 84112, USA  Jennifer S.
Sobeck  Department of Astronomy, University of Washington, Seattle, WA, 98195,
USA  Steven R. Majewski  Department of Astronomy, University of Virginia,
Charlottesville, VA, 22903, USA  S. D. Chojnowski  Department of Astronomy,
New Mexico State University, Las Cruces, NM, 88001, USA  Department of
Physics, Montana State University, P.O. Box 173840, Bozeman, MT 59717-3840,
USA  Nathan De Lee  Department of Physics, Geology, and Engineering
Technology, Northern Kentucky University, Highland Heights, KY 41099, USA
Department of Physics & Astronomy, Vanderbilt University, Nashville, TN,
37235, USA  Ryan J. Oelkers  Department of Physics & Astronomy, Vanderbilt
University, Nashville, TN, 37235, USA  Guy S. Stringfellow Center for
Astrophysics and Space Astronomy, Department of Astrophysical and Planetary
Sciences, University of Colorado, Boulder, CO, 80309, USA  Andrés Almeida
Instituto de Investigación Multidisciplinario en Ciencia y Tecnología,
Universidad de La Serena. Avenida Raúl Bitrán S/N, La Serena, Chile  Borja
Anguiano  Department of Astronomy, University of Virginia, Charlottesville,
VA, 22903, USA  Department of Physics & Astronomy, Macquarie University,
Balaclava Rd, NSW 2109, Australia  John Donor  Department of Physics &
Astronomy, Texas Christian University, Fort Worth, TX, 76129, USA  Peter M.
Frinchaboy Department of Physics & Astronomy, Texas Christian University, Fort
Worth, TX, 76129, USA  Sten Hasselquist  Department of Physics & Astronomy,
University of Utah, Salt Lake City, UT, 84112, USA  NSF Astronomy and
Astrophysics Postdoctoral Fellow  Jennifer A. Johnson  Department of
Astronomy, The Ohio State University, Columbus, OH, 43210, USA  Juna A.
Kollmeier  The Observatories of the Carnegie Institution for Science, 813
Santa Barbara St., Pasadena, CA 91101  David L. Nidever  Department of
Physics, Montana State University, P.O. Box 173840, Bozeman, MT 59717-3840,
USA  Adrian. M. Price-Whelan Center for Computational Astrophysics, Flatiron
Institute, 162 Fifth Ave, New York, NY 10010, USA  Alvaro Rojas-Arriagada
Instituto de Astrofísica, Facultad de Física, Pontificia Universidad Católica
de Chile, Av. Vicuña Mackenna 4860, Santiago, Chile  Millennium Institute of
Astrophysics, Av. Vicuña Mackenna 4860, 782-0436, Macul, Santiago, Chile
Mathias Schultheis  Observatoire de la Cote d’Azur, Lagrange Boulevard de
l’Observatoire 06304 Nice, France  Matthew Shetrone  University of California
Observatories, Santa Cruz, CA 95064, USA  Joshua D. Simon  The Observatories
of the Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA
91101  Conny Aerts  Institute of Astronomy, KU Leuven, Celestijnenlaan 200D,
B-3001 Leuven, Belgium  Jura Borissova Instituto de Física y Astronomía,
Universidad de Valparaíso, Av. Gran Bretaña 1111, Playa Ancha, Casilla 5030,
Chile.  Millennium Institute of Astrophysics, Av. Vicuña Mackenna 4860,
782-0436, Macul, Santiago, Chile  Maria R. Drout  The Observatories of the
Carnegie Institution for Science, 813 Santa Barbara St., Pasadena, CA 91101
Department of Astronomy and Astrophysics, University of Toronto, 50 St. George
Street, Toronto, Ontario, M5S 3H4 Canada  Doug Geisler  Departamento de
Astronomía, Universidad de Concepción, Casilla 160-C, Concepción, Chile
Instituto de Investigación Multidisciplinario en Ciencia y Tecnología,
Universidad de La Serena. Avenida Raúl Bitrán S/N, La Serena, Chile
Departamento de Astronomia, Facultad de Ciencias, Universidad de La Serena.
Av. Juan Cisternas 1200, La Serena, Chile  C.Y. Law  Department of Space,
Earth & Environment, Chalmers University of Technology, SE-412 96 Gothenburg,
Sweden  Department of Physics, The Chinese University of Hong Kong, Shatin,
NT, Hong Kong SAR  Nicolas Medina  Instituto de Física y Astronomía,
Universidad de Valparaíso, Av. Gran Bretaña 1111, Playa Ancha, Casilla 5030,
Chile.  Millennium Institute of Astrophysics (MAS), Santiago, Chile.  Dante
Minniti Departamento de Ciencias Físicas, Facultad de Ciencias Exactas,
Universidad Andrés Bello, Fernández Concha 700, Las Condes, Santiago, Chile
Vatican Observatory, Vatican City State, V-00120, Italy  Antonela Monachesi
Instituto de Investigación Multidisciplinario en Ciencia y Tecnología,
Universidad de La Serena. Avenida Raúl Bitrán S/N, La Serena, Chile
Departamento de Astronomia, Facultad de Ciencias, Universidad de La Serena.
Av. Juan Cisternas 1200, La Serena, Chile  Ricardo R. Muñoz  Departamento de
Astronomía, Universidad de Chile, Camino El Observatorio 1515, Las Condes,
Santiago  Radosław Poleski Astronomical Observatory, University of Warsaw, Al.
Ujazdowskie 4, 00-478 Warszawa, Poland  Department of Astronomy, The Ohio
State University, Columbus, OH, 43210, USA  Alexandre Roman-Lopes Departamento
de Astronomia, Facultad de Ciencias, Universidad de La Serena. Av. Juan
Cisternas 1200, La Serena, Chile  Kevin C. Schlaufman Department of Physics
and Astronomy, Johns Hopkins University, 3400 N Charles St., Baltimore, MD
21218, USA  Amelia M. Stutz  Departamento de Astronomía, Universidad de
Concepción, Casilla 160-C, Concepción, Chile  Johanna Teske  NASA Hubble
Fellow  Earth and Planets Laboratory, Carnegie Institution for Science, 5241
Broad Branch Road, NW, Washington, DC 20015, USA  Much of this work was
completed while this author was a NASA Hubble Fellow at the Observatories of
the Carnegie Institution for Science.  Andrew Tkachenko  Institute of
Astronomy, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium  Jennifer
L. Van Saders  Institute for Astronomy, University of Hawai’i, 2680 Woodlawn
Drive, Honolulu, HI 96822, USA  Alycia Weinberger  Earth and Planets
Laboratory, Carnegie Institution for Science, 5241 Broad Branch Road, NW,
Washington, DC 20015, USA  Manuela Zoccali  Millennium Institute of
Astrophysics, Av. Vicuña Mackenna 4860, 782-0436, Macul, Santiago, Chile
Instituto de Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña
Mackenna 4860, 782-0436 Macul, Santiago, Chile

###### Abstract

APOGEE is a high-resolution ($R\sim 22,000$), near-infrared, multi-epoch,
spectroscopic survey of the Milky Way. The second generation of the APOGEE
project, APOGEE-2, includes an expansion of the survey to the Southern
Hemisphere called APOGEE-2S. This expansion enabled APOGEE to perform a fully
panoramic mapping of all the main regions of the Milky Way; in particular, by
operating in the $H$-band, APOGEE is uniquely able to probe the dust-hidden
inner regions of the Milky Way that are best accessed from the Southern
Hemisphere. In this paper we present the targeting strategy of APOGEE-2S, with
special attention to documenting modifications to the original, previously
published plan. The motivation for these changes is explained as well as an
assessment of their effectiveness in achieving their intended scientific
objective. In anticipation of this being the last paper detailing APOGEE
targeting, we present an accounting of all such information complete through
the end of the APOGEE-2S project; this includes several main survey programs
dedicated to exploration of major stellar populations and regions of the Milky
Way, as well as a full list of programs contributing to the APOGEE database
through allocations of observing time by the Chilean National Time Allocation
Committee (CNTAC) and the Carnegie Institution for Science (CIS).

Astronomical Databases – Galaxy abundances – Galaxy dynamics – Galaxy
evolution – Galaxy formation – Galaxy kinematics – Galaxy stellar content –
Galaxy structure – Milky Way Galaxy – Surveys

††facilities: Du Pont (APOGEE), Sloan (APOGEE), Spitzer, _WISE_ , 2MASS,
SkyMapper, Gaia††software:  Astropy (Astropy Collaboration et al., 2013,
2018), NumPy (van der Walt et al., 2011; Harris et al., 2020), TopCat (Taylor,
2005)

##  1 Introduction

Detailed analyses of the different substructures of the Milky Way and the
physical processes that govern their interplay require high precision,
homogeneous, large data samples covering all of its main regions. In that
sense, modern photometric surveys like the Sloan Digital Sky Survey (SDSS;
York et al., 2000) or the Two Micron All-Sky Survey (2MASS; Skrutskie et al.,
2006) have been key to expanding our knowledge about our Milky Way. The
remarkable discoveries enabled by these SDSS and 2MASS imaging include: (i) a
large population of ultrafaint dwarf galaxies and low luminosity star clusters
(Belokurov et al., 2007; Koposov et al., 2007; Belokurov et al., 2010), (ii)
constraints on the morphology of both the stellar and dark matter halo (e.g.,
Majewski et al., 2003; Helmi, 2004; Johnston et al., 2005; Law et al., 2005;
Belokurov et al., 2006; Jurić et al., 2008; Law & Majewski, 2010; Deg &
Widrow, 2013), (iii) tidal tails from both disrupting star clusters and Milky
Way satellite galaxies (e.g., Ivezić et al., 2000; Odenkirchen et al., 2001;
Newberg et al., 2002; Majewski et al., 2003; Grillmair & Johnson, 2006;
Grillmair & Dionatos, 2006; Grillmair, 2009), (iv) multiple stellar
populations in globular clusters (e.g., Lardo et al., 2011; Gratton et al.,
2012), and (v) the characterization of complex substructures in the bulge/bar
association using red clump stars (e.g., McWilliam & Zoccali, 2010; Saito et
al., 2011; Wegg et al., 2015).

Despite the importance of photometric surveys in addressing these topics, full
chemo-dynamical models of the Milky Way require input from precise and large-
scale spectroscopic datasets. In this sense, a large number of recent
spectroscopic Galactic surveys have enabled mapping the large phase space
covered by the different stellar populations of the Milky Way, and the
intrinsic properties of those stars, e.g., their masses, temperatures,
chemistry and evolutionary stages. Some examples of the contributions from
these surveys have been the new estimates of escape velocity and mass of the
Milky Way by Piffl et al. (2014) using data from the Radial Velocity
Experiment (RAVE; Steinmetz et al., 2006), and the constraints on the
formation and evolution of the thin disk, thick disk and halo (Lee et al.,
2011; Schlaufman et al., 2009, 2011, 2012) using data from the Sloan Extension
for Galactic Understanding and Exploration survey (SEGUE; Yanny et al., 2009).

Most major spectroscopic surveys of the Milky Way performed to date, including
SEGUE (Yanny et al., 2009, C. Rokosi et al. (in prep.)), RAVE (Steinmetz et
al., 2006), Gaia-ESO (Gilmore et al., 2012) LAMOST (Cui et al., 2012), and
GALAH (Martell et al., 2017) use the optical range of the electromagnetic
spectrum. As a result, their sampling of both the inner Galaxy and within the
Galactic plane is extremely limited due to the severe attenuation of optical
light by dust. However, the Galactic mid-plane, inner disk and Milky Way bulge
are critical to understanding Galactic evolution because these regions of
highest stellar density contain the vast majority of the Milky Way’s stellar
mass as well as stellar populations spanning the largest range in chemical
composition and age.

The need for a panoramic, homogeneous, high-precision, spectroscopic study
throughout all the major components of the Milky Way motivated the inception
of the Apache Point Galactic Evolution Experiment (APOGEE; Majewski et al.,
2017). APOGEE is a high-resolution ($R\sim 22,500$), near-infrared (NIR;
$\lambda=1.51$–$1.70\,{\rm\mu m}$), multi-epoch, spectroscopic survey of the
Milky Way. During its first generation (2011-2014; hereafter APOGEE-1), the
survey was one of the projects within SDSS-III (Eisenstein et al., 2011), and
provided spectra for $\sim 163,000$ stars with a signal-to-noise ratio ($S/N$)
of $\sim 100$, covering a large variety of Galactic environments. Along with
the spectra, APOGEE-1 provided high level data products derived from the
spectra — fundamental stellar parameters like radial velocity, effective
temperature, surface gravity, and chemical abundances for 15 elements, the
latter derived via the APOGEE Stellar Parameter and Chemical Abundance
Pipeline (ASPCAP; García Pérez et al., 2016); were released in DR12 (Holtzman
et al., 2015).

APOGEE data have been applied to a wide variety of topics in stellar
astrophysics and Galactic archaeology. APOGEE-enabled research covers a wide
range of Galactic environments allowing for the detailed study of the Milky
Way’s main structures: the disk (Bovy et al., 2012; Frinchaboy et al., 2013;
Bovy et al., 2014; Nidever et al., 2014; Hayden et al., 2015; Martig et al.,
2015; Anders et al., 2017; Schiavon et al., 2017; Mackereth et al., 2017;
Hayes et al., 2018b; Donor et al., 2018; Mackereth et al., 2019a; Hasselquist
et al., 2019a; Eilers et al., 2019; Frankel et al., 2019; Donor et al., 2020),
the bulge (Nidever et al., 2015; Ness et al., 2016; Schultheis et al., 2014;
Zasowski et al., 2016, 2019; Weinberg et al., 2019; Hasselquist et al., 2020a;
Rojas-Arriagada et al., 2020a; Griffith et al., 2021), and the halo
(Fernández-Alvar et al., 2017, 2018; Hayes et al., 2018c; Helmi et al., 2018;
Mackereth et al., 2019b; Fernández-Alvar et al., 2019; Mackereth & Bovy,
2020), as well as it’s constituent globular clusters, satellite galaxies, and
tidal streams (Majewski et al., 2013; Mészáros et al., 2015; Hasselquist et
al., 2017; Schiavon et al., 2017; Fu et al., 2018; Hasselquist et al., 2019b;
Masseron et al., 2019; Hayes et al., 2020; Horta et al., 2020; Mészáros et
al., 2020a).

In addition to better understanding the Milky Way through classic Galactic
astronomy exploration, as APOGEE-1 was originally designed to perform, the
APOGEE dataset has also been used to study fields outside of it’s original
intent, delving into stellar astrophysics (Pinsonneault et al., 2014; Epstein
et al., 2014; Pinsonneault et al., 2018; Mackereth et al., 2021), studies of
the ISM (Schultheis et al., 2014; Zasowski et al., 2015b, a), and even time
series analyses of radial velocity variability as an indicator of stellar
companions (Troup et al., 2016; Badenes et al., 2018; Clark Cunningham et al.,
2019; Price-Whelan et al., 2020; Mazzola et al., 2020), planet hosts (Fleming
et al., 2015; Cañas et al., 2018; Wilson et al., 2018; Cañas et al., 2019a, b)
and intrinsically variable stars (Chojnowski et al., 2015, 2019, 2020; Lewis
et al., 2020).

