The APOGEE SDSS-III Radial Velocity Survey of M dwarfs I

The SDSS-III APOGEE Radial Velocity Survey of M dwarfs I: Description of Survey and Science Goals

Abstract

We are carrying out a large ancillary program with the Sloan Digital Sky Survey, SDSS-III, using the fiber-fed multi-object near-infrared APOGEE spectrograph, to obtain high resolution H-band spectra of more than 1200 M dwarfs. These observations will be used to measure spectroscopic rotational velocities, radial velocities, physical stellar parameters, and variability of the target stars. Here, we describe the target selection for this survey, as well as results from the first year of scientific observations based on spectra that will be publicly available in the SDSS-III DR10 data release. As part of this paper we present radial velocities and rotational velocities of over 200 M dwarfs, with a precision of 2 km s and a measurement floor at =4 km s. This survey significantly increases the number of M dwarfs studied for rotational velocities and radial velocity variability (at m s), and will inform and advance the target selection for planned radial velocity and photometric searches for low mass exoplanets around M dwarfs, such as HPF, CARMENES, and TESS. Multiple epochs of radial velocity observations enable us to identify short period binaries, and AO imaging of a subset of stars enables the detection of possible stellar companions at larger separations. The high-resolution APOGEE spectra, covering the entire H band, provide the opportunity to measure physical stellar parameters such as effective temperatures and metallicities for many of these stars. At the culmination of this survey, we will have obtained multi-epoch spectra and radial velocities for over 1400 stars spanning the spectral range M0-L0, providing the largest set of near-infrared M dwarf spectra at high resolution, and more than doubling the number of known spectroscopic v values for M dwarfs. Furthermore, by modeling telluric lines to correct for small instrumental radial velocity shifts, we hope to achieve a relative velocity precision floor of 50 m s for bright M dwarfs. With three or more epochs, this precision is adequate to detect substellar companions, including giant planets with short orbital periods, and flag them for higher-cadence followup. We present preliminary, and promising, results of this telluric modeling technique in this paper.

Subject headings:
stars: M dwarfs, low-mass stars–instrumentation: APOGEE–techniques: radial velocity
42

1. Introduction

M dwarfs are a major stellar constituent of the Galaxy and are increasingly important for exoplanet science and the quest for discovering low mass planets in or near habitable zones (Dressing & Charbonneau, 2013; Kopparapu, 2013). High-resolution spectroscopic observations of M stars are crucial for understanding stellar astrophysics at the bottom of the main sequence and planet statistics across the HR diagram. A large, multi-epoch spectroscopic survey enables us to not only detect low-mass stellar and sub-stellar companions (including giant planets) but also to address a wide range of questions, including the statistics of stellar multiplicity, kinematics, metallicity, and activity. High-resolution spectra in the near infrared (NIR) for a range of M dwarfs will also be critical for modeling of chemical abundances and for probing the physical processes that occur in the complex atmospheres of M dwarfs. The multiplexed Sloan Digital Sky Survey (SDSS-III) APOGEE spectrograph is uniquely suited to provide many hundreds of such spectra, increasing the number of available high-resolution NIR M dwarf spectra by at least an order of magnitude.

Radial velocity (RV) surveys to detect exoplanets have mostly targeted FGK stars over the past two decades, but are beginning to explore the M dwarfs in the solar neighborhood. With temperatures below 4000 K, the spectral energy distributions of M dwarfs peak between 0.9 and 1.8 m (the   bands), where RV measurement techniques are less developed than in the optical. Rodler et al. (2012) derived RV measurements of eight late-M dwarfs as part of a large survey by Deshpande et al. (2012) to monitor RV variability among late-M dwarfs (M5.0 - M9.5) using the NIRSPEC spectrograph (McLean et al., 1998). At a spectral resolution , in the band, they obtained RV precisions between 180 m s and 300 m s. Blake et al. (2010) targeted a magnitude-limited sample of M dwarfs and ultracool dwarfs using NIRSPEC over a period of six years. Employing a forward-modeling technique in the band (Blake et al., 2007) at , they report a RV precision of 50 m s for a bright, slowly rotating M dwarf and 200 m s for slowly rotating, ultracool dwarfs. Bean et al. (2010) used ammonia gas cell as an iodine analog in the NIR on the very high () spectrograph CRIRES (Kaüfl et al., 2004) in the band and achieved an RV precision of 3–5 m s over long timescales.

Though this level of precision is a big step forward, it is restricted to wavelength regions overlapping the ammonia cell and for relatively bright stars. In addition, the process also requires very high spectral resolution, which is not generally available. New infrared instruments like Habitable Zone Planet Finder (Mahadevan et al., 2012) and CARMENES (Quirrenbach et al. 2010) are now being designed to try to detect Earth-mass planets in the habitable zones of nearby low-mass M dwarfs. Target selection for these surveys (which tend to be very expensive in terms of telescope time) will benefit immensely from the characterization of activity and binarity in a large sample of M dwarfs.

Fully convective, late-type M dwarfs show strong magnetic activity (Morin et al. 2008; Browning 2008; Reiners & Basri 2008, Reiners & Basri 2009, Reiners & Basri 2010). A relation between stellar activity and projected rotational velocity () is well established for FGK stars (Noyes, 1984) and appears to govern the M dwarfs as well. Therefore, acts as a good proxy for activity. In general, fast rotating M dwarfs are more active than their slow rotating counterparts. Reiners & Basri (2008) showed that early M dwarfs are slow rotators while stars M5 and later, a boundary where they become fully convective (Chabrier Baraffe, 1997), are generally fast rotators ( 10 km s). A study of a sample of 27 M dwarfs over a period of 6 years by Gomes da Silva et al. (2012) found RV variations with a amplitudes 5 m s among 36 of their stars, which they attributed to magnetic cycles. Therefore, measuring to identify slowly rotating stars that are likely less active (or at least likely to exhibit less RV noise) is an important component of any search for low-mass companions to low-mass stars.

RV surveys of solar-type stars have estimated the frequency of giant planets at 7 for FGK stars (Marcy et al., 2000b; Udry et al., 2007) within 10 AU. The frequency of brown dwarf (BD) companions in RV surveys, however, falls down to about 0.6-1 at similar orbital distances (Marcy & Butler, 2000a; Grether & Lineweaver, 2006). When restricting the sample to ”hot Jupiters” (at a  0.1 AU), the frequency of giant planets is 1.2, and 2.5 for a  1AU. The expected frequency of close-in giant planets (a  1AU) from M dwarf survey at the Hobby-Eberly Telescope (HET) (Endl et al., 2003) is roughly 1.3 (Endl et al., 2006).