This diversity of topics addressed is only possible because of the efforts put
into the careful creation of the APOGEE data, which, on the one hand, needs to
sample a broad range of stellar types and populations, but, on the other hand,
must be chosen with simple enough criteria that a reliable selection function
can be generated. The selection criteria used to select stars for the
different science programs in APOGEE-1 were presented in Zasowski et al.
(2013), which includes details on how these criteria have been optimized for
the survey science goals, the tools required to calculate and account for the
selection function, and how the different selection methods are identified
using a set of targeting bits.

The second generation of the APOGEE project (APOGEE-2; S. Majewski et al. in
prep.) is part of SDSS-IV (2014-2020; Blanton et al., 2017), and uses near-
twin spectrographs (described in Wilson et al., 2019) operating simultaneously
in the Northern and Southern Hemispheres. the original spectrograph used for
APOGEE-1, remains mounted on the Sloan Foundation 2.5-meter telescope at the
Apache Point Observatory (APO; Gunn et al., 2006), and is carrying out
observations for the APOGEE-2 North (APOGEE-2N) program, while a second, near-
clone spectrograph, APOGEE-S, (Wilson et al., 2019) is mounted on the Irénée
du Pont 2.5-meter telescope (Bowen & Vaughan, 1973) at Las Campanas
Observatory (LCO), where it is used to execute the APOGEE-2 South (APOGEE-2S)
observing program.

The expansion to the Southern Hemisphere in APOGEE-2 has provided the survey a
truly panoramic view of the Milky Way, but, particularly, its “dust-hidden”
inner regions. The initial observational design of APOGEE-2 was explained in
Zasowski et al. (2017, hereafter Z17), which included a detailed description
for each of the distinct science programs planned for APOGEE-2 and was
published alongside the first data release from APOGEE-2 (in DR14 Abolfathi et
al., 2018; Holtzman et al., 2018), It also included a general overview of a
survey component unique to APOGEE-2S, that of Contributed Programs,
observations allocated outside of SDSS-IV via proposals to use the APOGEE-S
instrument through either the the Chilean National Time Allocation Committee
(CNTAC) or the Time Allocation Committee (TAC) for the Observatories of the
Carnegie Institution for Science (OCIS). However, Z17 was written before
survey observations on the du Pont had commenced, and before the first
Contributed Programs had even been scheduled111Time for Contributed Programs
were allocated for observing semesters starting in 2017A and continued until
2020A.. Thus, the first description of APOGEE-2S targeting (Z17) both did not
contain details for the Contributed Programs, and

The main goal of this paper is to present the targeting strategy adopted for
APOGEE-2S through the final stage of the APOGEE-2S operations that ended in
January 2021. The target selection methods for APOGEE-2S have evolved since
the publication of Z17, and hence, could not have been contained in that or
other past references. Such changes were implemented after a detailed
consideration of the early on-sky performance from APOGEE-2S (DR16 was the
first public release of data obtained with APOGEE-S spectrograph; Ahumada et
al., 2020; Jönsson et al., 2020), in particular, the true observing efficiency
and instrumental through-put. With the experience and operational strategies
of APOGEE-1 and APOGEE-2N in hand (see concluding section of R. Beaton et al.
(submitted; AAS29028)), we were able to optimize the observations for
APOGEE-2S in a timely manner. We demonstrate how those modifications not only
increase the likelihood of reaching our initial scientific goals, but also
enabled us to exceed them in many cases.

Alongside this present paper, R. Beaton et al. (submitted; AAS29028) presents
the final targeting strategy of APOGEE-2N, which is focused on its Bright Time
eXtension and ancillary programs. Both papers are intended to complete the
references about APOGEE target selection and complement the existing APOGEE
targeting selection references (; ), the data release references (Ahumada et
al. 2020, Jönsson et al. 2020), and our online documentation (e.g.,
https://www.sdss.org/dr16/ for DR16, https://www.sdss.org/dr17/ for DR17).
Together, these papers present the final field plan spatial coverage of
APOGEE-2, as well as the statistics of our observing schedule. The papers
focus on how the targeting strategy changed from that presented in Z17,
explaining these differences for each scientific program separately, and also
detailing the characteristics of any new programs. These articles also
represent a unique opportunity to analyze how the differences between
APOGEE-2S and APOGEE-2N, in terms of timeline of implementation, observing
time availability per local sidereal time (LST), and telescope
characteristics, impacted on the targeting strategy and observing progress for
some programs. In this paper dedicated to APOGEE-2S we also present
descriptions for each of the programs contributed to the SDSS-IV survey from
CIS and CNTAC allocations; the Contributed Programs represent $\sim$23% of the
total observing time for APOGEE-2S survey from 2017 to 2020 (For comparison,
the APOGEE-2N Ancillary Programs were approximately 5% of the 6-year program)
and are a significant component of the APOGEE-2s dataset.

The outline of the paper is as follows: Section 2 defines key concepts
associated with that are relevant to targeting. Section 3 gives an overview of
how the different types of APOGEE-2S fibers (science, sky, and calibration)
are assigned. Changes to the original field plan and targeting strategy for
APOGEE-2S are given in Section 4 . Contributed Programs are detailed in
Section 5. A summary is given in Section 6. A glossary of common terms used in
this paper is presented in Appendix A to aid the reader.

##  2 APOGEE Observations & Targeting Basics

In this section, we provide a summary of the primary methods used for
selecting targets in APOGEE; much of this material is also presented in Z13,
Z17, and R. Beaton et al. (submitted; AAS29028), because these are the core
set of principles guiding the design of all APOGEE observations. Key SDSS- and
APOGEE-specific concepts and terms affiliated with the process are described
and defined; such terms are first introduced in quotation marks (e.g., “term”)
to indicate that they are specific technical terms. The key nomenclature are
also organized as a Glossary in Appendix A as a convenience (following that of
Z13 and Z17, but also including the new terms used for this present paper). We
also note that this section will include some detailed discussions on
important topics that will be useful to guide the reader through the content
of this paper.

Throughout this paper we will also refer to different “tags” that are part of
various APOGEE-2 data products, and we will use their official names in those
files to aid the user in finding data of interest. Each time we refer to one
of those “tags’ we will use true-type fonts, (e.g., LOCATION_ID), and they
will generally correspond to the ones present in the summary files allStar and
allVisit, but they can also be found in several other APOGEE data products.

For reviewing the full description of the APOGEE data products, we refer the
reader to our online
documentation.222https://www.sdss.org/dr16/irspec/spectro_data/

###  2.1 Concepts and Nomenclature

##### Fields:

The full observing program consists of a set of “fields.” A field is a
particular location in the sky defined by a central coordinate and a radius
that defines the field-of-view (FOV). Targets are then selected for fields
according to specific criteria that define where holes are to be drilled in
corresponding fiber optic plugplates.

Each field is uniquely identified using an integer known as the “location ID”
(in the data products, LOCATION_ID). We also assign a name to each field
stored in the FIELD tag that follows the naming scheme of $LLL$+$BB$, where
$LLL$ and $BB$ represent the central Galactic longitude and latitude rounded
to the closest integer; for example, a field centered at Galactic coordinates
$(\ell,b)=(44.76,-8.64)$ would have a field name of 045$-$09\. Some exceptions
exist to this naming scheme for fields dedicated to specific astronomical
objects like dwarf galaxies (e.g., with names like ‘CARINA’ or ‘LMC1’) or star
clusters (like ‘N6441’). Fields that are close to each other on the sky may
have the same name, but they will always have a unique location ID.

For Contributed Programs, a suffix is added to the name that indicates the
Time Allocation Committee (TAC) awarding the program. Fields from programs
assigned through the CNTAC have a “-C” suffix, and fields from the OCIS TAC
programs have an “-O” suffix . A particularly large Contributed Program
allocated through OCIS that focuses on NASA’s Transiting Exoplanet Survey
Satellite (TESS, Ricker et al., 2015) Southern Continuous Viewing Zone have
the suffix “-O_TESS” (see Subsection 5.8).

##### Plates:

To observe our targets in APOGEE-2S, we use standard SDSS plug-plates that
hold the APOGEE-S fibers at the desired target and a “plate” corresponds to
the physical piece of metal used to hold the fibers at their sky positions,
and each is identified with a plate ID. When drilling a design of stars into a
plate, atmospheric refraction corrections need to be taken into account to
calculate the positions of the fibers on the plate and these corrections vary
depending on the altitude and azimuth of the field over the night. For this
reason, a “drill angle” needs to be specified for each plate, which
corresponds to the hour angle (HA) at which a plate is intended to be
observed; the same set of targets can occupy plates drilled to different hour
angles to increase the chances that that particular design will get observed.
Each plate is thus associated with a particular design and HA combination.

##### Design:

Each APOGEE plate includes a set of stars for observation referred to as its
“design.” While multiple plates can have stars in common, even a implies that
uniquely identified with its own design ID.

A design is composed of one, two, or three “cohorts”, which are sets of stars
restricted to a specific magnitude range. Stars are split into cohorts that
receive different amounts of total exposure time such that all stars in a
design will obtain roughly the same $S/N$ over the full range of magnitudes.
Bright stars are grouped into “short cohorts” (meaning that this group of
stars would receive a relatively short amount of total exposure time via a
smaller number of “visits” to those stars — see below), medium brightness
stars into “medium cohorts”, and the faintest stars are grouped into “long
cohorts” (receiving the largest amount of total exposure time).

Each design has a cohort “version,” which is a three digit number of the form
$sml$ where $s$, $m$, and $l$ identify which of that field’s short, medium,
and long cohorts (uniquely numbered starting with 1), respectively, are
included in that design. For example, a design for a given field that includes
the second short cohort, the first medium cohort, and no long cohort would
have cohort version $210$. A design can, therefore, be thought of as a
combination of a field and a cohort version. In their Figure 1, Z13 provides a
schematic example of how different cohorts are combined into different designs
and distinct plates for a single APOGEE field.

Figure 1: Example of an APOGEE-2S plate. a smaller area on the sky (due to
telescope plate scale differences), have a slightly different layout (compare
to Figure 13 in Majewski et al. 2017). Most obviously, there is a central hole
for an on-axis acquisition camera and another rectangular hole for an off-axis
camera. These fiber exclusion regions are taken into account in the target
selection and plate design software. Another difference with APOGEE-N plates
is that all plate markings, including coding of the holes to denote bright,
medium and faint fibers, are automatically printed for the APOGEE-S plates,
whereas they are hand-marked for the APOGEE-N plates . Photo by R. Beaton.

##### Visits:

The amount of time each star is observed is measured in “visits”, where a
single visit corresponds to a standard length of integration of $\sim$1 hour.
Exposures are observed in pairs due to the need for half-pixel dithering in
the spectral domain implemented for the recovery of Nyquist sampling of the
native resolution delivered by the spectrograph optics onto the detectors (see
Majewski et al. 2017; Wilson et al. 2019); in the Data Processing and
Reduction pipeline (DRP; Nidever et al., 2015), these pairs of individually
under-sampled exposures are effectively blended together via interpolation to
achieve proper sampling of the resolution element (for the DR16
implementation, see Jönsson et al., 2020). In the end, a standard visit
corresponds to a single sequence of observations comprised of eight exposures
with a dither sequence of ABBA ABBA (where A and B refer to the two nominal
dither positions), which sums to a total of 4000 seconds (the same as with
APOGEE-2N). In APOGEE-2, exceptions to this scheme were applied to those
fields that contained five or more extremely faint stars ($H$ $\gtrsim$ 13.5).
For these cases, the observing sequence was modified to enhance the exposure-
level or visit-level $S/N$ for these targets in a particular visit.
Modifications could occur in two forms: (i) “DAB” exposures, where only a
single ABBA sequence occurs with each exposure at double length (for the same
sum total exposure of 4000 seconds), thereby reducing the relative
contribution of readnoise, and (ii) “TDAB” exposures (for “triple DAB”), where
an extra, double length exposure AB pair is added to the sequence for a total
visit length of 6000 seconds (ABBAAB).

##### Plate Design:

The process of assigning targets to fibers takes into account the physical
size of the fibers on the plate to avoid collisions between fibers and also
considers regions in the focal plane used by each of the two acquisition
cameras. Figure 1 provides an example of an APOGEE-S plate. The ferrule that
contains each fiber has a diameter equivalent to $56\arcsec$ in the focal
plane and this physical size sets the lower limit of allowable separation
between two fibers below which they will “collide” ( the fiber collision
radius for APOGEE-N plates is 72$\arcsec$). For initial field acquisition, a
central and off-axis acquisition cameras (Manta G-235B) are employed; this is
different to the setup for the Northern system, which relies upon coherent
fiber bundles for field acquisition. These cameras are used to zero-in on the
central location of the pointing, determine the rotational alignment, and
measure the focal plane scale. Use of these cameras creates regions that are
not available for science fibers, and candidate targets at these positions are
not permitted. As shown in Figure 1, these two acquisition cameras, which
directly attach to the fiber plugplate, create exclusion zones in the center
of the plate (with a circular footprint $5.5\arcmin$ in diameter) and
somewhere off-axis that varies with each plate (with a rectangular footprint
occupying an area equivalent to approximately $10\arcmin\times 7\arcmin$).
Though the physical plates in the South are the same physical size as the
plates for APOGEE-N, due to differences in the telescope plate scales, the
APOGEE-S plates cover a smaller area than APOGEE-N. Ignoring the above
exclusion zones, the maximal field-of-view of an APOGEE-S plate is 2.8 deg2
(corresponding to a 1.9∘ diameter), compared to the 7.1 deg2 FOV for APOGEE-N
(corresponding to a 3.0∘ diameter) (for a discussion of maximal FOV versus the
drillable FOV, see section 2.1 of Z17, ). To see other differences between the
APOGEE-N and APOGEE-S plates, compare Figure 1 here to Figure 13 in Majewski
et al. (2017).

###  2.2 Targeting Bits

Like APOGEE-1, APOGEE-2 uses target flags to indicate the reason why each
target was selected for observation; the flags are encoded using bitmasks .
These flags are set to help reconstruct the target selection function of the
survey. Note, however, that use of these flags may not allow for the complete
retrieval of a desired set of stars. As one example, stars selected for
observation because they are red clump (RC) candidates have bit 25 set in
APOGEE2_TARGET2, but a large number of RC stars are serendipitously included
in our sample, and hence, will not have that bit set .

The APOGEE-2 targeting bit labels are APOGEE2_TARGET1, APOGEE2_TARGET2,
APOGEE2_TARGET3, and, the recently defined, APOGEE2_TARGET4. Currently,
APOGEE2_TARGET4 has no assigned bits, but we anticipate that it will be used
for the final APOGEE-2 data release (DR17). Table 1 provides a summary of all
APOGEE-2 targeting bits for both APOGEE-2N and APOGEE-2S.