On the other hand, Metchev & Hillenbrand (2009) found a frequency of 3.2 of BDs from adaptive optics survey of 266 young solar type stars at larger distances between 28 - 1590 AU, and Lafrenière et al. (2007) found a frequency of 1.9 of BDs companion at 25-250 AU. Jódar et al. (2013) have found that the volume-limited binary fraction of early-to-mid type M dwarfs of 8.8 from a sample of 451 M dwarfs at less than 25 pc (at orbital distances less than 80 AU). When including literature data at larger orbital distances these authors find a binary fraction of 20.3.

Exploring these large orbital distances is probably beyond the capabilities of the APOGEE M Dwarf Survey, but we will be able to discover close-in BDs around M dwarfs, and therefore place constraints on the frequency of close-in BDs and maybe giant planets around M-dwarfs.

The well-established correlation between metallicity and planet occurrence seems to also apply to M dwarfs (Neves et al., 2013; Rojas-Ayala et al., 2012; Terrien et al., 2012a) The different between mean metallicity of the M-dwarf stars with and without giant planets is  0.20 dex (Neves et al., 2013), from a sample of 102 M dwarfs in the HARPS RV survey (Bonfils et al., 2013).

Imaging and RV observations of stellar multiple systems enable direct measurements of the physical properties of stars and provide a key window into the process of star formation. Comprehensive surveys probing a wide range of orbital separations using multiple observational techniques have been carried out for F, G, and K stars (Duquennoy & Mayor 1991; Raghavan et al. 2010), but sample sizes for similar surveys targeting low-mass stars remain small (Fischer & Marcy 1992; Marchal et al. 2003; Delfosse et al. 2004). There are, however, clear indications that the overall rate of occurrence of multiple systems is a strong function of stellar mass (Lada, 2006; Raghavan et al., 2010). Montet et al. (2013) find that  6.5 of all M dwarfs stars host a giant planet with 1 M 13 M and a 20 AU.

The distribution of orbital separations and mass ratios in multiple systems can be compared to numerical simulations of star formation. Individual binary star systems that eclipse, or that can be spatially resolved, can be used to make precise measurements of fundamental physical properties of stars, such as mass and radius (see Southworth et al. 2011 and Torres et al. 2012 for recent examples). These measurements provide primary observational constraints on theoretical models of stellar structure and evolution. At the bottom of the stellar main sequence only a handful of these systems are known, and measurements deviate from theoretical expectations at the level of a few percent(Chabrier et al., 2007; Torres, 2012; Feiden & Chaboyer, 2012; Terrien et al., 2012b). For this reason, it is particularly important to identify bright low-mass binaries over a wide range of orbital periods.

Previous large spectroscopic surveys designed to study M dwarf stellar properties (e.g. Reiners et al., 2012; Jenkins et al., 2009) have included 300 M dwarfs. In this paper, we describe an ongoing, extensive M dwarf spectroscopic survey of 1404 M dwarfs designed to detect low mass companions, quantify the statistics of stellar multiplicity, and measure basic stellar physical parameters at the bottom of the main sequence. Using 253 of the 1404 stars that have been observed so far, we illustrate the techniques employed to measure observational and model-derived stellar parameters, and we demonstrate the concurrent use of RV monitoring and AO imaging to search for stellar companions to our sample of M dwarfs. The reduced and calibrated spectra for this first set of stars will be publicly available as part of the SDSS-III DR10 data release in Summer 2013 and spectra for all stars will be released in Dec 2014 as part of the SDSS-III final data release. In addition to providing spectroscopic rotational velocities and radial velocities, this paper serves as an introduction to this unparalleled data-set, lays out our target selection choices, and highlights some of the science investigations we are undertaking.

2. The APOGEE M Dwarf Survey

The Apache Point Observatory Galactic Evolution Experiment (APOGEE, Majewski et al., 2010) is a high-resolution (R 22500), near-infrared ( band), multi-object, fiber-fed, and cryogenically cooled spectrograph (Wilson et al., 2010, 2012). The instrument is part of SDSS-III (Eisenstein et al., 2011), attached to the 2.5m SDSS telescope (Gunn et al., 2006) at Apache Point Observatory, and covers a wide field of view ( diameter). The instrument can observe up to 300 targets simultaneously on a three-segment mosaic of Teledyne H2RG 2048 x 2048 detector arrays. Each detector has a wavelength range of 0.07 m and covers 1.514 - 1.581 m (blue), 1.586 - 1.643 m (green), and 1.643 - 1.696 m (red), respectively. The entire assembly is enclosed in a vacuum shell and is intrinsically very stable.

Our M dwarf survey is an ancillary program to the main SDSS-III APOGEE survey, which began in September 2011 and will end in June 2014. The observations are made during bright time. The light from the telescope is focused onto standard SDSS plugplates which have holes drilled in them to accommodate fibers. A total of 300, 120 m fibers are attached to the plugplate. Each fiber has a 2” diameter. The 300 fibers on each plate are allocated as follows: 230 are placed on science targets, 35 on telluric standards (hot stars used to calibrate and remove telluric features), and another 35 fibers are placed in sky regions devoid of celestial objects in order to obtain sky spectra (Nidever et al. 2013). Multiple visits are made to many of the APOGEE fields during the course of the survey, allowing us to monitor RV variability among our sample of stars.

The main goal of APOGEE is to measure radial velocities and chemical abundances of 10 red giant branch stars spanning various Galactic environments such as the bulge, disk, bar, and halos (Majewski et al, in prep). Hence, the SDSS-III survey footprint primarily spans these regions. A detailed discussion of the APOGEE target selection and field plan can be found in Zasowski et al. (2013). Targets from our survey were generally distributed among fields with 3–24 visits, though some M dwarf targets are also present on single-visit fields. The M dwarfs can be identified in the DR10 release data by looking for bit flag 19. Spectra with this bit flag correspond to this program.

The APOGEE data reduction process is described in detail in Nidever et al. (2013). Products from the data reduction pipelines include: (1) apCframe files containing individual 1-D, dithered, wavelength calibrated spectra that represent individual exposures taken over the course of a single visit; (2) apVisit files consisting of co-added apCframe spectra from a single visit that are wavelength calibrated, flux normalized, and telluric corrected; and (3) apStar files including RV-shifted, co-added apVisit spectra and a best matching synthetic spectrum. A detailed list of various file formats are given in Nidever et al. (2013) and also described in detail as part of the SDSS-III DR10 release.

The goal of this survey is to characterize M dwarfs through measurement of projected rotational velocities, absolute RV, and metallicity, and to discover new low mass companions. This multi-epoch spectroscopic survey is sensitive enough to detect low-mass stellar and sub-stellar companions to M dwarfs and will also shed light on the statistics of stellar multiplicity at the bottom of the main sequence. Furthermore, these observations will create an atlas of high-resolution spectra in the NIR covering a wide range of sub-spectral types. These spectra are critical for modeling chemical abundances and probing the physical processes that occur in the complex atmospheres of M dwarfs. As an ancillary project to the APOGEE survey, this project has been awarded 6000 fiber hours 43 over the SDSS-III survey.

2.1. Target Selection

Targets for the APOGEE M dwarf survey primarily consist of stars from the all-sky Leṕine and Shara proper motion North catalog (Lépine & Shara, 2005, LSPM-N hereafter) and the all-sky catalog of bright M dwarfs (Lépine & Gaidos, 2011, LG11 hereafter).

The LSPM-N catalog contains stars with proper motions 150 mas yr. We apply magnitude and color cuts to select red stars that fall within the APOGEE target field plan (; ; ; ). Contamination from M giants in a sample of M dwarfs is not uncommon, but they can be distinguished from dwarfs using infrared color cuts. Stars that pass these selection criteria and lie on planned APOGEE main survey fields are selected as targets. Aspects of this selection are also discussed in Zasowski et al. (2013), which describes target selection for the entire APOGEE survey, but are presented in more detail here.

Figure 1.— Infrared color-color diagram of our sample. The gray points are the 7059 LSPM-N stars obtained using the magnitude and color-cuts described in Section 2.1. The LSPM-N (blue), LG11(red), and stars observed in year one (green) are also plotted. Stars within the box, defined as the “red dwarf box” in LG11, are likely to be dwarfs, though some contamination by giants is possible.

The LG11 catalog became available only after we had submitted targets for initial plate drilling. LG11 is an end result of a careful application of infrared color and magnitude cuts to stars in the SUPERBLINK proper motion survey with the goal of selecting bright M dwarfs. Stars in the catalog are limited by apparent magnitude 10 and 40 mas yr. When the catalog became available we used it to select targets for future plate drillings. To comply with our observational constraints, we apply declination () and magnitude cuts to their sample ( to avoid saturating the APOGEE detector array). An important point to emphasize is that while our LSPM-N cuts were designed to select stars of spectral type M4 and later, our LG11 selection includes M dwarfs of all spectral types. The target selection in color-color space is illustrated in Figure 1. The region defined by equations 9-13 from LG11 should contain stars that are potentially red dwarfs, while those objects outside the box, especially the reddest objects, are more likely M giants. We find that the majority of our target stars selected from LSPM-N (blue points) and LG11 (red points) lie within this box in color-color space.

Figure 2.— The entire APOGEE M dwarf sample (gray filled circles) and calibrators (magenta squares). The stars observed in the first year (Sept. 2011 - July 2012) are shown in color: LSPM-N (red filled circles), LG11 (green filled triangles). The vertical dash lines mark approximate positions of M dwarf spectral sub-types.

Each APOGEE field consists of a circular plate with a radius of 1.49. The plate has a bolt at the center with a radius of 5 that cannot accept fibers. We assembled our final target list by cross-correlating our master target list with the area covered by each APOGEE plate. We anticipate observations of more than 1400 M dwarfs over the course of the survey.

In the first year of the SDSS-III APOGEE survey 285 of these stars were submitted during plate drilling, of which 253 were observed (the remaining 32 were lost due to fiber conflicts with other targets or fell off the inner or outer plate edge when plate centers were slightly adjusted during final design). Figure 2 shows our entire sample in terms of color, magnitude, and approximate spectral types. The LSPM-N and LG11 (gray) is our total sample. The 253 targets observed during the first year are plotted as red (LSPM-N) and blue points (LG11). As a result of the timing of the LG11 catalog release, most of stars observed during the first year were selected from LSPM-N and have spectral type of M3.5 and later. The observations of these stars have produced 1127 spectra. The distribution of their magnitude is shown in Figure 3.

Figure 3.— Distribution of magnitudes of the targets observed during the first year (gray; Sept. 2011 - July 2012) and our entire sample (blue).

We have also deliberately targeted some calibration stars, which include RV standards from the California Planet Survey, standards from literature (Jenkins et al., 2009), stars from the MEarth Project (Nutzman & Charbonneau, 2008) and M dwarfs in the Kepler field that are known to be active (Ciardi et al., 2011; Walkowicz et al., 2011). The selection of calibrators do not follow the stringent magnitude and color-cuts used as listed above, with the exception of bright magnitude cut: . Figure 2 shows the sample (magenta squares). These stars are listed in Table 2. In total, 25 calibration stars have been observed in the first year.

In order to explore the relationship between M dwarf subtype and features in the APOGEE high-resolution spectra, we constructed a set of spectral templates, using the combined spectra in the apStar files. For each subtype, we grouped the spectra by their V-J color, which we calibrated to spectral type using the relation from Lépine & Gaidos (2011). and bins centered on integer spectral types (e.g. M3 contains all stars with V-J colors corresponding to M2.5 to M3.5). It is important to note that the V magnitudes for many of these targets are based on scans of photographic plates and are therefore only reliable to mag. This error in V corresponds to approximately 1-2 subtypes. We then shifted these spectra to a common RV, interpolated to a common wavelength grid, and filtered each spectrum for strong remaining sky lines and other artifacts. With these cleaned spectra, we constructed an unweighted average spectrum for each spectral type. The spectral type bins contained as few as three (M1) or four (M8) spectra and as many as 95 (M4) spectra. Finally, we constructed artificial spectra for each 0.1 subclass by linearly interpolating between subclasses for each pixel.

Figure 4.— The average spectrum for each approximate spectral type, binned by V-J color. The gray regions highlight the spectral-type sensitive regions that were used for spectral type estimation, and the numbers in parentheses indicate the number of targets in each bin.The three plots correspond to blue chip (top), green chip (center), and red chip (bottom).

We then constructed a routine to apply these templates to estimate the spectral type for any APOGEE M dwarf spectrum. We selected regions that showed the most sensitivity to spectral type (Figure 4), and set the remaining spectrum to a flat continuum. For each target we then performed a cross-correlation on these filtered spectra with the equivalently-filtered template spectra. The 0.1 subclass with the highest cross-correlation value was taken to be the estimated spectral type. Although this method is imprecise, it can be efficiently applied to estimate spectral types for large sets of targets with poorly constrained visual magnitudes. And despite the high uncertainties in the V-J colors, the likely range of values for our targets, and the possible multiplicity of many targets, these templates clearly demonstrate the regions of M dwarf spectra in the H-band that are the most sensitive to spectral type.