=1.7in  APOGEE2_TARGET1 APOGEE2_TARGET2 APOGEE2_TARGET3 Bit Criterion Bit
Criterion Bit Criterion 0 Single $(J-K_{s})_{0}>0.5$ bin 0 K2 GAP Program 0
KOI target 1 “Blue” $0.5<(J-K_{s})_{0}<0.8$ bin 1 California Cloud Target 1
Eclipsing binary 2 “Red” $(J-K_{s})_{0}>0.8$ bin 2 Abundance/parameters
standard 2 KOI control target 3 Dereddened with RJCE/IRAC 3 RV standard 3 M
dwarf 4 Dereddened with RJCE/WISE 4 Sky fiber 4 Substellar companion search
target 5 Dereddened with SFD $E(B-V)$ 5 External survey calibration 5 Young
cluster target 6 No dereddening 6 Internal survey calibration (APOGEE-1+2) 6
K2 Star 7 Washington+DDO51 giant 7 Outer Disk Substructure Member 7 APOGEE2
Target 8 Washington+DDO51 dwarf 8 Outer Disk Substructure Candidate 8
Ancillary target 9 Probable (open) cluster member 9 Telluric calibrator 9
Massive Star 10 Globular Cluster Candidate 10 Calibration cluster member 10 –
QSOs 11 Short cohort (1–3 visits) 11 K2 Planet Host 11 – Cepheids 12 Medium
cohort (3–6 visits) 12 – Kepler Synchronized Binaries 12 – The Distant Disk 13
Long cohort (12–24 visits) 13 Literature calibration 13 – Emission Line Stars
14 Random sample member 14 Gaia-ESO overlap 14 – Moving Groups 15 MaNGA-led
design 15 ARGOS overlap 15 – NGC 6791 Populations 16 Single
$(J-K_{s})_{0}>0.3$ bin 16 Gaia overlap 16 – Cannon Calibrators 17 No
Washington+DDO51 classification 17 GALAH overlap 17 – Faint APOKASC Giants 18
Confirmed tidal stream member 18 RAVE overlap 18 – W3-4-5 Star Forming Regions
19 Potential tidal stream member 19 APOGEE-2S commissioning target 19 –
Massive Evolved Stars 20 Confirmed dSph member (non Sgr) 20 Halo Member 20 –
Extinction Law 21 Potential dSph member (non Sgr) 21 Halo Candidate 21 –
Kepler M Dwarfs 22 Confirmed Mag Cloud member 22 1-m target 22 – AGB Stars 23
Potential Mag Cloud member 23 Modified bright limit cohort ($H>10$) 23 – M33
Clusters 24 RR Lyra star 24 Carnegie (CIS) program target 24 – Ultracool
Dwarfs 25 Potential bulge RC star 25 Chilean (CNTAC) community target 25 –
SEGUE Giants 26 Sgr dSph member 26 Proprietary program target 26 – Cepheids 27
APOKASC “giant” sample 27 N-CVZ OBAF stars 27 – Kapteyn Field SA57 28 APOKASC
“dwarf” sample 28 N-CVZ GI Programs 28 – K2 M Dwarfs 29 “Faint” target 29
N-CVZ CTL star 29 – RV Variables 30 APOKASC sample 30 N-CVZ Giant with RPMJ 30
– M31 Disk Note 2: Flags that are new or different than what was presented in
Z17 are highlighted in bold.

Table 1: APOGEE-2 Targeting Bits  Figure 2:  Final APOGEE field plan in
Galactic coordinates with APOGEE-2S fields from the main survey highlighted in
color. The color-coding corresponds to the scientific program affiliated with
the field. The background image corresponds to the dust map from Schlegel et
al. (1998) and grey fields correspond to the APOGEE-1 and APOGEE-2N fields for
context. For completeness, we also show the other components of the APOGEE
survey (APOGEE-1 and APOGEE-2N) as grey semi-transparent circles. The
meridians are spaced every $\Delta\ell$=90∘ and the parallels are spaced every
$\Delta b$=30∘ .

###  2.3 Targeting Flag Changes

In the middle of 2020, targeting flags to ensure the consistency of their
application for APOGEE-2 targeting. In the course of this process, we fixed
some flags that were set incorrectly for certain classes of stars, added new
targeting flags, and slightly modified some of the flag definitions to match
better how they were used.

In Table 1, we present all of the APOGEE2_TARGET1, APOGEE2_TARGET2, and
APOGEE2_TARGET3 flag bits and their descriptions.

, we list all the APOGEE-2 related targeting flags that were modified, either
in their definition or in their implementation. Those flags that are
highlighted in Table 1, but are not listed in this section are new flags that
have been defined since Z17 but were only used for APOGEE-2N, with their
descriptions given in R. Beaton et al. (submitted; AAS29028). The one
exception is APOGEE2_TARGET1=6, which was used for K2 targeting and is
described in Section 4.7.

APOGEE2_TARGET1=29: “Faint” target.
Even though this flag was defined prior to the review, it had only been used
for a small group of targets for which it was set “manually” in plate design.
To make this flag consistent with its description, we systematically compared
the $H$ magnitudes of stars with the number of visits they were planned to
receive. We then flagged all stars that had fewer visits planned than what
they needed to reach the nominal $S/N$ value lower limit of $100$ in Table 2.
We highlight that there is a type of stars in out sample called “special
target” (see Subsubsection 3.3.2) for which this flag was not set because the
$S/N$ goals associated with those stars is, on occasion, different than the
ones for the rest of our sample.

APOGEE2_TARGET2=16: Gaia overlap.
This flag was previously designed to be used to flag any stars that overlapped
with the Gaia no stars were intentionally targeted because of their overlap
with did not serve to identify a reason for why specific stars were targeted.
given that Gaia is photometrically-complete well beyond APOGEE-2’s faintest
magnitude limits, such a flag would nominally include nearly all of APOGEE-2’s
targets. In addition, a Gaia cross-match is provided with APOGEE-2 data
products (e.g., Jönsson et al., 2020, and for DR17 a crossmatch with EDR3,
Holtzman et al. in prep.), providing a clearer way to identify that stars have
overlap between Gaia and APOGEE. Since overlap with Gaia could be easily
ascertained from other information provided by APOGEE-2, this flag, therefore,
had less meaning than originally intended.

The meaning of this targeting flag has been changed to identify any targets
that explicitly used Gaia data (almost exclusively proper motions) for the
target selection process, and we have set this flag for those stars.

APOGEE2_TARGET1=10: Globular Cluster Candidate.
A new flag used for globular cluster candidates that were selected either by
photometry only or by membership probabilities based on proper motions. At the
time of their selection no such flag existed, so targets selected as Globular
Cluster candidates were not identified in any way. This has now been remedied.

APOGEE2_TARGET2=0: K2 GAP Program.
This is a new flag defined to identify targets selected because they were part
the K2 Galactic Archaeology Program (GAP) (Stello et al., 2017). Most of these
stars were already flagged with APOGEE2_TARGET3=6, which is used for all K2
targets, but now all K2 targets, additionally, have flags associated with
their .

APOGEE2_TARGET2=20: Halo Members.
This flag was selected as part of the APOGEE-2N Bright Time eXtension (BTX).
Now we have extended the meaning of this flag to include a similar class of
stars in APOGEE-2S that were selected using information from the SkyMapper
survey (Keller et al., 2007), Subsubsection 4.3.1.

APOGEE2_TARGET2=21: Halo Candidates.
originally defined to be used for stars from the APOGEE-2N BTX, but halo
candidates from APOGEE-2S that were selected using Gaia proper motion
information (Subsubsection 4.3.1).

##  3 Targeting Selection Overview

For APOGEE-2, the $300$ fibers of each APOGEE spectrograph are divided among
$250$ science targets, $35$ sky targets, and $15$ telluric targets.333APOGEE-1
used $230$ fibers for science targets, $35$ for sky targets, and $35$ for
telluric targets. See Z17 for the motivations for this change. This section
provides an overview of how each of these targets types are selected.

###  3.1 Telluric Absorption Calibration Targets

The wavelength range of the APOGEE spectrographs contains a number of
contaminant spectral features from the Earth’s atmosphere . To measure the
telluric absorption we need to observe stars whose spectra are as close as
possible to a featureless blackbody in each field for this purpose. The
spectra of these stars are processed by the APOGEE data reduction pipeline to
make the telluric corrections (apred; Nidever et al., 2015; Holtzman et al.,
2018; Jönsson et al., 2020). To take into account angular variations in the
telluric absorption during observations, telluric calibrators are spatially
distributed across the plugplate as homogeneously as possible. For this
purpose, the FOV for each field is divided into a number of segmented, equal-
area zones (Figure 8 of Z13 provides a zone schematic) . These stars are the
first ones selected for APOGEE-2S plates and can be identified with bit 9 in
APOGEE2_TARGET2.

###  3.2 Sky Contamination Calibration Targets

The APOGEE data reduction pipeline uses observations of “empty” sky regions to
monitor the airglow and other foreground and background emissions. To select
sky targets in a field, we first select candidate positions that correspond to
locations that have no 2MASS sources within a $6\arcsec$ radius. Then, as we
do for selecting telluric absorption calibrators (Subsection 3.1), the
plugplate FOV is split into equal area zones (Figure 8 of Z13 provides a zone
schematic) and we select up to eight candidate positions for each zone, to
create the final list of sky positions. These fibers are the third and last
type of targets selected in APOGEE plates. Sky positions will have bit 4 set
in APOGEE2_TARGET2, but typically these spectra are not kept throughout the
reduction process.

###  3.3 Science Target Selection

Our science programs are designed to address many distinct scientific goals,
which can require targeting specific Galactic sub-components or specific
stellar types. The subsections that follow explain the most important aspects
of the science target selection process.

science targets are selected after telluric correction targets but before sky
targets are selected. There are two major types of science targets in APOGEE,
the “main red star” sample, which is randomly selected to map the bulge, disk,
or halo based on , and “special targets”, which correspond to specific high
priority targets (e.g., red clump, stream members, RR Lyr stars). In this
latter class, targets can be selected using complex combinations of
photometric, chemical, and kinematical information.

“Special targets” have top priority and then the “main red star” sample is the
source for all remaining fibers. In the following subsections, we explain how
these two types of stars are selected.

####  3.3.1 Main Red Star Sample

The “main red star” sample comprises the majority of the APOGEE-2S stars by
number. The underlying targeting strategy for this sample is a simple color-
magnitude criterion to select stars from the bulge, disk, and halo (these are
given in Table 3).

To select targets for the “main red star” sample, we start with all of the
objects in the 2MASS Point Source Catalog (PSC; Skrutskie et al., 2006) that
fall in the FOV of a given field. The NIR photometry is complemented by mid-IR
photometry from either the Spitzer$+$IRAC GLIMPSE (Benjamin et al., 2005;
Churchwell et al., 2009) or the AllWise (Wright et al., 2010) . The Rayleigh-
Jeans Color Excess method (RJCE) to estimate the line-of-sight extinction for
each individual target (Majewski et al., 2011; Zasowski et al., 2013, 2017,
also discussed below). Data quality limits are applied to ensure that the
sources have small magnitude uncertainties and reliable quality photometry
flags (for the specifics, we refer the reader to Table 2 of Z17, ).

Table 2: Cohort Visits and Magnitude Limits NVisits | Hmin | Hmax
---|---|---
| [mag] | [mag]
1 | 7.0 | 11.0
3 | 11.0 | 12.2
6 | 12.2 | 12.8
12 | 12.8 | 13.3
24 | 13.3 | 13.8

To maximize the number of giant stars targeted while ensuring a simple
selection function, we apply a simple color selection using the de-reddened
$(J-K_{\rm s})_{0}$ color. For most APOGEE fields, we use the RJCE method to
estimate $E(J-K_{\rm s})$ (Majewski et al., 2011); RJCE assumes that, for
filters sampling the Rayleigh-Jeans tail of stellar spectra, all stars
nominally have the same color such that any deviation from that baseline color
(in this case we adopt the $(H-I2)$ or $(H-W2)$ indices) is due to foreground
dust.

RJCE is known to be less reliable when the total $E(J-K_{\rm s})$ is of order
the color-uncertainty in a given field; . To avoid the overestimation of
$E(J-K_{\rm s})$ for low extinction halo fields, the reddening was determined
using the dust maps from Schlegel et al. (1998).

Because multiple dereddening methods are used, the targeting flags indicate
the method adopted for a given target. More specifically, the dereddening
method used for each target is indicated by the APOGEE2_TARGET1 flags recorded
in: bit $3$ for RJCE using Spitzer$+$IRAC, bit $4$ for RJCE using _WISE_ , bit
$5$ using Schlegel et al. (1998), or bit $6$ if no de-redenning was applied to
that target. In addition to the targeting flags, the summary files contain a
number of convenience tags that provide the values used for extinction; these
include AK_TARG for the $A_{K}$ used in targeting, AK_TARG_METHOD with a
string defining the method, AK_WISE with the all sky RJCE value from WISE
photometry, and SFD_EBV with the all sky value from Schlegel et al.
(1998)444For additional description, please see the data model here:
https://data.sdss.org/datamodel/files/APOGEE_ASPCAP/APRED_VERS/ASPCAP_VERS/allStar.html.
The appropriate 2MASS, WISE and Spitzer photometry, when available, is also
provided in the summary files.

The color criteria for selecting red stars in a given field depends on the
Galactic component being targeted; these criteria are summarized in Table 3.
The color selection strategy employed for each target is indicated in the
APOGEE2_TARGET1 flag by bit 0 for $(J-K_{\rm s})_{0}$ > 0.5, bit 1 for the
“blue” bin of $0.5~{}\leq~{}(J-K_{s})_{0}$ < 0.8, bit 2 for the “red” bin of
$(J-K_{\rm s})_{0}$ > 0.8, and, bit 16 for $(J-K_{\rm s})_{0}$ > 0.3.

Table 3: Color Cuts for Galactic Regions  Galactic | $\ell$ | $b$ | Color Selectiona | Targeting Flag in APOGEE2_TARGET1b
---|---|---|---|---
Region | Range | Range | [mag] | bit | Description
Bulge | < 20∘or > 340∘ | < 25∘ | $0.5~{}\leq~{}(J-K_{\rm s})_{0}$ | 0 | APOGEE2_ONEBIN_GT_0_5
Disk |  $\geq$ 20∘and $\leq$ 340∘ | < 25∘ |  $0.5~{}\leq~{}(J-K_{s})_{0}$ < 0.8 | 1 | APOGEE2_TWOBIN_0_5_TO_0_8
|  |  | $0.8~{}\leq~{}(J-K_{\rm s})_{0}$ | 2 | APOGEE2_TWOBIN_GT_0_8
Halo | no $\ell$ limits |  $\geq$ 25∘ | $0.3~{}\leq~{}(J-K_{\rm s})_{0}$ | 16 | APOGEE2_ONEBIN_GT_0_3
(a) The values for a star are coded in the MIN_JK and MAX_JK tags.
(b) The equivalent bit for APOGEE1 is APOGEE1_TARGET1 and it follows the same
definitions.