In addition to the M dwarfs directly selected as part of our ancillary program other M dwarfs are sometimes serendipitously observed by APOGEE. We do not discuss those in this intermediate data release paper, but they will be included in the final survey analysis.

3. Initial Results

Our APOGEE M dwarf spectra span a wide range of signal-to-noise (S/N). Depending on the target brightness and observing conditions, the S/N of individual APOGEE visits varies from a few tens to several hundred per resolution element. The number of visits available for each target for the stars observed in the first year of the survey also varies: some targets only have a single visit so far, while others have 12 or more. In the following subsections we present initial results based on the analysis of spectra from Year 1 of the survey.

3.1. Projected Rotational Velocities:

We measured projected rotational velocities for all of our targets using cross-correlation techniques. To maximize the precision of our measurement, we use the entire APOGEE spectral range. The first method cross-correlates a rotationally broadened synthetic spectrum against an observed target spectrum, and derives by maximizing the amplitude of the resulting correlation peak. The second method cross-correlates the observed spectrum of a slowly rotating template star against the observed target spectrum and measures the full-width at half-maximum (FWHM) of the resulting correlation peak. This width is compared to tabulated values obtained by rotationally broadening the template spectrum and cross-correlating it against the unbroadened version of itself. Both of these methods are described in further detail below.

Projected Rotational Velocities: Method I

Our first method for measuring the of a target star uses a synthetic template spectrum with stellar characteristics (, , and ), spectral resolution, and wavelength sampling that match those of the target. The template is rotationally broadened over a wide range of to generate a suite of broadened synthetic templates. Each broadened template is cross-correlated against the target spectrum, and the amplitude of the resulting correlation peak is measured. The correlation amplitude varies slowly with the template , and the peak of this function determines the best estimate. This technique utilizes the entire free-spectral range that we deem to be free of telluric absorption and night sky OH emission, and we have used it in several past analyses of cool star spectra (e.g, van Eyken et al., 2012; Bender & Simon, 2008). Observations with S/N or spectral resolution insufficient for more traditional approaches that examine the line profiles of specific individual spectral features (Gray, 1992), or where the spectral line density implies significant line blending, can still utilize this correlation based approach.

Figure 5.— Measurements of for M dwarfs, including the measurements presented here (blue filled circles) and those from the literature (gray filled circles), for a range of V-J colors. The dashed lines mark the approximate positions of M dwarf spectral sub-types.

Carrying out this analysis requires a priori knowledge of the target star’s , , and , so an appropriate synthetic template can be selected. An inaccurate choice at this point can introduce systematic errors in the derived rotational velocities. In the initial APOGEE data reduction pipeline, each apVisit spectrum is cross-correlated against a large grid of synthetic spectra as part of an initial spectroscopic characterization. The section of this grid that corresponds to 4000 K, and relevant for our M dwarf sample, is composed of synthetic spectra from the standard BT-Settl grid. These initial correlation-based estimates return to the nearest 100 K, and and to the nearest 0.5 dex. Most APOGEE spectra are subsequently passed through the APOGEE spectra analysis pipeline (ASPCAP), which re-derives these parameters with much finer precision. However, ASPCAP results are currently not regarded as reliable for cool stars with 4000 K. As such, we average the , , and derived for each visit spectrum from the synthetic grid, and use these values to select the appropriate BT-Settl model (Allard et al., 1997) for our analysis.

Figure 6.— Comparison of literature measurements of stars with Method 1. Stars in this figure include spectral types of A5 to M6. Literature M dwarfs are listed in Table 2. The solid line indicates 1:1. Literature stars that do not have reported errors are marked by dash lines.

The spectral resolution of a model must be degraded to match the resolution of the corresponding target spectrum. APOGEE’s spectral resolution varies across the spectral range, and from fiber to fiber (Wilson et al., 2012) across the spectral range, but the Line Spread Function (LSF) for each fiber is automatically parametrized by the reduction pipeline as a Gauss-Hermite polynomial and stored along with the individual visit spectra. APOGEE targets with multiple visits are not guaranteed to be carried out using the same spectrograph fiber, although in practice they often are. Targets with visits distributed over multiple fibers will result in visit spectra with slightly different LSFs; these effectively get averaged together when the data pipeline co-adds the individual visit spectra. For simplicity, we only consider a target’s average LSF, and approximate it as a Gaussian to derive the corresponding effective spectral resolution. We then degrade the synthetic template spectrum to the derived resolution.

We rotationally broaden the synthetic templates using a four parameter non-linear limb-darkening model (Claret et al., 2012; Claret, 2000; Gray, 1992), with parameters appropriate for the characteristics of the stellar spectrum and the APOGEE H-band bandpass, over a range of v from 3 km s – 100 km s. Finally, we resample both the APOGEE spectra and synthetic models to log-lambda wavelength space (Tonry & Davis, 1979) in preparation for cross-correlation. The apStar files produced by the APOGEE data pipeline contain co-added spectra for each multi-visit target using two different co-adding schemes. Our analysis measures both co-added apStar spectra, and also each of the individual apVisit spectra. The from the individual visit spectra are then combined using a weighted average, with the weights derived from the S/N of each visit. We take the standard deviation of the distribution as the measurement precision on , and impose the following additional rules: (1) single visit spectra have default precision of 2 km s; (2) multi-visit spectra with three or fewer visits have a minimum precision of 1 km s. In addition, we set a conservative floor in our ability to measure at 4 km s, which also corresponds to the minimum where the broadening kernel is resolved at APOGEE resolution and sampling.

We further tested the method by measuring of main sequence stars in the main APOGEE survey. We found 9 stars with spectral types of A5 – K0 with a large range of previously reported values (Randich et al., 1996; Mermilliod et al., 2008). Figure 6 illustrates this effort. Most of our stars are within 1- of the 1:1 line.

Projected Rotational Velocities: Method II

Our second method measures by cross-correlating object spectra against a slowly rotating template spectrum of similar spectral type and measuring the FWHM of the cross-correlation peak. This process is well established in literature (e.g. Bailer-Jones, 2004) and assumes that the line profile is primarily dominated by rotation.

Four slowly rotating stars are used as templates: 2M054709070512106 with 4.5 km s (Jenkins et al., 2009) and 2M19125504423937, 2M191211284316106, and 2M193324544515045 with rotation periods of 48.5, 19.0, and 42.6 days, respectively, determined from Kepler photometry (McQuillan et al., 2013). We used the apVisit and apStar files in the analysis.

Figure 7.— Comparison of measurements using Method 1 and Method 2, as described in Section 3.1. The solid line represents perfect agreement. The linear regression fit (y = Bx + A; B = 1.099, A = -1.212) is indicated by a dash green line.

Prior to cross-correlating, the spectra are first continuum normalized and strong telluric absorption lines and OH emission lines are masked out. In the H-band, the number of potential contaminating sky emission lines can be large, and even after sky subtraction the flux in the residual sky emission lines sometimes exceed the stellar flux by a considerable amount. If not masked, these telluric features can dominate the cross-correlation signal. To limit the number of mask edges, we define a small number of regions in the observed rest frame that are relatively free from the strongest telluric absorption and night sky emission features. For each object, these unmasked regions were checked for any major contamination (such as stellar flux set to zero). If any such contamination was found, the entire unmasked region was discarded. On the green chip, the four unmasked regions are 1.5875–1.5968, 1.6050–1.6065, 1.6150–1.6215, and 1.6240–1.6330 m. On the red chip, the three unmasked regions are 1.6505–1.6552, 1.6556–1.6650, and 1.685–1.690 m.

To map FWHM to , we broaden each of the template spectra with a rotation kernel for a range of between 2–30 km s in increments of 2 km s, from 30–60 km s in increments of 5 km s, and from 60–90 km s in increments of 10 km s. The rotational kernel is given by Equation 17.12 of Gray (1992), using a limb darkening parameter () of 0.25, which is appropriate for the NIR H band (Claret et al., 2012). These broadened templates are used as object spectra and run through the same pipeline as the program stars. For a given kernel we averaged the resulting FWHM of all the broadened spectra for each combination of chip and un-broadened template. This allowed us to create a mapping from FWHM to for each template and chip. The true modeled by the artificially broadened template includes both the intrinsic rotation of the template stars and the applied rotation kernel. To account for the intrinsic rotation, we used 4.5 km s as an estimate of the intrinsic stellar rotation, and set the of the artificially broadened spectra to be the quadrature sum of the intrinsic and the kernel . To apply this mapping to the object spectra, we fit a 6th-order polynomial to each relationship. The relationship for the blue chip was very different from that of the red and green chips, and we decided to exclude that chip in this paper. Although the mapping to varies little between each template, especially at low , we still mapped each combination of chip and template independently.

Before using the polynomials to map the FWHM of the object spectra to , we first apply a quality cut requiring that the height of the cross-correlation peak be at least 0.4 and that the center of the cross-correlation peak be within 5 km s of zero, since all apStar spectra should be in the stellar rest frame. These cuts should remove correlations for which the largest peak is in fact a noise peak. The FWHM measurements making this cut are mapped to , and we compute an upper and lower by mapping to the average FWHM plus and minus the standard deviation in the FWHM, respectively. These are used for upper and lower errors in . In all of these cases, small FWHM that would otherwise map to negative values are set to zero. Next, we average together all the measurements for a given chip. We propagate the high and low errors by taking the quadrature sum of each. We also compute the standard deviation in the values () as a measure of systematic errors arising from the different templates. Finally, we take a weighted average of the two individual chip ’s to compute the final , denoted (). The weights are given by . We set a floor of to 0.5 km s, to avoid giving overly high weights. The final error in the is given by the quadrature sum of the formal errors and the measured standard deviation.

The two methods, as discussed above, independently measure of the M dwarfs from Year 1, and are directly compared in Figure 7. For most stars with   9 km s, the measurements derived from two methods are within 2- of the 1:1 line. However, for below 9 km s we find that method 2 either underestimates velocities or method 1 overestimates them for some of the stars. Nonetheless, most of the slow rotators are within 1- of the 1:1 line.

Figure 8.— APOGEE relative RV measurements compared to the published orbit for HD114762.

Both methods rely on a comprehensive library of templates. Method 1, uses the BT-Settl models (Allard et al., 1997) at the finest grid these atmospheric models provide. However, Method 2 is limited by a small number of observed templates. This is a consequence of finding few templates that overlapped with pre-designed APOGEE fields. Preliminary APOGEE spectra pipeline analysis suggests that all of the observed templates have T between 3300-3500 K while their V–J colors confirm them to be early M dwarfs. The same analysis done on our sample indicates a T range of 3500 K - 2700 K with the mean T of 3300 K. However, there are 70 stars with T below 3100 K. As the chemical composition of M dwarfs changes faster than the effective temperature Reiners et al. (2012), early M dwarf templates are likely to give erroneous measurements for late-M dwarfs. For completeness and due to lack of a comprehensive library of observed templates in our sample, we report measurements as derived by Method 1. These measurements are listed in Table 1 along with their errors. Figure 5 plots measurements derived from Method 1 (blue filled circles) as a function of V–J color along with those from literature. Upper limits on slow rotators of 4 km s are indicated by downward arrows. For comparison we also plot literature values (gray filled circles).

Figure 9.— APOGEE relative RVs for two low-mass stars. 2M1426+0510 (top panel) is a K0 star with a known planetary companion, resulting in a RV semi-amplitude of 7.32 m s at an orbital period of 3.41 years (Howard et al., 2010).

3.2. Relative Radial Velocities using Telluric Modelling

APOGEE is, in principle, very well suited for making precise RV measurements of low-mass stars because of the LSF stability intrinsic to a fiber-fed instrument housed in a vacuum enclosure. While the modest resolution of the instrument precludes precision at the level achieved by instruments designed specifically for RV planet searches at optical wavelengths, such as HARPS (Mayor et al., 2003), precision better than 50 m s should be possible for bright targets. Given the low masses of our targets, this is sufficient to detect a wide range of companions, including giant planets with short orbital periods.

Precise RV instruments generally rely on one of two strategies for calibrating the pixel-to-wavelength scale of the instrument and monitoring short- and long-term instrumental drifts: an emission line source coupled via an optical fiber to a stabilized instrument or an absorption reference gas cell in the telescope beam prior to the entrance of a slit spectrograph. The primary wavelength calibration of the APOGEE data relies on a combination of ThAr and UNe lamps (Redman et al., 2011, 2012), but the numerous telluric absorption features present in the APOGEE spectra can act as a wavelength reference, providing a secondary wavelength calibration that is obtained simultaneously with the stellar spectra. The bulk motion of the atmosphere causes instability in telluric absorption features at the 5–10 m s level (e.g. Figueira et al. 2010 and references therein). Given the resolution of APOGEE and the typical S/N of the spectra, we expect the RV precision limitations imposed by the intrinsic stability of the telluric lines to be a factor of a few smaller than the limitations imposed by the intrinsic information content of the spectra and the stability of the spectrograph.