For some fields targeting the halo ($|b|~{}\geq$ 25∘), we apply an additional
photometric criterion designed to distinguish between dwarf and giant stars of
the same spectral type. This classification is performed by combining the
Washington filter system with the $DDO51$ filter (hereafter W+D), an
intermediate-band filter that spans the surface gravity-sensitive Mgb feature
in the spectra of cool stars, to construct a color-color diagram, $(M-T_{2})$
against $(M-DDO51)$. Because of the gravity sensitivity of the $DDO51$ filter
(McClure, 1973) and $T_{\rm eff}$ sensitivity of the Washington filters (here
$M$ and $T2$ Canterna, 1976), this color-color space provides an effective
means of selecting likely giants even in dense foregrounds (e.g., Geisler,
1984; Majewski et al., 2000; Muñoz et al., 2005). Z13 (Z17) provides a
detailed discussion of how this photometry is used for APOGEE-1 (APOGEE-2)
targeting. This same methodology is used for the APOGEE-2S targeting when W+D
photometry was available (the photometry and its application are discussed in
Z17). When assigning priorities to the targeting in halo fields that have W+D
photometry, the first priority were W+D selected giants, then stars with no
W+D classification, and lastly, W+D classified dwarfs were used to fill
remaining fibers.

Finally, to attain a goal $S/N$ of $100$ per pixel in the spectra, magnitude
limits must be set on the targets that are selected for each design. Because
each field design has short, medium, or long cohorts that receive different
numbers of visits, the magnitude limits applied to the cohorts are modified
according to the number of visits that each cohort will receive (following
Table 2). The total number of visits for a field is typically equivalent to
the number of visits planned for the longest cohort (i.e., faintest target)
included in its designs.

####  3.3.2 Special Targets

Some APOGEE-2S fields are designed with special scientific goals in mind and,
therefore, include a list of specific stars to be targeted at the highest
priority, which we refer to broadly as “special targets.” Typically, “special
targets” are provided by a specific Science Working Group in prioritized lists
. In some cases, the “special targets” for an APOGEE-2S field may use all of
the available fibers, as in the Large Magellanic Cloud program , while other
programs only require a handful of fibers, as in the Open Cluster program. Any
remaining, unallocated fibers are used to bolster the “main red star” sample.

The Working Group for each APOGEE-2S program sets their own criteria to select
high priority targets; Table 4 provides a brief summary of these programs.
Details about the original selection method used for all APOGEE-2S programs is
described in Z17. Stars that were selected as different types of “special
targets” can also be identified according to their set targeting bits (Table
1).

Table 4: Summary of APOGEE-2S Main Survey Programs  Name |  Total Fields |  Total Visits |  Section |  Special Target Flags |  Systems Included |  Additional References (if applicable) |  PROGRAMNAME
---|---|---|---|---|---|---|---
Bulge |  $56$ |  $347$ |  4.2 |  — |  — |  Z17 |  bulge
Disk |  $78$ |  $579$ |  — |  — |  — |  Z17 |  disk, disk1, disk2
Halo |  $15$ |  $126$ |  4.3.1 |  Target1=18 Target2=20,21 |  Sagittarius stream, Orphan stream |  Z17 for main red star sample; Hayes et al. (2018b) for Sagittarius stream targets |  halo, halo2_stream
Streams |  $26$ |  $132$ |  4.3.2 |  Target1=18,26 Target2=20,21 |  Jhelum stream, Orphan stream |  — |  sgr_tidal, stream_halo, stream_disk
Open Clusters |  $15$ |  $87$ |  4.6 |  Target1=9 |  Berkeley 75, Berkeley 81, M 8, M 16, M 67, NGC 2204, NGC 2243, NGC 6253, NGC 5999, NGC 6583, NGC 6603, Trumpler 20, Trumpler 32, Tombaugh 2, Collinder 261 |  Donor et al. (2018) |  cluster_oc
Globular Clusters |  $20$ |  $147$ |  4.8 |  Target1=10 Target2=2,10 |  47 Tucanae, M 10, M 12, M 22, M 4, M 55, M 68, M 79, NGC 1851, NGC 2808, NGC 288, NGC 2298, NGC 3201, NGC 362, NGC 6388, NGC 6397, NGC 6441, NGC 6752, Omega Centauri |  — |  cluster_gc
Magellanic Clouds |  $48$ |  $483$ |  4.5 |  Target1=22,23 |  LMC, SMC |  Nidever et al. (2020) |  magclouds
Dwarf Spheroidals |  $4$ |  $96$ |  4.4 |  Target1=20,21 |  Carina, Sextans, Sculptor , Fornax |  Z17 |  halo_dsph
Sagittarius |  $6$ |  $36$ |  — |  Target1=26 Target2=10 |  Sagittarius dwarf core |  — |  sgr
K2 |  $87$ |  $87$ |  4.7 |  Target1=30 Target2=0,11 Target3=6,28 |  K2 Campaigns: C6, C8, C10, C14, C15, C17 |  R. Beaton et al. (submitted; AAS29028) |  k2

##  4 Changes to the Main Survey

In this section we detail all the changes made to the targeting strategy,
which includes the target selection and field locations of APOGEE-2S, with
respect to the original plan given in Z17. Subsection 4.1 provides the
motivation for these changes and, in particular, contains an overview of the
time-allocation for APOGEE-2S. After this overview, the subsections that
follow are organized by APOGEE-2S science program and describe the changes
applied to the targeting strategy.

###  4.1 Motivation

One of the main motivations for this paper is to describe modifications to the
original APOGEE-2S survey strategy described in Z17. These modifications
occurred for three reasons: (1) internal evaluations via Targeting Reviews of
whether the survey strategies in place would enable APOGEE-2S to achieve its
scientific goals, (2) the advent of new data from surveys outside of SDSS
(e.g., Gaia) that could significantly enhance APOGEE targeting efficiency, and
(3) modifications to the main survey plan due to alterations in the observing
schedule.

Internal evaluations of all APOGEE-2 programs occurred on an approximately
yearly basis. For some scientific programs, the review suggested that a
modification to the original targeting strategy was needed to meet the science
goals, or that the program would significantly benefit from considering
additional aspects for the target selection process. In other cases, the sky-
efficiency was either lower or higher than originally estimated; this
particularly occurred at some local sidereal time (LST) windows for which the
weather was better than our adopted weather model.

Additional motivations for modifying the targeting strategy came by way of
previously unavailable information from space-based missions like Gaia (Gaia
Collaboration et al., 2016a, b, 2018), the K2 mission of the Kepler spacecraft
(Howell et al., 2014), or TESS (Ricker et al., 2015), as well as complementary
ground-based surveys like GALAH (Zucker et al., 2012), SkyMapper (Keller et
al., 2007), or RAVE (Steinmetz et al., 2006; Kunder et al., 2017).

Finally, modifications to the APOGEE-2S observing schedule occurred both
because of the addition of some nights to the originally expected allocation
or shifts in the scheduled time a delay in commissioning and a forced and
lengthy closure of Las Campanas Observatory due to the COVID19 pandemic near
the end of the survey. The total observing hours and their distribution
throughout the year determine the total number of visits we expect to observe
at each LST, and thus, are crucial for estimating the fields that we will be
able to observe. All of these factors were considered simultaneously to design
and implement modifications to what became a somewhat dynamic targeting
scheme, but one that always pointed at maximizing scientific return.

In the end, a total of 352 nights were allocated for the Main Survey
programs555With 10 nights in 2017 used for the commissioning of the APOGEE-S
spectrograph, which are not counted toward the Main Survey observing total. .
More details about the allocation of du Pont 2.5-m time to the APOGEE project
will be given in the forthcoming APOGEE-2 overview paper (S. Majewski et al.
in prep.).

The final field map for the APOGEE-2S Survey is given in Figure 2, where we
show the positions, in Galactic coordinates, for all the Main Survey APOGEE-2S
fields. The fields in APOGEE-2S are color-coded by their science program. We
also show in grey circles the APOGEE-1 and APOGEE-2N fields to exhibit the
overall coverage of the APOGEE survey. This figure shows how APOGEE-2S makes
APOGEE a truly panoramic survey reaching all regions and components of the
Milky Way by covering regions inaccessible from the Northern Hemisphere, most
notably the inner Galactic regions.

####  4.1.1 Observing efficiency of APOGEE-2S and resulting modification to
visit plan

The observing efficiency of continuously calculated and compared to the
initial estimate . The original observing plan of the survey was constructed
assuming a seasonally averaged observing efficiency of $\sim$4.7 visits per
night, and involved $1493$ visits planned to be observed over the entire
survey period from .

During the first year of the survey (2017), operational strategies were under
development and initial plate delivery timescales were sometimes mismatched to
the optimal observation dates. This translated in miscalculations of the
visits expected per LST for the first plateruns, which in turn resulted in
nights that had some unused visits because there were no suitable plates.
Additionally, confronted with a completely new instrument and still evolving
observing infrastructure that had many significant differences with that in
place for decades at APO, the APOGEE-2S engineering and observing teams took
some time to optimize operational strategies and software and to become
proficient in their use. Together, these factors translated to a lower than
expected efficiency of $\sim$3.1 visits per night during that year (65% of the
anticipated efficiency). These initial challenges, however, were solved and,
for and the first half of , the observing efficiency grew to $\sim$5.8 and
$\sim$5.5 visits per night, respectively (123% and 117% of the anticipated
efficiency).

Assuming that the observing efficiency would remain constant until the end of
the survey, we re-estimated that our overall observing efficiency would be
$\sim$ 5.0 visits per night. Using this new efficiency, we concluded that in
our total APOGEE-2S nights we would be able to observe $\sim 224$ visits more
than our original expectations. For this reason, the original field plan was
modified from a $1493$ visit plan, to one containing $1717$ total visits. From
these extra visits $58$ (26%) were necessary to account for the modifications
made to the Bulge and RRL Programs, while the others were used to observe new
fields that were not in the original targeting plan.

####  4.1.2 COVID-19 Shutdown and Final Plan

Due to the COVID-19 pandemic’s global spread in early 2020, LCO shut down all
operations in mid-March 2020. This included APOGEE-2S, which had to stop
operations about 6 months before the nominal conclusion of the APOGEE-2S
survey. Ultimately, this resulted in a loss of 77 originally planned APOGEE-2S
nights . When LCO reopened in early October 2020, APOGEE-2S was granted an
extension that encompasses the original 77 nights lost due to the COVID-
related closure as well as 11 additional nights.

The total APOGEE-2S extension period includes 88 nights over the October 20,
2020 - January 21, 2020 time frame . While this extension allowed APOGEE-2S to
(more than) recover its lost time, the allocated nights gave very little
access to the same portion of the sky, which necessitated a major overhaul of
the plan for the remainder of the survey, with modified objectives to make
compelling use of the altered sky access. The most notable impact on the
survey was a loss of almost the entire final year (i.e., about 1/3) of the
planned APOGEE observations of the central Milky Way.

The COVID-19 extension left a projected 403 visits to fill with newly drilled
plates, but a short timeline in which to produce them, and with the imminent
danger that any resumption of operations might be tentative. Under such
circumstances, it was decided that the most expeditious path forward was to
expand those APOGEE-2S programs already primarily focused on those regions of
the sky — namely the Magellanic Cloud and the Galactic Halo Programs, both of
which would not only benefit from greater coverage, but also could be flexible
in the event of additional closures or extensions. With the extra 403 visits
from the COVID-19 extension the APOGEE-2S observing plan reached its
definitive version, consisting of 2120 visits, whose sky coverage is shown in
Figure 2. In the end, despite numerous obstacles the survey had overcome, the
size of the final observing plan represents an increase of $\sim{42\%}$ with
respect to the original $1493$-visit plan, albeit with some shift in emphasis
from that originally envisioned.

The following sections present all of the changes to the APOGEE-2S
observations originally planned and presented in Z17. organized by scientific
program.

Table 5: APOGEE-2S Galactic Bulge Observing Plans  |  |  |  | “Short” Cohort | “Medium” Cohort | “Long” Cohort
---|---|---|---|---|---|---
Plan | Stars | Visits | Fields |  $H<11.0$ Stars |  $11.0<H<12.2$ Stars |  $12.2<H<12.8$ Stars
|  |  |  | $S/N>100$ | $80<S/N<100$ | $S/N>100$ | $80<S/N<100$ | $S/N>100$ | $80<S/N<100$
Original | 33374 | 264 | 61 | 22751 | 0 | 10223 | 0 | 400 | 0
New | 27168 | 347 | 56 | 10355 | 0 | 6525 | 3732 | 6253 | 303
Percent Change | -19% | +31% | -9% | -55% | 0% | -37% |  | +1463% |
Figure 3: The APOGEE-2S coverage and depth plan for the Galactic bulge. The
full Galactic bulge region is shown with medium (red) and long (blue) fields
indicated. (a) The original plan, which was composed of 3-visit fields to a
depth of $H\sim$12.2 (red), with three deeper pointings at $\ell$=0∘(blue).
(b) The final plan, which demonstrates the increase in fields reaching
$H\sim$12.8 (blue), the elimination of some fields (black crosses), as well as
the fields that were properly designed for $H\sim$12.2 that were unchanged. As
discussed in the text, the result of these modifications to the survey is that
our mapping of the Galactic bulge goes deeper and has built a larger sample of
bone-fide bulge stars (see e.g., Rojas-Arriagada et al., 2020a; Hasselquist et
al., 2020a).

###  4.2 The Milky Way Bulge

In May 2018 that, due to an error in the execution of the targeting selection
software, a significant fraction of the plates in the Bulge Program contained
stars fainter than the originally intended magnitude limit for the plate
(e.g., see Table 2). In this subsection, we will briefly explain the origin of
this problem, the actions taken to resolve it, and how the implemented
solution, along with an increased observing efficiency, fortuitously resulted
in a deeper, more complete survey of the Galactic bulge than originally
planned.

####  4.2.1 The Problem

The spatial distribution of the fields in the Bulge Program is given in Figure
3, which shows the original plan (Figure 3a) and the final plan (Figure 3b).
The color-coding in Figure 3 indicates the targeting depth of either $H$=12.2
($S/N$=100 in 3-visits; red) or $H$=12.8 ($S/N$=100 in 6-visits; blue). The
intended Bulge Program (Figure 3a; Z17) was to sample the bulk of the Galactic
bulge region in a grid with plates going to $H$=12.2 depth, with a handful of
deeper fields at strategic locations designed to complement the APOGEE-1 Bulge
Program (Z13). However, the Bulge Program that was implemented in the target
selection software is shown in Figure 3b; the latter reflects the fact that
the majority of the bulge fields were inadvertently drilled with stars as
faint as $H$=12.8 (blue) and, given that observations had already begun, the
options to resolve the problem were limited. Were the nominal survey minimum
$S/N$ requirement enforced, completion of the observing plan shown in Figure
3b would have required about twice as much time as was available for the Bulge
Program.

More specifically, the original Bulge Program (Figure 3a) contained 34 fields
meant to be observed with 3-plates each. Each of the fields included three
short cohorts scheduled for 1-visit each and a single medium cohort scheduled
for 3 visits (in the cohort nomenclature introduced earlier, a “310 plate”).
Ten of the bulge fields were intended to have 6-visits total, but in order to
observe more of the stars in these dense bulge fields, they were intended to
have a 3-visit depth like the above fields, having two pairs of 3-visit medium
cohorts and six 1-visit short cohorts (e.g., a 620 cohort complement, with two
sets of 310). In both the 3-visit and 6-visit fields, the 1-visit short
cohorts were erroneously filled with stars as faint as $H$=12.2 (i.e., what is
normally a 3-visit depth) and some of the 3-visit cohorts were filled with
stars as faint as $H$=12.8 (i.e., the normal 6-visit depth). This is
problematic for APOGEE observations, because, in 1-visit, the faintest stars
in the short cohorts would be expected to achieve $S/N\sim 58$ and, in
3-visits, the faintest stars in the medium cohorts should reach $S/N\sim 75$ —
i.e., neither cohort satisfying the APOGEE goal of $S/N$=100 for all
targets.666For context, the ASPCAP pipeline automatically flags anything with
$S/N<70$ with SN_WARN or bit 11 of ASPCAPFLAG (see Table 11 of Holtzman et
al., 2015).