To estimate small corrections to wavelength solutions derived from the emission line lamps alone, we forward model the APOGEE spectra using a technique similar to the one used in Blake et al. (2010) and Rodler et al. (2012), which are both based on the data analysis strategy outlined in Butler & Marcy (1996). We model spectra spanning 850 pixels from the green chip, covering the approximate wavelength range 1.598 to 1.616 m. While this is less than a third of the total spectral coverage of APOGEE, this region is rich with telluric and stellar spectral features and also suffers less from the undersampling of the LSF found at bluer wavelengths. Following Blake et al. (2010), we forward model the spectra as the product of a stellar template and telluric model convolved with the spectrograph LSF. For a stellar template, we use the apStar spectra, the weighted combination of all the individual spectra of each object, produced by the APOGEE pipeline. We deconvolve this apStar template with the LSF estimated by the APOGEE pipeline (Nidever et al., 2013) using a Jansson technique based on that used in Butler & Marcy (1996). Given enough APOGEE epochs over a wide enough range of barycentric velocity, this technique can effectively average out errors due to imprecise telluric modeling and residuals from the subtraction of bright sky lines. We note that constructing a template in this way makes all of our resulting RV measurements fundamentally differential and also relies on the assumption that any intrinsic stellar RV variations are small compared to the barycentric motions and the APOGEE pixels (1 pixel  5 km s)

In the spectral region we are focusing on, there are prominent telluric absorption features due to CO. We calculate a high-resolution telluric transmission model appropriate for average conditions at Apache Point Observatory using the radiative transfer code described in Blake & Shaw (2011). Our model for the APOGEE spectra has four free parameters: one optical depth scale factor for the telluric model, two for a linear wavelength correction to the APOGEE pipeline wavelength solutions, and one for stellar velocity. We use the LSFs provided by the APOGEE pipeline. We fit the individual apCframe spectra, several of which are obtained at each epoch as part of a dither set. The model is first generated at a resolution seven times the APOGEE resolution, then interpolated to the APOGEE wavelength scale while explicitly integrating over the extent of each detector pixel. We use the AMOEBA downhill simplex method (Nelder & Mead, 1965) to fit the model to each apCframe spectrum and find the best-fit values for the four free parameters by minimizing . Prior to fitting each spectrum we mask out regions known to have strong OH emission lines. Finally, we decorrelate the RV estimates from the forward modeling process against the measured skewness of the APOGEE pipeline LSFs for each apCframe spectrum. We found that this correction improves the scatter of the resulting RV measurements by up to 30 m s.

In Figures 8 and 9 we show examples of RV precision, including a star known to be RV stable to better than 10 m s and the giant planet companion to the star HD114762 (Latham et al., 1989; Kane et al., 2011). This was observed serendipitously by APOGEE as a telluric standard, and was independently recovered as a signal of a possible sub-stellar companion. It serves to demonstrate that NIR radial velocities even with a survey instrument are at the level of precision to enable discovery of giant planets. The telluric modeling techniques presented here are still being developed, improved, and more precise radial velocities deriving from this analysis will be presented in future work.

3.3. Barycentric Radial Velocities

Barycentric radial velocities for each star are derived in the final step of the pipeline reduction process. The detailed description of this RV determination is given in Nidever et al. (2013). Here, we summarize the steps. Radial velocity is determined by cross-correlating a normalized observed spectrum with a library of synthetic BT-Settl models that span the effective temperature and range of M dwarfs with metallicities between -4.0 and 0.3. First, a model template is selected through cross-correlating each model template from the library with the observed target. The best template is chosen through minimization. This template is then cross-correlated with the observed spectra of the target and velocity is estimated by fitting the CCF with a Gaussian plus a linear fit. Finally, a barycentric correction is applied to this velocity measurement. The standard deviation of the RV measurements from multiple observations is 130 m s. The absolute RVs of stars from our sample are listed in Table 1. For the sake of consistency these velocities are the same as those released as part of the pipeline output with the DR10 release. The column of -RV in Table 1 shows the RMS scatter in the measured radial velocities for stars that have measurements at three or more epochs.

Stars that show RV variation larger than 1 km s or result in CCFs with distinct peaks are identified as potential binaries. These candidate binaries are listed in Table 4 along with the number of observations and their infrared magnitudes. Orbital parameters, mass ratios and other analysis of these systems will be presented in separate papers, along with additional radial velocities and high-resolution spectra.

3.4. Physical Parameters of M dwarfs

Important improvements in stellar atmospheric models of low-mass stars have resulted from the availability of new atomic line profile data and the inclusion of dust and clouds in the models. Atomic line profile data becomes especially important in situations where line blanketing and broadening are crucial, and stellar models incorporating these updated atomic data give a much improved representation of the details of the line shapes in optical and NIR spectra of cool dwarfs (Rajpurohit et al., 2012). The recent suite of synthetic BT-Settl models include dust and clouds in their computation of stellar atmospheres and therefore provide a good fit to the observed stellar spectrum. These model atmospheres are computed with the PHOENIX code assuming hydrostatic equilibrium and convection using mixing length theory (Prandtl, 1926) with a mixing length of according to results of radiation hydrodynamics (Ludwig et al., 2006). The models are calculated using spherically symmetric radiative transfer, departure from LTE for all elements up to iron, the latest solar abundances by (Asplund et al., 2009; Caffau et al., 2011), equilibrium chemistry, a database of the latest opacities and thermochemical data for atomic and molecular transitions, and monochromatic dust condensates and refractory indexes. Grains are assumed spherical and non-porous, and their Rayleigh and Mie reflective and absorptive properties are considered. The diffusive properties of grains are treated based on 2-D radiation hydrodynamic simulations, including forsterite cloud formation to account for the feedback effects of cloud formation on the mixing properties of these atmospheres (Freytag et al., 2010). They are distributed via the PHOENIX web simulator44.


Figure 10.— Comparison between the observed spectrum (blue) and the model (red) for one of our M dwarf targets. The stellar parameters for this star are listed in Table 3. The BT-Settl model that fits best has the following parameter: T = 3000 K; = 5.0; Fe/H = 0.3. The three panels illustrate the wavelength coverage of three chips: the blue chip (top panel), the green chip (center panel) and the red chip (bottom panel).

We selected four APOGEE M dwarfs that have also been observed by us with the IRTF (Terrien et al., 2012a) and for which we have derived empirical H-band low-resolution metallicities. We used these stars and performed a detailed analysis between BT-Settl models and the spectra. We compute synthetic spectra over the entire spectral range of interest using a model grid described as follows: T from 2000 K to 4000 K with 100 K steps, log g = 5.0 and 5.5, [M/H] = -2.0 dex to +0.5 dex with 0.5 dex steps. We convolve the synthetic spectra with a Gaussian kernel at the APOGEE resolution and then rebin to match the pixel sampling of the observations. As a first step, we calculate a goodness of fit statistic by comparing the observed spectra with the grids of synthetic spectra. This allows us to estimate effective temperature. Next, assuming this effective temperature we use the most prominent lines in the spectra, the atomic Al lines at 16718 and 16750, to constrain the other parameters (log g and [M/H]). The derived parameters are given in Table 3. The comparison between the observed spectrum (blue) and the best fit model (red) is shown in Figure 10 for 2M19081153+2839105.

We derive stellar parameters using our improved atmosphere models and spectroscopic information covering the given NIR range. Metallicity and gravity are determined from specific spectral features such as Al i, Fe i and Ca i, whereas effective temperatures are constrained from the overall shape of the spectra via the following steps: (1) a first minimization is performed on the overall spectra considering effective temperature, metallicity, and gravity as free parameters. It gives a first guess for the parameter space of each component; (2) we look for those specific spectral features that are mainly sensitive to metallicity or gravity to refine these two parameters; (3) we fixed these parameters to perform another minimization and derive effective temperature. At each step we check that the resulting value is not sensitive to changes in the values of the other parameters

Figure 11.— Adaptive optics images of three APOGEE M-dwarf targets taken at Palomar (left) and Keck (middle, right). Our diffraction-limited observations help assess the multiplicity of sources by probing separations complementary to RV observations.

The synthetic spectra reproduce very well most of the spectral features like Fe i, Ca i, Al i. Some discrepancies remains in the strengths of some atomic lines, which are either too strong or weak in the model, such as Fe i (15267.02 Å, 15237.7 Å, 15335.00 Å, 15964.87 Å), and Ca i (16197.04 Å). This is mainly due to the fact that the models have to use some incomplete or approximate input physics, such as broadening damping constants and uncertain oscillator strengths, for some lines and molecular bands. Also, the BT-Settl models use general atomic damping constants according to Unsöld (1968) with a correction factor to the van der Waals widths of 2.5 (Valenti & Piskunov, 1996), and van der Waals broadening of molecular lines with generic widths according to Homeier et al. (2003). Furthermore, the BT-Settl models do not have a good handle on modeling the HO bands. This discrepancy is clearly seen in panel 3 of Figure 10

Recent progress has been made in the development of empirical calibrations that allow estimation of [Fe/H] for M dwarfs to a precision of 0.12 – 0.15 dex (Rojas-Ayala et al., 2012, 2010; Terrien et al., 2012a). Terrien et al. (2012a) developed such a calibration that uses the equivalent widths of specific regions in R 2000 band M dwarf spectra (Terrien et al., 2012a). This relation is calibrated using a set of 22 M dwarf companions to FGK stars having well-constrained metallicities and by assuming the individual systems are coeval. Column 3 in Table 3 lists the metallicity of three M dwarfs observed by APOGEE and that have had their metallicity determined using this technique using spectra from the IRTF. The three methods agree with each other within the errors. The more comprehensive comparison study of the metallicity determination through empirical spectroscopic relationships and stellar atmospheric modeling will be explored in a subsequent paper.

The features used for the band calibration are K I (1.52 m) and Ca I (1.62 m). These features fall inside the spectral region covered by APOGEE, and so should be amenable to a similar empirical calibration strategy as employed with R 2000 spectra used in Terrien et al. (2012a). The results of this empirical metallicity calibration for APOGEE observations of M dwarfs will be presented in a subsequent paper.

3.5. AO Imaging of M dwarfs

We have initiated an extensive campaign to collect adaptive optics (AO) imaging of a significant sample of M dwarfs in the APOGEE RV survey in an effort to also detect binaries at wider separations. A number of factors make this attractive and practical:

  1. Because they are intrinsically faint, M dwarfs offer less demanding contrast requirements compared to solar-type stars for the direct imaging detection of low-mass companions at small angular separations.

  2. M dwarfs in close proximity to the Sun ( pc) are (nevertheless) sufficiently bright to serve as their own natural guide star.

  3. AO instruments offer diffraction-limited performance at near-infrared wavelengths, facilitating the detection of faint (and red) companions whose black-body radiation peaks in the m range.

  4. By concentrating companion light into a compact and locally-intense point-spread-function, the sensitivity of AO observations benefits from an increased signal-to-noise ratio compared to seeing-limited or speckle observations.

Large aperture telescopes equipped with AO imagers, such as Palomar (Bouchez et al., 2009), Keck (Wizinowich et al., 2000), and the Large Binocular Telescope (Esposito et al., 2012), provide sensitivity to stellar companions of any mass using only seconds of integration time. High-contrast observations, such as those using AO in combination with a coronagraph and/or point-spread function subtraction (Marois et al., 2006), are sensitive to brown dwarfs over essentially all masses and ages with 1 hr integration times, even at sub-arcsecond separations (Crepp et al., 2012a).

The scientific motivation for combining precision RV measurements with AO observations is equally compelling. By combining two complementary observing techniques, it is possible to place strong constraints on the presence of both short-period and long-period companions around each star. A joint Doppler and imaging survey will enable detailed studies of stellar multiplicity at the low-mass end of the main sequence. Further, the frequency of brown dwarf companions to low-mass stars is still unknown in a large fraction of the parameter space explored by our survey. For instance, Metchev & Hillenbrand (2009) have quantified the occurrence rate of brown dwarfs orbiting FGK stars in the 29-1590 AU range, but similar studies for M-dwarf primaries have only recently commenced (Bowler et al., 2012).