While the fields just described formed the bulk of the bulge design problem,
there were other bulge fields where the magnitude limits were properly set
given the scheduled number of visits, and a few fields where the number of
visits was larger needed . However,

####  4.2.2 The Solution

By the time this situation was discovered, a significant fraction of the
problematical plates had already been drilled, and some were even observed.
For that reason, re-designing, re-drilling, and re-shipping these plates with
the aim of restoring the original plan was deemed impractical, and a solution
was sought that optimized utilizing the plates already in hand. This required
finding a compromise between $S/N$ needs and other modifications that made
optimal use of the available, bulge-accessible observing nights for APOGEE-2S.

The solution that was devised involved the following action items:

  * •

Cancel all pending visits to plates that would yield $S/N>100$ for the
faintest stars on the plate . The three fields involved correspond to those
indicated by blue circles in Figure 3a and Figure 3b.

  * •

Cancel visits for the second set of three plates for the 6-plate fields (i.e.,
remove the second 310 cohort set from a 620 cohort complement field). Because
there are no common stars between the two sets of medium cohorts (and all
1-visit cohorts are distinct), canceling one set does not affect the $S/N$ of
the stars in the other set. This change maintains our spatial coverage, but
with a smaller total sample in those fields.

  * •

Cancel fields from bulge regions that had another field nearby and/or a field
symmetric with respect to the $\ell=0$∘ axis. These fields are indicated with
an ‘x’ marker in Figure 3b.

  * •

Increase the number of total visits for cohorts whose faintest stars are
$H\sim 12.2$ stars from 1-visit to 2 visits. This change ensures that all
targets reach $S/N>\sim 80$ .

  * •

Increase the number of total visits for cohorts whose faintest stars have
$H\sim 12.8$ from 3 visits to 6 visits. This change ensures that all stars in
these fields reach $S/N>$100.

Implementation of the above action items required a net increase in the total
number of visits assigned to the Bulge Program from 264 to 347 visits (a 31%
increase).

we elected to cancel the 25 Main Survey visits allocated to the Bulge RR Lyrae
(RRL) Program described in Z17 their section 4.9. At the time that the Bulge
Program was redesigned, a Contributed Program with the same goals (Subsection
5.6) had already completed a number of visits that far exceeded the 25-visits
initially scheduled as part of the original APOGEE-2S targeting plan. Since
the Contributed Program data become part of the overall APOGEE-2 dataset, the
Science Requirement goal for the Main Survey RRL program ($\sim$4000 stars)
had formally been met (albeit not through the route intended), whereas, at the
time, the “main red star” sample from the Bulge Program were not meeting their
Science Requirement.

58 more visits had to be found to complete the new observation plan for the
Bulge Program. At that point in the survey (October 2018), based on evidence
for a growing APOGEE-2S observational efficiency that would deliver a mean
value that exceeded the estimate used in the design of the original survey (as
discussed in Section 4.1), we found that the remaining 58 visits would be made
up through faster completion of plates overall.

####  4.2.3 Summary of Bulge Modifications

Table 5 provides a summary of the most relevant information about the intended
and actual Bulge Programs, in which we can see that even though the total
number of bulge targets has lessened from the original plan by $\sim 19\%$
($6206$ stars), the stars “lost” in the modified plan are the brightest, with
$H<11.0$; typically, stars brighter than $H\sim 11$ are more likely to be disk
stars in the foreground to the bulge. The new plan significantly increases the
number of stars in the magnitude range $12.2<H<12.8$, which were practically
non-existent in the original plan . It is also worth mentioning that even
though the new plan will produce $\sim$15% of stars observed in the Bulge
Program with $S/N<100$ per pixel, these stars will obtain, at a minimum,
$S/N\sim 80$ per pixel, which does not represent a considerable cost to our
science goals given current pipeline performance (Jönsson et al., 2020;
Majewski et al., 2017).

###  4.3 Galactic Halo and Stellar Streams

The observing scheme for the Galactic halo and halo substructure in APOGEE-2
(both APOGEE-2N and APOGEE-2S) changed significantly from that presented in
Z17. The original Halo Program was a uniform grid of pointings out of the
Galactic plane, covering a range in $|b|$ from $30$ to $75$ degrees. While
visits were set aside to sample streams in APOGEE-2N, no stellar stream
observations were planned for APOGEE-2S, with the exception of a single field
targeting the Sagittarius stellar stream (field name SRGT-2).

In APOGEE-2S, only two of the original halo grid fields, 280+45 and 320+45,
were . The targets for these halo fields were selected using a color criterion
of $(J-K_{\rm s})_{0}>0.3$ (dereddened color and employing the W+D giant
method, Subsubsection 3.3.1) and no other targeting criterion. , however, were
designed using a new targeting strategy .

Then, the final APOGEE-2S Halo Program totals 41 fields and 258 visits: 48
visits split between the original 280+45 and 320+45 dedicated halo fields, 78
visits divided among the 13 new dedicated halo fields, 12 visits in the
original dedicated stream field SGRT-2, and 120 visits split between the 25
new dedicated stream fields. The specific targeting priorities for each of
these programs and their specific fields are given in the next subsections.

Dedicated halo fields have PROGRAMNAME tag value “halo”777There is one
exception for the field 066-79 that has PROGRAMNAME “halo2_stream” due to an
error. and their field names were assigned based on their Galactic coordinates
like all disk and bulge fields. For the dedicated stream fields, Sgr stream
fields have PROGRAMNAME “sgr_tidal,” and other stream fields have PROGRAMNAME
of “stream_halo” or “stream_disk,” depending on the Galactic coordinates, and
the field names for this program indicate the stellar stream being targeted.

####  4.3.1 More Efficient Halo Targeting

In this section we explain . An analysis of the data from APOGEE-2N halo
observations suggested that the target selection was not observing enough
stars at large line-of-sight distances to place them securely in the outer
halo. This process and resulting changes are described in our companion paper
on APOGEE-2N targeting R. Beaton et al. (submitted; AAS29028), but we
summarize the key results here.

Prior to the Bright Time Extension (BTX), the Halo Program for APOGEE-2N
relied on “deep” and “narrow-area” targeting relying on the Washington$+DDO51$
photometry technique to identify likely giant stars from the dwarf star
foreground (see ; , ). While this strategy worked at $\sim$80% efficiency to
identify giants, the method was not particularly effective at identifying
stars whose distances placed them securely in the outer halo; specific
heliocentric distance limits were made in the APOGEE-2 Science Requirements
Document for a certain number of halo stars to be surveyed at $>$15 kpc and
$>$25 kpc, whereas the actual yields were around 3$\times$ smaller than
anticipated for survey goals ( R. Beaton et al. submitted; AAS29028). By
studying the proper motions of distant stars identified in APOGEE-1 and
APOGEE-2N, it was found that proper motions could be used to remove the vast
majority of the foreground dwarf contamination, which, in turn, greatly
increased the likelihood of targeting a rare distant giant in a given field.
As shown in R. Beaton et al. (submitted; AAS29028), the distant star yields
using this procedure were between 2-3 times more effective than the original
selection procedure. Because the APOGEE-2S halo targeting had not yet been
fully implemented when the investigations described in R. Beaton et al.
(submitted; AAS29028) were concluded, it was possible to incorporate the
results of that investigation en masse for the APOGEE-2S Halo Program.

To maximize the number of halo stars in our APOGEE-2S Halo Program, we
selected targets using the following priority ranking:

  1. 1.

The highest halo candidate/member priority targets were selected from the
SkyMapper survey (Keller et al., 2007). Casagrande et al. (2019) used
SkyMapper ($uvgriz$) and 2MASS ($JHK$) photometry to produce $T_{\rm
eff,phot}$ estimates at a precision of $\sim$100 K, metallicity estimates at
0.2 dex precision (for [Fe/H]$>-2$), and a reliable dwarf/giant separation.
Using these data,888The catalog is available:
https://github.com/casaluca/SkyMapper. halo candidates were identified using
the following criteria: [Fe/H]phot<$-0.9$ and 3200 K $<$ $T_{\rm eff,phot}$
$<$ 5500 K. Stars targeted using these photometric stellar parameters have bit
20 set in APOGEE2_TARGET2. This targets were included in all the fields from
our Halo Program excepting the two original dedicated halo fields 280+45 and
320+45.

  2. 2.

Then, we selected proper motion candidates taken from the Gaia DR2 (Gaia
Collaboration et al., 2018). The criteria for selecting these stars was $\mu$
< 5 mas yr-1 and $\sigma_{\rm{\mu}}/\mu$< 0.1 for all the 13 new dedicated
halo fields, and < 5 mas yr-1 and $\sigma_{\rm{\mu}}$< 0.2 for the 18 new
sgr_tidal stream dedicated fields. For the 15 fields sgr_tidal4 to sgr_tidal18
a magnitude limit of $H<13.3$ was used for selecting these stars, while a
magnitude limit of $H<12.8$ was used for all other fields, which is standard
for 6-visits fields (see Table 2). Stars selected using these proper motion
restrictions have bit 21 set in APOGEE2_TARGET2 flag.

  3. 3.

Then, for all APOGEE-2S Halo program fields containing W+D photometry we
incorporated W+D photometric giant candidates (see Subsubsection 3.3.1) and
these targets have bit 7 set in APOGEE2_TARGET1.

  4. 4.

Finally, all APOGEE-2S Halo program fields that still have remaining
unassigned fibers are back-filled with stars from the “main red star” sample
following the magnitude and color ranges appropriate for the number of visits,
as given in Tables 2 and 3, respectively.

Figure 4:  Comparison of the targeting efficiency for giants in Halo Programs.
We compare the original halo targeting from APOGEE-2N that relied on
Washington$+DDO51$ (“OG Halo N;” blue circles), the BTX APOGEE-2N targeting
(“Halo BTX;” purple circles), and the APOGEE-2S halo targeting (“Halo S;”
green triangles). For these figures, we only consider those stars that have
measured stellar parameters ($\log{g}$ and $T_{\rm eff}$) and we utilize
spectrophotometric distances following the analysis described in Rojas-
Arriagada et al. (2020b, and references therein). (a) Number of stars in
different distance bins. (b) Overall efficiency at identifying distant halo
stars normalized by the total fiber hours in the program. The total fiber
hours are computed by summing the number of visits that contribute to the
final spectrum used for ASPCAP analyses for all of the targets in the program
(NVISITS).

In Figure 4, we show the efficiency of the different halo targeting strategies
used throughout APOGEE-2. (i) the original method used for APOGEE-2N based on
W+D photometry for giant-dwarf pre-classification (labelled “OG Halo N”), (ii)
the method used in the APOGEE-2N BTX based on HSOY proper motion selection
(Altmann et al., 2017) and SEGUE-confirmed distant K-giants (labelled “Halo
BTX”) (Xue et al., 2014), and (iii) the modified APOGEE-2S halo selection
described here, based on SkyMapper data and proper motion information
(labelled “Halo S”).

The left panel of Figure 4 shows the number of stars from each Halo Program
obtained within broad distance bins. Overall, the total number of stars in
each distance bin is more-or-less consistent between the three targeting
methods, but to compare how successful each method was we also need to
consider the observing time invested in each Halo Program. Thus, to calculate
the efficiency of each method, we normalized the number of stars observed
within each distance bin by the total number of “fiber hours” from each
program, where a fiber hour is one visit for a single fiber from a plate, and
a single plate visit has a total of 265 fiber hours dedicated to stars.

The right panel of Figure 4 shows the number of Halo Program stars obtained
per distance bin divided by the total number of fiber hours associated with
each Halo Program. The APOGEE-2S strategy is about 3 times more effective than
the original APOGEE-2N halo strategy in terms of observing distant halo stars
for all distance bins. This demonstrates that altering the targeting strategy
for APOGEE-2S has resulted in a much more efficient method for pre-selecting
distant halo stars than originally used in APOGEE-2. On the other hand, the
APOGEE-2S and APOGEE-2N BTX halo targeting strategies show similar
efficiencies, as displayed in Figure 4b. Achieving this for APOGEE-2S is
remarkable given that APOGEE-2N includes known halo members from SEGUE which
were not available for APOGEE-2S, and the plates in APOGEE-2N have a larger
FOV that enable mapping larger region of the sky in a single visit.

####  4.3.2 Targeting Stellar Streams

To increase the number of halo stars in APOGEE-2S while simultaneously
sampling halo substructure, we added 25 dedicated fields, whose locations were
placed on the footprints of known stellar streams. This represents one of the
most important changes to our observing plan, considering that originally the
Halo Program only contained one dedicated stream field called SGRT-2. The 26
dedicated stream fields were designed targeting three streams in the Southern
Hemisphere, and were split in the following way:

  1. 1.

19 fields placed on the Saggitarius (Sgr) stream, consisting of field SGRT-2,
fields Sgr_tidal1 to Sgr_tidal3, and fields sgr_tidal4 to sgr_tidal18. All
these fields have PROGRAMNAME “sgr_tidal”

  2. 2.

6 fields (JHelum1 to JHelum6) placed on the JHelum stream. All these fields
have PROGRAMNAME “stream_halo”

  3. 3.

1 field placed on the Orphan stream (Orphan1), with PROGRAMNAME “stream_disk”

Besides these 26 dedicated stream fields, Sgr stream targets were added to 8
dedicated halo fields (032-62, 037-43, 060-72, 066-79, 120-85, 137-71, 173-61,
179-57), and Orphan stream targets were added to the dedicated halo field
339-44. This means that our Halo Program includes a total of 27 fields
targeting Sgr stream targets, 6 fields targeting JHelum stream targets, and 2
fields targeting Orphan stream targets. Throughout this subsection we are
going to explain how we selected targets from these 3 streams in all these
fields.

Sagittarius Stream Selection: The original dedicated stream field SGRT-2
selected targets from the Sgr stream based on W+D dwarf/giant classification,
and the location of the stars in a $([J-K_{\rm s}]_{0},H)$ CMD (see Z17, for
more details). In the new APOGEE-2S Halo Program, we included Sgr stream
targets in 18 new dedicated stream fields, and 8 new halo dedicated halo
fields, by using the candidate stars presented in Hayes et al. (2018a) as our
parent sample.

To describe the regions observed in this stream, we use the heliocentric Sgr
spherical coordinate system presented in Majewski et al. (2003). In this
system, the equator is defined by the Sgr debris midplane and corresponds to a
pole with Galactic coordinates $(\ell,b)=(273.8,-13.5)$. Then, Sgr latitudes,
$|B_{\odot}|$, are defined as the angular distance to the Sgr debris equator
as viewed from the Sun and Sgr longitudes, $\Lambda$, are defined to increase
in the direction of trailing Sgr debris, with $\Lambda$=0 defined as the
longitude of Sgr center from the King profile fitting results of (Majewski et
al., 2003).

Hayes et al. (2018a) identified candidate Sgr stream red giants in the
magnitude range of $10<H<13.5$ lying at Sgr stream latitudes of
$|B_{\odot}|\lesssim$ 20∘ along $\sim$90∘ of the trailing arm of the Sgr
stream. Because the Sgr stream is kinematically colder than the rest of the
local halo, these candidates could be selected confidently based on their
proper motions, particularly in having small, halo-like proper motions that
are oriented in the direction of motion of the Sgr stream (see Hayes et al.,
2018a). The locations for the 18 new stream dedicated Sgr tidal fields (called
Sgr_tidal1 to Sgr_tidal3, and sgr_tidal4 to sgr_tidal18) were selected to
maximize the number of Sgr stream candidates from this sample and the spatial
coverage along the stream. The 8 new dedicated halo fields also included Sgr
stream candidates from the Sgr sample, but the field location was chosen to
maximize halo targets (see Subsubsection 4.3.1) over stream targets. As a
result of these changes, the APOGEE-2 coverage of the Sgr stream goes more or
less homogeneously from $\Lambda$ = 35∘ to $\Lambda$ = 110∘ at Sgr stream
latitudes of $|B_{\odot}|\lesssim$ 10∘ ($\ell$ from 10∘ to 175∘ and $b$ from
-48∘ to 82∘).

Jhelum Stellar Stream : Six stream fields were designed to target the Jhelum
stream (Bonaca et al., 2019; Shipp et al., 2018), with FIELD of “JHelum1”
through “JHelum6”. The fields were selected by tracing the stream using Gaia
DR2 photometry and astrometry. Candidates were selected as high-probability
members of the stream based on their proximity (in sky position) to the stream
track defined by Bonaca et al. (2019), and by modeling the (solar motion
corrected) proper motion distribution along the stream.

In detail, following the method used in Price-Whelan & Bonaca (2018), we
construct a mixture model for the full proper motion distribution in this part
of the sky. A Gaussian mixture model (GMM) representation of the “background”
proper motion distribution was first constructed by fitting a GMM to the
proper motion distribution of stars in a sky track offset by two degrees north
and south (in a Jhelum stream-aligned coordinate system; Bonaca et al. 2019).
At locations along the Jhelum stream track, we then fit a mixture model
containing the GMM background model as one component, and a single Gaussian
with varied mean and variance as the “stream” component. We also fit for the
mixture weight, which defines the relative contribution of the stream and
background components to the total proper motion distribution.

This model is then used to assign membership probabilities to stars in the
vicinity of the Jhelum stream. Stars were selected with $>50\%$ membership
probability that also lie within 0.25 mag of the red giant branch for a a
metal-poor ($[{\rm Fe}/{\rm H}]=-2$) isochrone (from the MIST stellar
isochrone library; Dotter 2016; Choi et al. 2016). By this means, a total of
seven candidate stars from the Jhelum stream were selected. The dedicated
publication on the Jhelum stream provides some additional details Sheffield et
al. (2021).

Orphan Stellar Stream: Orphan stream (Belokurov et al., 2006; Koposov et al.,
2019) targets were included in the halo field 339-44 and the stream field
Orphan1. To select candidate Orphan stream members, we use the sample of RR
Lyrae-type Orphan stream stars from Koposov et al. (2019) to fit polynomial
trends in sky position and the two proper motion components (all in the Orphan
stream coordinate system defined in Koposov et al. 2019). We then select all
sources with Gaia DR2 astrometry and 2MASS photometry in a 70∘ by 10∘ region
around the extension of the Orphan stream into the Southern Hemisphere. We use
the polynomial tracks of the stream combined with a color-magnitude selection
using a metal-poor ($[{\rm Fe}/{\rm H}]=-2$) isochrone (from the MIST stellar
isochrone library; Dotter 2016; Choi et al. 2016) to select candidate red
giant branch star members of the stream. A dedicated publication on the Orphan
stream will provide additional details (K. Hawkins et al. in prep.).

All stars targeted as stellar stream candidates have bit 18 set in
APOGEE2_TARGET1. The remaining targets in each field were selected following
the halo targeting strategy discussed in Subsubsection 4.3.1.

###  4.4 Dwarf Spheroidals: Fornax

Because of improvements in survey efficiency and the allocation of extra
nights to APOGEE-2S it was possible to expand the coverage of the survey and
add an additional dwarf galaxy to APOGEE’s sample, the Fornax dSph galaxy . As
for all of the other dSphs in APOGEE-2S, Fornax is planned to be observed with
a single cohort of targets for 24 visits. Stars for this field were selected
using a combination of spectroscopic, photometric, and proper motion
information that we now describe.

At highest priority, we targeted four of the five confirmed Fornax globular
clusters (Hodge, 1961), three of which were targeted as integrated light
observations (Fornax 3, 4, and 5), while for the fourth cluster (Fornax 2) we
specifically targeted the brightest star. These integrated light observations
complement programs in APOGEE-1 for M 31 globular clusters (Sakari et al.,
2016, Z13) and in APOGEE-2N for M 33 clusters (a description is given in R.
Beaton et al. submitted; AAS29028).

At second priority we targeted individual Fornax member stars identified by
prior radial velocity and chemical abundance analyses using VLT$+$FLAMES from
Letarte et al. (2010) and Lemasle et al. (2014). Additional radial velocity
members from the wide-area survey with Magellan$+$M2FS by Walker et al. (2009)
were added at third priority.

Because many spectroscopic studies have small footprints compared to the
APOGEE-2S FOV, additional candidate members were selected by combining ground-
based photometry with Gaia DR2 proper motions. The photometry came from two
sources: (i) optical CFHT photometry from Muñoz et al. (2018) (highest
priority) and (ii) NIR photometry from 2MASS (Skrutskie et al., 2006). Lastly,
we included photometric candidates from the NIR study of Gullieuszik et al.
(2007). In all categories, stars below the tip of the red giant branch (i.e.,
with magnitudes $14.7\,<H<15.2$) were selected ahead of stars with asymptotic
giant branch (AGB) like magnitudes above the tip of the red giant branch
(i.e., $H<14.7$).

###  4.5 Magellanic Clouds

Targeting of the Magellanic System — the Large and Small Magellanic Clouds
(LMC, SMC) and the substructure in their vicinity — formed a major component
of the APOGEE-2S program; a summary is given in Z17 with additional details
and the first results of the program given in Nidever et al. (2020). For
reference, the Magellanic Clouds program pulled targets from a variety of
targeting classes to cover a wide range of luminous stellar evolutionary
states, while also building a sample of red giants, which could be reliably
analyzed by APOGEE and compared to Milky Way red giant samples. targeting
classes for general LMC and SMC targeting are as follows, in order of
priority:

  1. 1.

Supergiants following Neugent et al. (2012) and Bonanos et al. (2009) (limited
to $\leq 20$ per plate),

  2. 2.

Hot main-sequence stars (limited to $\leq 20$ per plate),

  3. 3.

Olsen et al. (2011) retrograde stars (limited to $\leq 20$ per plate),

  4. 4.

Post-AGB stars from Kamath et al. (2014, 2015) (limited to $\leq 10$ per
plate),

  5. 5.

RGB stars with high resolution public spectroscopy (limited to $\leq 10$ per
plate),

  6. 6.

AGB Carbon-rich stars following Nikolaev & Weinberg (2000) (limited to $\leq
20$ per plate),

  7. 7.

AGB Oxygen-rich stars (limited to $\leq 20$ per plate),

  8. 8.

RGB stars ($\geq$130 per plate).

All designs belonging to Magellanic Cloud fields in the Main Survey have
PROGRAMNAME tag value of “magclouds.”

The Magellanic Clouds Program was augmented in three ways: (1) expanded LMC
and SMC spatial coverage, (2) a optical cross-calibration field, and (3) the
inclusion of a Contributed Program in the Main Survey.

Expanded Spatial Coverage: The COVID-19 pandemic closed operations of
APOGEE-2S from March 2020 to October 2020 and after reopening, the APOGEE-2S
observations spanned an ideal time of the year to focus on the Magellanic
Clouds. A total of 23 new fields were added, placing five 12-visit fields in
the SMC (named SMC$8-12$) and the remaining 18, 9-visit fields placed
throughout the LMC (named LMC$18-35$). This increases the SMC coverage by 70%
and the LMC coverage by 106%. The target selection for these fields are
identical to that

Optical Calibration: The APOGEE-2S Magellanic Cloud program is one of the
largest spectroscopic surveys of the Magellanic System, but there was very
little overlap with prior studies in the optical to which the APOGEE
measurements could be directly compared. To rectify this, we added an APOGEE
field that overlaps with the study of Van der Swaelmen et al. (2013) that
measured stellar parameters and elemental abundances from optical
spectroscopy. While the APOGEE-2S targeting primarily focused on the most
luminous stars in the LMC, Van der Swaelmen et al. observed stars lower on the
giant branch. The purpose of this field is to characterize any differences
between the APOGEE-2 and Van der Swaelmen et al. (2013)

This field is named ‘LMC_VdS’ with a field center at $(\ell,b)=(283,-34)$ and
was observed using a single cohort in a 24-visit design. Using a plate radius
of 1.0∘, 67 targets from Van der Swaelmen et al. (2013) were prioritised to
$H=14.5$ mag, with three stars rejected due to fiber collisions. The targets
from Van der Swaelmen et al. (2013) will have targeting bit 22 set in
APOGEE2_TARGET1 because they are confirmed members. The remaining fibers in
this field were selected following the LMC target selection . The
corresponding depth for both of these targeting schemas is $H$=14.5 and this
is fainter than the magnitude limit needed to reach our nominal $S/N$=100 goal
in a 24-visit field (see Table 2).

LMC Substructure: A Contributed Program (see Subsection 5.16) targeted the LMC
substructure and these observations were coordinated with the Magellanic
Clouds Working Group. As part of the COVID-19 extension, these were folded
into Main Survey and each plate was allocated additional visits to reach the
survey $S/N$ goal at 9-visits. No changes were made to the targeting bits or
PROGRAMNAME to reflect this change. For details on this program see Section 5
for the general implementation of Contributed Programs and Subsection 5.16
specifically.

###  4.6 Open Clusters

Open Clusters are important tools to study the chemical patterns and evolution
of the disk and targeting such objects has been a major component of APOGEE-1
and APOGEE-2. In particular, the Open Cluster Chemical Abundance and Mapping
(OCCAM) Survey has worked to ensure that as many open clusters as possible are
included in the APOGEE footprint (e.g., Frinchaboy et al., 2013; Donor et al.,
2018, 2020). In DR16, Donor et al. (2020) found 128 clusters had some
observations with 71 clusters having sufficiently many members to be used to
study chemical gradients in the disk.

Targeting for the Open Clusters proceeds in a series of steps that are
explained in detail in the OCCAM papers (Frinchaboy et al., 2013; Donor et
al., 2018, 2020) as well as Z13 and Z17. First the cluster mean proper motion
is determined using a kernel convolution method. Stars closer to the cluster
average proper motion value are given higher priority and, where available,
spectroscopic and/or kinematic member stars from previous studies are
targeted. Finally, photometry is used to remove clear non-members from the
color-magnitude diagram. Stars selected as potential open cluster members have
the targeting bit 9 in APOGEE2_TARGET1 set.

Additions to the Open Cluster Sample: The goal in supplementing the Open
Cluster sample was specifically to target distant clusters in both the inner-
and outer- Galaxy to improve measurements of the Galactic abundance gradient
(e.g., Frinchaboy et al., 2013; Donor et al., 2018, 2020). Additionally,
clusters were included to help expand our cluster-based calibration efforts
for both the metal-rich and metal-poor extremes (see e.g., Holtzman et al.,
2018). We added six open clusters amounting 20 visits; these clusters are
Berkeley 75, Berkeley 81, NGC 5999, NGC 6583, NGC 6603, and Tombaugh 2.

Main Sequence Calibrators in M 67: The COVID-19 extension opened up some time
during which the open cluster M 67 was observable. APOGEE-2N designed a field
dedicated to observing down the main sequence of M 67 to build a calibration
sample of M dwarfs (see R. Beaton et al. submitted; AAS29028). However, this
36-visit field could not be completed in the COVID19-modified schedule for
APOGEE-2N Because this important calibration field could not be finished in
APOGEE-2N, and time was available with the COVID-19 extension to APOGEE-2S,
the decision was made to re-design this northern field for southern
observation. While this required changing the targets slightly from the
original design, which is described in R. Beaton et al. (submitted; AAS29028)
due to the difference in plate scale between APOGEE-2N and -2S, the target
selection and design follows the description given there .

###  4.7 K2

APOGEE-2N initiated a large-scale campaign to obtain complementary APOGEE
spectra in the K2 campaigns (described in R. Beaton et al. submitted;
AAS29028). The full program was difficult to accommodate fully in APOGEE-2N
and, with the goal of providing the most complete possible scientific dataset
leveraging K2, we transferred 87 1-visit fields from six different K2
campaigns to the APOGEE-2S field plan. At the time of this decision,
comparisons of the relative performance of the ASPCAP pipeline on targets
observed both with APOGEE-2N and APOGEE-2S suggested that splitting the
program would not cause bias in the K2 scientific results (a full discussion
is given in Jönsson et al., 2020). The fields transferred to APOGEE-2S plan
correspond to Campaigns C8, C10, C14, C15, C17, and half of the fields from
C6. We note that the differences between the field-of-view and plate-scale
mean that the plates for APOGEE-2N and APOGEE-2S are not identical .

We briefly summarize the targeting here, noting that a more involved
discussion is given in R. Beaton et al. (submitted; AAS29028). The targeting
made use of knowing what stars were already targeted by HERMES (Sheinis et
al., 2015; Sheinis, 2016) using the setup used in the GALAH survey (Wittenmyer
et al., 2018; Sharma et al., 2019). . From all stars with K2 data, we first
remove stars with existing APOGEE observations (APOGEE-1 or APOGEE-2). From
here the targets were prioritized as follows:

  1. 1.

known planet hosts (APOGEE2_TARGET2 bit 11),

  2. 2.

stars with a confirmed oscillation or granulation signal (APOGEE2_TARGET1 bit
30),

  3. 3.

red giants targeted by the K2 Galactic Archaeology Program (GAP; Stello et
al., 2017, APOGEE2_TARGET2 bit 0) and not observed with HERMES,

  4. 4.

GAP targets observed by HERMES (see Wittenmyer et al., 2018; Sharma et al.,
2019, APOGEE2_TARGET2 bit 17),

  5. 5.

M-dwarfs in the unbiased sample from the APOGEE-2N ancillary program
(APOGEE2_TARGET3 bit 28).

  6. 6.

stars meeting the criteria for the “main red star” sample (APOGEE2_TARGET1 bit
14).

While the target selection was prioritised following this scheme, an
individual target could be present in multiple target categories. Field
centers were optimized to reach the most targets weighted by priority.

All K2 observations will have the PROGRAMNAME ‘k2_btx’ and field names like
‘K2_C#_$lll$$\pm$$bb$_btx’, where C# indicates the K2 campaign and
$lll$$\pm$$bb$ indicate the Galactic coordinates for the field center. All
targets in K2 fields have APOGEE2_TARGET3 bit 6 set, as well as specific flags
for the sub-targeting category as detailed above.

###  4.8 Globular Clusters

The original targeting of globular clusters in APOGEE-2S is described
generally in Z17 . While there were no changes to the globular cluster program
during the main survey of APOGEE-2S, the COVID-19 extension allowed for the
expansion of observations on four globular clusters: NGC 1851, NGC 2808, M 79,
and $\omega$ Centauri ($\omega$Cen), and the design of a new globular cluster
field, NGC 2298, in total summing to 30 new visits, with six per cluster. For
NGC 1851, NGC 2808, and M 79, new designs were created to target known members
from Sollima (2020) that are brighter than $H=12.8$ mag. A new field (FIELD of
N2298) was made to target the globular cluster NGC 2298, and similarly,
targets for this cluster were taken from Sollima (2020) with the same
magnitude limit. The member stars from these five clusters are flagged with
APOGEE2_TARGET2 bit 10.

####  4.8.1 Omega Centauri

In the original targeting of $\omega$Cen, the acquisition camera, with its
5.5′ occlusion radius, was placed near the center of the cluster, blocking the
core of the cluster from observation. This notably leaves a significant gap in
the APOGEE-2 spatial coverage of $\omega$Cen. In addition, since the design of
the original $\omega$Cen field, Ibata et al. (2019) used Gaia DR2 (Gaia
Collaboration et al., 2018) observations to reveal a thin tidal stream coming
off of $\omega$Cen. This too motivated observing more of $\omega$Cen.

With some of the time made available in the COVID-19 extension of APOGEE-2S,
it was decided to allocate some of the available time to better cover
$\omega$Cen and fill in this gap (by moving the field center, and therefore
the location of the acquisition camera to a different position on the sky),
albeit not to the same depth as originally designed. Instead of the 24 visits
assigned to the original $\omega$Cen field — which were split into two sets of
long cohorts that received 12 visits each, with short and medium cohorts
receiving 3 and 6 visits, respectively — the new $\omega$Cen field (FIELD
named ‘Omegacen2’) was designed to have 6 visits, which were split into two
sets of medium cohorts that received 3 visits each, with short cohorts
receiving 1 visit each. The minimum magnitude for this field was lowered to
$H=12.8$ for special targets, instead of the nominal $H=12.2$ for a 3-visit
faint cohort, $S/N$ $\sim 70$ was deemed sufficient.

The target selection for this new field, first, prioritized observing stars
with high resolution optical spectra from Johnson et al. (2020), followed by
proper motion identified $\omega$Cen members from van Leeuwen et al. (2000),
and finally $\omega$Cen stream candidates were prioritized last, however,
because of their low sky density and distance from the center of the cluster
all of the identified candidates were included. Stream candidate giants were
identified by consolidating stream candidates from Anguiano et al. (2015),
Fernández-Trincado et al. (2015), and stars observed by the STREGA survey
outside of $\omega$Cen’s tidal radius and along $\omega$Cen’s sequence in the
$g_{\rm 0}$ vs $(g-i)_{\rm 0}$ color-magnitude diagram (STRucture and
Evolution of the GAlaxy with the VST; Marconi et al., 2014). These latter
stars were also required to have Gaia DR2 proper motions within 1.6 mas yr-1
of the bulk proper motion of $\omega$Cen
$(\mu_{\alpha}\cos(\delta),\mu_{\delta})=(3.24,-6.73)$ from Baumgardt et al.
(2019). $\omega$Cen members with optical spectra or identified from their
proper motions have been flagged with APOGEE2_TARGET2 bit 10 and the
$\omega$Cen stream candidates have been flagged with APOGEE2_TARGET1 bit 19.

=1.2in  Program TAC Program Total Total Stars Average Depth Subsection Contact
Name Name Visits Stars Observed SNR $H$ [mag] Star Forming Region G305 CNTAC
borissova_17a 8 1000 250 71.4 12.2 5.1 J. Borissova Cool dwarfs in K2 fields
CIS teske_17a 43 10750 7250 134.9 11.0 5.2 J. Van Saders TeskeVanSaders_17b
Upper Scorpius cluster CIS weinberg_17a 98 21750 5106 143.0 11.7 5.3 A.
Weinberger weinberg2_17a Inner bulge and disk CNTAC zoccali_17a 17 3750 1750
91.4 11.7 5.4 M. Zoccali zoccali_18b Metal-poor stars in the inner Galaxy CIS
schlaufman_17a 18 4500 3000 97.1 11.0 5.5 K. Schlaufman The structure of the
Ancient MW CIS kollmeier_17a 43 10750 10250 47.5 11.0 5.6 J. Kollmeier Low
metallicity Cepheids CIS beaton_18a 18 1500 1500 195.1 12.2 5.7 R. Beaton
TESS/APOGEE survey CIS TeskeVanSaders_18a 154 38500 26500 168.1 11.0 5.8 J.
Teske, J. Van Saders and R. Beaton Carina Star Forming Complexes CNTAC
RomanLopes_18a 5 750 750 175.3 12.2 5.9 A. Roman-Lopes Corona Australis
protocluster CNTAC stutz_18a 4 500 500 135.9 11.7 5.10 A. Stutz Bulge globular
clusters CNTAC geisler_18a, geisler_19a 57 5561 3217 106.9 12.8 5.11 D.
Geisler geisler_18b, geisler_20a Massive Stars in the SMC and LMC CIS
Drout_18b 22 5250 3500 130.5 11.7 5.12 M. Drout Rossete Molecular Clouds CNTAC
stutz_18b 4 370 370 56.5 12.2 5.13 A. Stutz Carina Protocluster CNTAC
stutz_19a 6 750 500 66.3 11.7 5.14 A. Stutz OB Stars CIS kollmeier_19b 42 2750
500 160.6 12.8 5.15 J. Kollmeier A. Tkachenko LMC substructures CNTAC
monachesi_19b 21 1500 1250 55.7 12.4 5.16 A. Monachesi Orion Nebula Cluster
CNTAC stutz_20a 7 1000 0 0.0 11.7 5.17 A. Stutz Carina Nebula Cluster CNTAC
medina_20a 7 750 0 0.0 12.2 5.18 N. Medina NGC6362 cluster CNTAC fernandez_20a
2 500 0 0.0 11.0 5.19 J. Fernández-Trincado

Table 6: Summary of APOGEE-2S Contributed Programs Figure 5:  Sky distribution
of APOGEE fields highlighting in color those from APOGEE-2S Contributed
Programs. The color-coding indicates the number of visits observed per field;
grey symbols represent all other fields for context. The background image is
the dust map from Schlegel et al. (1998). The inlays indicate the dense
targeting in the Galactic center (left) and the Upper Scorpius star forming
region (right), where we have overlaid circles to indicate the unique plate
centers. These fields represent $\sim$23% of the APOGEE-2S observing program.

##  5 Contributed Programs

Roughly 23% of the observing time of the APOGEE-S spectrograph was used for
programs that are independent from the main survey observing plan. Such
programs are allocated either through the Chilean Time Allocation Committee
(CNTAC) or by the Observatories of the Carnegie Institution of Science TAC
(CIS) and are both scheduled “classically” for specific night(s).

The targeting scheme of each of these programs is entirely decided by its
Principal Investigator (PI) . The APOGEE-2S team only applies some basic
restrictions to the target lists to ensure that the plates can be plugged and
are observable during the night(s) assigned to the program.

The PI(s) of each project may choose whether the observed data would be
included in the SDSS Data Releases, known as “Contributed Programs,” or if the
data would remain external to the survey, known as “External Programs.” For
Contributed Programs, while the data are collected according to the
specifications of the TAC and the PIs, the spectroscopic data, itself, is
treated identically to that of the main survey. More specifically, the data
are processed with the existing APOGEE data processing pipelines, are made
into the same data products, and are made available to the collaboration in
the same way. all of the PIs chose for their observations to be executed as
“Contributed Programs.”

Table 6 provides the main observational aspects of the 19 Contributed
programs, including the nominal depth calculated based on the maximum visits
received per star. Figure 5 provides the sky distribution of Contributed
Programs. Each field is color-coded by the planned field depth (recall, 1
visit is roughly 1 hour of on-sky integration) to provide a sense of the
targeting strategy. The two insets in Figure 5 zoom in on particularly densely
targeted regions of the sky.

Field naming conventions from the main survey were adopted for these programs,
but the fields from Contributed Programs have “-C” and “-O”appended to their
name, for CNTAC and CIS programs, respectively. Fields from the TESS CIS
program specifically (TeskeVanSaders_18a; Subsection 5.8) have a further
“_TESS” appended at the end of their names. Targets included in these
observations have bit 24 and 25 set in APOGEE2_TARGET2 flag for CIS and CNTAC
programs, respectively.

Because the targets are not selected following standard APOGEE-2 procedures,
the programs are not identifiable using targeting bitmasks. Each program is
identified by its “program name” in the PROGRAMNAME tag (given in Table 6).
The program name is typically constructed as the last name of the PI followed
by the first semester it was allocated; because of the classical-style
implementation of these programs, many programs spanned multiple observing
semesters.

###  5.1 Star Forming Region G305

Contact Information: J. Borissova (Universidad de Valparaíso).
Located within the Scutum-Crux arm of the Milky Way ($\ell$=305.4∘, $b$=0.1∘),
with projected diameter of $30\,\rm{pc}$, the G305 star-forming complex is
both relatively nearby ($\sim 3.8\,\rm{kpc}$) and one of the most luminous HII
regions in the Milky Way (Urquhart et al., 2014). The region contains several
distinct sites and epochs of star formation, which permits the study of
massive star formation, massive star evolution, and the impact of these
processes on the surrounding environment. The morphology of the region and
positions of star formation indicators suggests that interaction between the
evolved massive stars and remnant, natal molecular material is taking place,
resulting in ongoing star formation activity. Thus, G305 region is a perfect
test-bed object, both for intermediate and high mass star formation.

The scientific aim of this project is to analyze the kinematics and
metallicity of stars in G305 region. The project will combine the homogeneous,
high precision photometry and variability from VVV (Minniti et al., 2010),
astrometry from Gaia DR2 (Gaia Collaboration et al., 2018), and radial
velocity and metallicity measurements from APOGEE-2. With this data, the
project will: (1) improve the census of both massive and intermediate-mass
stars in the area; (2) measure the kinematics of different stellar groups
(YSOs, OB, WR stars) and confirm/reject memberships of the stars to the
clusters projected in the region; (3) outline the potential spatial
substructures and measure the star formation histories to probe models of
triggered versus passive star formation; and (4) calculate the present-day
star formation rate in the area using the method of direct counts of YSOs as
compared with other star forming regions in the Milky Way. Some results from
these observations are published in Borissova et al. (2019). Observations from
this project have PROGRAMNAME borissova_17a.

###  5.2 Cool Dwarfs in K2 fields

Contact Information: J. van Saders (University of Hawaii) and J. Teske
(Carnegie Institution For Science, Earth and Planets Laboratory).
The goal of this program is to collect APOGEE-2S spectra of bright, cool dwarf
stars that are being monitored by the K2 ecliptic survey (Howell et al.,
2014), including stars known to host planet candidates through the analysis of
their light curves. These data will be used to measure stellar parameters and
chemical abundances for low-mass stars in the K2 fields. The scientific goals
are: (1) to determine rotation-based ages, (2) to constrain the age-
metallicity relation, and (3) look for a correlation between exoplanet
architecture and host-star composition. In particular, M dwarf spectra are of
high value in the development of an analysis method for extracting reliable,
detailed abundances of $T_{\rm eff}<4000\,K$ stars. This project aims at
observing 34 fields from six K2 Campaigns: C1, C2, C3, C4, C7, and C8.
Observations from this project have PROGRAMNAME teske_17a, or
TeskeVanSaders_17b.

###  5.3 Upper Scorpius Cluster

Contact Information: A. Weinberger (Carnegie Institution For Science, Earth
and Planets Laboratory).
This program aims to survey the young ($\sim 10\,{\rm Myr}$ old), Upper
Scorpius cluster to measure the properties of a large, homogeneously targeted
population of young stars. We primarily target cluster members that were
included in K2 and for each star we intend to measure $T_{\rm eff}$,
$\log{g}$, and radial velocity.

The targets for this project come from three separate sources:

  1. 1.

we included all targets fainter than $H$=7.5 from three K2 guest observer
programs during Campaign 2999https://keplerscience.arc.nasa.gov/k2-approved-
programs.html#campaign-2 that focused on Upper Sco. These are Program 2052 (PI
Covey: K2 Monitoring of Confirmed Members of Upper Sco and Rho Oph), Program
2057 (PI Hillenbrand: A K2 Study of Young Stars in Upper Scorpius), and
Program 2063 (PI Kraus: Planets Around Likely Young Stars in Upper Sco and Rho
Oph). These account for 1309 targets.

  2. 2.

we included all additional (16) Upper Sco targets that were part of a ground-
based parallax survey (Donaldson et al., 2017); these were all fainter than
$H$=7.5.

  3. 3.

we included additional Upper Sco targets that were part of the Spitzer surveys
of Upper Sco looking for circumstellar disks and were fainter than $H$=7.5 (78
targets) (Carpenter et al., 2005, 2006a, 2006b, 2009).

Thus there were 1403 sources included in our master target list. When
constructing input lists for the APOGEE-S targeting software, we allowed
targets in the vignetted (0.8 - 0.95∘radii) region of the field.

Observations from this project have PROGRAMNAME of weinberg_17a, or
weinberg2_17a.

###  5.4 Inner Bulge and Disk

Contact Information: M. Zoccali (Pontificia Universidad Católica-Instrituto
Milenio de Astrofísica).
The region called the “Nuclear Bulge” stands out from the main bulge due to
several observed properties: (1) a much higher stellar density, with a clear
break (Launhardt et al., 2002), (2) the presence of a dense interstellar
medium (the Central MolecularZone Morris & Serabyn, 1996), (3) ongoing star
formation in scattered dense clouds, and (4) a stellar Nuclear disk. The the
presence of a stellar nuclear bulge has been confirmed with APOGEE data
(Schönrich et al., 2015), however many open questions remain regarding its
formation and relationship to other bulge structures.

To sample this region with APOGEE, five fields were designed at the following
Galactic coordinates ($\ell$,b): (-4,0), (-2,0), (0,0), (2,0), and (4,0),
respectively. Targets were selected from imaging from VISTA Variables in the
Via Lactea (VVV; Minniti et al., 2010), but with PSF photometry derived by
Rodrigo Contreras (priv. communication) with the method described in Contreras
Ramos et al. (2017). Because the interstellar extinction towards the nuclear
bulge is extremely large ($A_{\rm V}>20$) the observed red giant branch has a
very broad distribution in color. To define a target box in color-magnitude
space that creates a uniform sampling of the stellar populations at different
metallicities, an initial selection of stars with 2.4$<E(J-K_{\rm s})<$3 was
imposed, using the reddening maps from Gonzalez et al. (2018). In the central
field, this color-cut excluded stars within $\pm$0.3∘of the Galactic plane,
but permitted the CMD box with $H<11.8$ to span the full RGB color-range for
the other four fields without imposing a significant color bias. If not
designed-out of the sample selection, a color bias could introduce a
metallicity bias; we note that the color-range is different for each of the
fields.

The APOGEE observations will be used to derive the metallicity distribution
function for these regions and it will be used to test if the Nuclear disk is
the central extension of the inner bulge, or if is a distinct stellar
component. Furthermore, an empirical metallicity distribution function will
break the degeneracy in the derivation of the star formation history of this
region, by comparing the available deep NIR CMDs (Nogueras-Lara et al., 2019)
with synthetic color magnitude diagrams. Observations from this project have
PROGRAMNAME of zoccali_17a, or zoccali_18b.

###  5.5 Metal-poor Stars in the Inner Galaxy

Contact Information: K. Schlaufman (Johns Hopkins University).
The oldest stars in the Milky Way are very metal-poor (i.e.,
$[\mathrm{Fe/H}]<-2.0$) and may be found in the inner Galaxy (e.g., Tumlinson,
2010). However, extreme reddening, extinction, and crowding in the inner
Galactic bulge have made finding metal-poor stars in this region impossible
with traditional techniques. Schlaufman & Casey (2014) published an efficient
metal-poor star selection that uses only infrared photometry, thereby
overcoming the previous barriers to the identification of metal-poor stars in
the inner Galaxy. The targets in this program were selected following the
pure-infrared metal-poor star selection from Schlaufman & Casey (2014) using
the photometry from the _Spitzer_ /IRAC Galactic Legacy Infrared Mid-Plane
Survey Extraordinaire (GLIMPSE; Benjamin et al., 2003; Churchwell et al.,
2009) and applying dereddening from high-resolution bulge-specific maps from
Gonzalez et al. (2011, 2012) assuming the Nishiyama et al. (2009) extinction
law. An restriction of $H\leq 12.5$ was applied. Observations from these
project have PROGRAMNAME schlaufman_17a.

###  5.6 The Structure of the Ancient Milky Way

Contact Information: J. A. Kollmeier (Observatories of the Carnegie
Institution for Science) and R. Poleski (Warsaw).
RR Lyrae (RRL) stars provide a unique view into the ancient interior of the
Milky Way. In addition to being old stars, the pulsations of RRL stars have
long allowed accurate distance estimates. The distance estimates can be
combined with proper motions (Poleski et al., 2013, 2015) and radial
velocities (from APOGEE) to obtain full six dimensional phase-space
information for these stars. The goal of this project is to target a large
sample of RRL stars identified by the Optical Gravitational Lensing Experiment
(OGLE) survey in Galactic bulge (Udalski et al., 1992) for radial velocity
measurement with APOGEE-2S. In particular, this program was designed to
penetrate the dust of the Milky Way to see the 3-D structure of it’s old
central component – to compare with theories of formation of the bulge.
Targets were selected by applying the OGLE-defined periods to the $H$-band
period luminosity relationship to predict the mean $H$-band magnitudes. All
the RRL stars from this program have bit 24 set in APOGEE2_TARGET1.
Observations from this project have PROGRAMNAME kollmeier_17a.

The original main survey plan also included RRL observations (Z17), designed
by the same Contributed Program PIs. Thus, for the purposes of analysis and
selection, this Contributed Program and the main survey program are identical.

###  5.7 Low Metallicity Cepheids

Contact Information: R. Beaton (Princeton University and the Observatories of
the Carnegie Institution for Science).
This Contributed Program has collected single-phase APOGEE-2S spectroscopy for
the brightest and most well-studied Cepheids in the LMC. The APOGEE
measurements can be combined with literature multi-band optical to mid-
infrared photometry to study trends metallicitiy and the absolute magnitude
dispersion of these stars against the mean Leavitt Law. The Cepheid sample was
largely selected from the OGLE-III catalog of Cepheid variables in the LMC
(Soszynski et al., 2008), but was supplemented with key calibrators used for
the Cepheid-based extragalactic distance scale (Persson et al., 2004;
Scowcroft et al., 2011, 2016). To obtain high $S/N$ data, these stars are
observed in two to three sequential visits and, thus, pipeline combined data
is all at the same phase of the photometric light curve. As a result, the
targets go to an $H$ depth of a 3-visit field (using the mean magnitudes;
Table 2). Additional fainter Cepheids were also targeted as part of this
program, with the caveat that they may not reach $S/N$ of 100 per pixel. We
caution that sometimes the observations were significantly distributed in
time. The remaining fibers were back-filled with targets from the “TESS/APOGEE
Survey” (Subsection 5.8) but only going to a depth of $H\sim 11$ mag.
Observations from this project have PROGRAMNAME beaton_18a.

###  5.8 TESS/APOGEE Survey

Contact Information: J. Teske (Carnegie Institution For Science, Earth and
Planets Laboratory), J. van Saders (University of Hawaii), and R. Beaton
(Princeton University and the Observatories of the Carnegie Institution for
Science).
This program intended to collect APOGEE-2S spectra of bright ($7<H<11\,{\rm
mag}$) stars that fall within the $450\,{\rm deg^{2}}$ of the Southern
Ecliptic Pole, a region of the sky where NASA’s TESS satellite (Ricker et al.,
2015) has had continuous 1 year coverage, and with TESS extended mission will
have an additional year of coverage. These APOGEE-2S data will be used to
measure stellar parameters and chemical abundances. When combined with the
precise TESS photometric light curves, these data will enable investigations
of open questions about exoplanets, stellar astrophysics, and distance ladder
calibration. Target selection was made via simple 2MASS color and magnitude
cuts: $7<H<11$ and $J-K>0.3$. As plates were drilled, target priorities were
defined as: (1) subgiants where asteroseismic detections are expected, (2)
asteroseismic dwarfs from the ATL (Schofield et al., 2019), (3) targets likely
to be placed on 2 minutes cadence for planet searches based on the CTL
(Stassun et al., 2018), (4) hot star seismic targets (exceptions to the color
cut), and (5) bright giants. Fields from this program have the word “-O_TESS”
appended at the end of their field name. Observations from this project have
PROGRAMNAME TeskeVanSaders_18a.

###  5.9 Carina Star Forming Complexes

Contact Information: A. Roman-Lopes (Universidad de La Serena).
The Carina star-forming complexes contain some of the most massive star-
forming regions in the Milky Way. It is an ideal laboratory to test theories
of the spatially segregated formation of stars and triggering mechanisms. This
program takes advantage of the large FOVand multiplexing capability of the
APOGEE-S spectrograph to confirm the massive nature of hot star candidates in
the Galactic plane. The fields observed in this project are located in the
vicinity and periphery of regions forming massive stars in the Carina star-
forming complexes. The excellent spectral resolution provided by the APOGEE-2S
instrument, and the high $S/N$ radial velocity measurements enabled us to
obtain spectroscopic information of about $1,750$ candidate massive stars, a
task virtually impossible using single slit NIR spectroscopic facilities.
Further details for this program are provided in Roman-Lopes et al. (2020).
Observations from this project have PROGRAMNAME RomanLopes_18a.

###  5.10 Corona Australis Protocluster

Contact Information: A. Stutz (Universidad de Concepción).
This program aims at measuring the radial velocities of the young stellar
population in the Corona Australis protocluster. The ”Slingshot” mechanism
proposes that young stars gain kinetic energy via gas filament oscillations
(Stutz & Gould, 2016; Boekholt et al., 2017; Stutz, 2018). Ultimately, such
oscillations may “eject” protostars from their dense gas cradles, cutting off
the supply of gas to the new stars. The “Slingshot” scenario proposes that
magnetically driven instabilities in the gas may be responsible for the
oscillations. Whatever the ultimate oscillation mechanism, the APOGEE-2S
Corona Australis RV measurements enable the dynamics of this proto-cluster to
be compared to those of the Orion-A Integral Shaped Filament.

Targets for this program were selected from the _Spitzer_ -based catalog of
Corona Australis members assembled by Peterson et al. (2011). We prioritize
all young stellar objects (Classes 0, I, II, and III) with $H<$ 14, comprising
a high-priority sample of 50 objects that are distributed across two plates to
cover the full stellar population. Observations from this project have
PROGRAMNAME stutz_18a.

###  5.11 CAPOS: the bulge Cluster APOgee Survey

Contact Information: D. Geisler (Universidad de Concepción and Universidad de
La Serena).
The Galactic bulge hosts a large number of globular clusters (e.g., Harris,
2010; Kharchenko et al., 2016). These clusters are powerful cosmological
probes to investigate the formation and chemical evolution of this key
Galactic component (APOGEE studies in individual stars include: Hasselquist et
al., 2020b; Rojas-Arriagada et al., 2020b; Queiroz et al., 2020).
Unfortunately, until recently, we have not been able to unleash the full power
of the bulge globular clusters to help unravel its mysteries due to their high
extinction, which strongly impedes optical observations (e.g., Gran et al.,
2019; Palma et al., 2019). However, extinction effects are minimized by
observing in the NIR, allowing us to fully exploit the bulge GC’s
extraordinary archaeological attributes. The bulge Cluster APOgee Survey
(CAPOS) will observe 20 of the bona-fide bulge globular clusters that were not
included for the APOGEE-2 observations (see Z17; Masseron et al., 2019;
Mészáros et al., 2020b). Combining this Contributed Program with the APOGEE
Main Survey bring the total number of bulge clusters targeted with APOGEE to
28, just over 50% of the known bulge clusters. CAPOS will supply almost 75% of
the observed objects and build a legacy database of the bulge globular cluster
system. This will provide much better and more self-consistent radial
velocities and spectroscopic metallicities than currently available for all
the observed bulge globular clusters. These observations will permit
investigation of many salient details of these systems like their chemistry,
existence and properties of multiple populations, and orbital properties,
among others. Observations from this project have PROGRAMNAME of geisler_18a,
geisler_19a, geisler_19b, or geisler_20a.

###  5.12 Massive Stars in the SMC and LMC

Contact Information: M. Drout (University of Toronto).
Our goal was to conduct a wide and shallow survey of the evolved massive star
populations (e.g. yellow supergiants, red supergiants, and luminous blue
variables) of the Large and Small Magellanic Clouds (LMC and SMC) with
APOGEE-S.

For targeting, we followed a procedure similar to that outlined in Neugent et
al. (2010, 2012), who study the red and yellow supergiants (RSGs and YSGs) of
the LMC and SMC. We first selected all objects with 2MASS $H$ quality flag of
‘AAA’ and magnitude of $H_{\rm 2MASS}$ < 12.2 that lie within 4 deg2 of the
LMC and SMC, respectively. Centers for each galaxy were define as
$(\alpha,\delta)_{\rm LMC}$ = (05:23:34.5, -69:45:22) and
$(\alpha,\delta)_{\rm SMC}$ = (00:52:44.8, -72:49:43).

To separate likely LMC/SMC supergiants from foreground dwarfs in the FOV we
use a combination of Gaia-DR2 (Gaia Collaboration et al., 2018) proper
motions/parallax values and radial velocities/spectroscopic classifications,
when available. We assign probabilities of membership based on Gaia-DR2
kinematics by the procedure described in O’Grady et al. (2020), which is based
on that outlined in Helmi et al. (2018). In brief, we use a curated sample of
highly probable LMC/SMC members to define a distribution in
($\mu_{\alpha},\mu_{\delta},\pi$) followed by LMC/SMC members. Each 2MASS
source described above is then cross-matched with Gaia DR2, and a $\chi^{2}$
value is computed to assess the consistency of its proper motion and parallax
with these distributions. For the purposes of targeting, we designate any star
with a $\chi^{2}<6.25$ (indicating that the star falls within the region that
contains 90% of LMC/SMC members) as having Gaia kinematics that are
“consistent” with LMC/SMC membership. In addition, we cross match all of the
2MASS sources with Simbad Wenger et al. (2000) in May 2018 in order to
retrieve any existing radial velocity measurements for spectroscopic
classifications. For the purposes of targeting we take any source with $v_{\rm
rad}$ greater than 200$\,{\rm km}\,{\rm s}^{-1}\>$and 135$\,{\rm km}\,{\rm
s}^{-1}\>$in the direction of the LMC and SMC, respectively, as having
velocities consistent with membership in the Clouds (Neugent et al., 2010,
2012), while we discard any source with a ‘V’-type classification as a
foreground star.

With this ancillary data in hand, all APOGEE fields were then assigned
targets, moving through an ordered list of priorities until fiber capacity was
reached. The ranked priorities for the LMC were all follows. In the following
definitions, we take the dividing line between ’blue/yellow’ and ‘red’ stars
to be $J-K$ = 0.9 mag. This corresponds to an effective temperature of
$\sim$4800 K and is taken as the rough dividing line between YSGs and RSGs in
(Neugent et al., 2012).

  * •

Star which are listed as a confirmed YSG or RSG in the spectroscopic sample of
Neugent et al. (2012) or as confirmed or candidate Luminous Blue Variables.

  * •

Stars which are consistent with LMC membership based on both Gaia kinematics
and an existing radial velocity, and have H < 11.3 mag.

  * •

Stars which are consistent with LMC membership based on both Gaia kinematics
and an existing radial velocity, and have $H$ < 11.8 mag.

  * •

Stars which are consistent with LMC membership based on Gaia kinematics, have
no existing radial velocity data, and fall within the 2MASS color cuts defined
by Neugent et al. (2012) in order to identify YSGs down to a completeness
limit of $\sim$12$M_{\odot}$, using the Geneva evolutionary models (Maeder &
Meynet, 2001) and ATLAS9 atmosphere models (Kurucz, 1993).

  * •

Stars which are consistent with LMC membership based on Gaia kinematics, have
no existing radial velocity data, and fall within the 2MASS color cuts defined
by Neugent et al. (2012) to identify RSGs with minimal contamination from AGB
stars.

  * •

Other blue/yellow stars with $H$ < 11.6 that are consistent with LMC
membership based on Gaia kinematics, have no existing radial velocity data.

  * •

Other red stars with $H$ < 10.8 that are consistent with LMC membership based
on Gaia kinematics, have no existing radial velocity data.

  * •

Any remaining stars with $H$ < 11.3 that are consistent with LMC membership
based on Gaia kinematics, have no existing radial velocity data.

  * •

Other blue/yellow stars with $H$ < 11.8 or red stars with $H$ < 11.6 that are
consistent with LMC membership based on Gaia kinematics, have no existing
radial velocity data.

  * •

Other blue/yellow stars with $H$ < 11.6 or red stars with $H$ < 12.0 that are
consistent with LMC membership based on Gaia kinematics, have no existing
radial velocity data.

  * •

Stars that are consistent with LMC membership based on Gaia kinematics and
were classified as carbon stars in Simbad (Wenger et al., 2000). Note that
objects with a listed spectral classification of ‘C’ were explicitly excluded
in all previous steps.

Priority listings for the SMC were entirely analogous. Main difference were
than in Step 1 confirmed YSGs were added from Neugent et al. (2010), and in
Steps 4 and 5 the $H$ magnitudes were shifted by 0.4 mag in order to account
for the difference in distance modulus between the LMC and SMC.

In total 16 LMC fields and 5 SMC fields were constructed and observed. Field
centers were chosen to optimize the number of confirmed RSG, YSGs, and LBVs
from the samples outlined in Steps 1 and 2, above, with over 97% being