In addition to discovering a plethora of short-period companions, APOGEE’s multiplexing capabilities will also reveal systems that exhibit long-term Doppler accelerations indicating the presence of unseen wide-separation companions. RV ”trends” act as a signpost to identify promising AO imaging follow-up targets (Crepp et al., 2012b). In the case of a direct detection, multi-epoch AO imaging and continued Doppler measurements can ultimately lead to the construction of three-dimensional orbits and calculation of dynamical masses (Crepp et al., 2012b). Such mass ”benchmark” systems may in turn be used to explicitly calibrate theoretical atmospheric models and theoretical evolutionary models of cool dwarfs. Finally, in the case of a non-detection, it is possible to place strong constraints on the mass and period of putative companions (Rodigas et al., 2011; Montet & Johnson, 2013).

Motivated by these factors, we have commenced AO observations of M-dwarf targets in the APOGEE target list starting with the brightest sources. Several candidate companions have been identified using the PALM-3000 AO system at Palomar (Bouchez et al., 2009) and PHARO camera (Hayward et al., 2001) as shown in Figure 11. Given their proximity to the Sun, M dwarfs in our sample generally have a high proper motion. With  10 mas astrometry precision, consecutive observations separated by only several months may be used to unambiguously determine whether each candidate shares a common proper motion with its host star. First epoch and follow-up AO measurements are on-going. Figure 11 gives examples of some of the M dwarf binary candidates that have been discovered through AO imaging. Table 4 lists their angular separations, position angles, and delta magnitudes.

4. Discussion Future Prospects

The APOGEE M dwarf survey described here will produce a catalog of multi-epoch RV measurements of more than 1400 low-mass stars. These RV measurements are derived from high-S/N, high-resolution (R) H-band spectra gathered as part of an ancillary science program of the main SDSS-III APOGEE survey. These observations will be used to identify individual low-mass spectroscopic binaries, and possibly even short period giant planets. The APOGEE spectra routinely provide velocity precision better than 100 m s, and we have shown that for bright targets, a detailed analysis of the spectra and the telluric absorption lines they contain can result in precision better than 50 m s. At the same time, these spectra can also be modeled to measure projected rotational velocities, , and chemical composition. We present measurements for over 200 M stars, a significant increase in the total number of available rotation measurements for low-mass stars. Another outcome of this survey is the determination of metallicity through empirical measurements and with the use of stellar atmosphere models such as the BT-Settl models. Combining the results of different analyses of the APOGEE M dwarf spectra will provide a wealth of information about the structure and evolution of the lowest mass stars.

One of the primary goals of this survey is to quantify the rate of occurrence of companions to M dwarfs over a wide range of separations and mass ratios. This complete picture of M dwarf multiplicity will place important observational constraints on theoretical models of the formation of stars at the bottom of the main sequence. We will carry out a joint analysis of wide-separation companions identified through AO imaging and small-separation companions detected as spectroscopic binaries in the APOGEE data. With over 1400 targets in our RV sample, we expect to detect a large number of binaries, significantly more than any previous single survey. Kinematic measurements derived from these RV data will also be important for placing the local population of M dwarfs in the context of Galactic stellar populations.

We have carried out a Monte Carlo simulation to estimate our expected sensitivity to short-period companions with a range of masses. We use the actual observational cadence for over 200 M dwarfs observed by APOGEE so far and a simple model for RV precision as a function of magnitude ( for  mag) to simulate APOGEE RV surveys. We assume Gaussian noise for stars drawn randomly from the actual magnitude distribution (Figure 3) and inject RV variations resulting from Keplerian orbits. We assume each star has a mass of and consider mass ratios in the range 0.001 to 1.0 and orbital periods from 1 to 300 days. We select random inclinations, orbital phases, and orbital orientations, and set eccentricity to for periods less than 10 days and uniformly distributed between 0 and 0.8 for longer periods. For each simulated set of RV measurements of a star we calculate assuming the null hypothesis of RVs consistent with no variation and count the injected Keplerian orbit as ”detected” if the probability of greater than or equal to the given value is less than 1. We average the percentage of detections, , in bins of and orbital period and show the results of this simulation in Figure 12. Contours corresponding to , and detection efficiency are shown.


Figure 12.— Results of a simulation of detection efficiency. Areas above each line correspond to detection efficiency above a given . For example, we expect sensitivity to companions with mass ratios and orbital periods less than 300 days (red, solid line).

Our simulations indicate that the survey will have nearly complete sensitivity to companions with masses greater than and orbital periods less than 300 days. At orbital periods less than 10 days, we have excellent sensitivity to companions down to . For stars brighter than =9 (N=235), we are sensitive to companions out to orbital periods of 40 days. With this sensitivity and the published occurrence rates for M dwarf binaries and giant planets orbiting M dwarfs, we expect to detect dozens of new spectroscopic binary systems and place strong limits on the frequency of giant planet companions around M dwarfs of all spectral types.

Given its large sample size and excellent RV precision, the APOGEE M Dwarf Radial Velocity Survey will provide a rich data set useful for addressing a number of important outstanding questions about low-mass stars. This survey will generate a large, homogeneous sample of M dwarf measurements, and when completed in 2014, will represent an unprecedented resource useful for studying stellar populations, binary statistics, and measuring physical stellar parameters. At the same time, the physical stellar parameters derived from the APOGEE observations will greatly benefit future planet search surveys such as HPF (Mahadevan et al., 2012) and CARMENES (Quirrenbach et al., 2010) by providing detailed information about chemical composition of low-mass stars that are found to host planets. This first paper in a series serves to describe the target selection and present rotational velocities and radial velocities derived from over 1000 individual spectra of more than 200 M dwarfs. The data described in this paper become publicly available as part of the SDSS-III DR10 data release in July, 2013.

This work was partially supported by funding from the Center for Exoplanets and Habitable Worlds. The Center for Exoplanets and Habitable Worlds is supported by the Pennsylvania State University, the Eberly College of Science, and the Pennsylvania Space Grant Consortium. We acknowledge support from NSF grant AST 1006676 and AST 1126413 in our pursuit of precision radial velocities in the NIR. This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France. This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. The authors are visiting Astronomer at the Infrared Telescope Facility, which is operated by the University of Hawaii under Cooperative Agreement no. NNX-08AE38A with the National Aeronautics and Space Administration, Science Mission Directorate, Planetary Astronomy Program. JRC acknowledges support from NASA Origins grant NNX13AB03G. This research has made use of NASA’s Astrophysics Data System. This work was based on observations with the SDSS 2.5-meter telescope. Funding for SDSS-III has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, and the U.S. Department of Energy Office of Science. The SDSS-III web site is http://www.sdss3.org/. SDSS-III is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS-III Collaboration including the University of Arizona, the Brazilian Participation Group, Brookhaven National Laboratory, University of Cambridge, Carnegie Mellon University, University of Florida, the French Participation Group, the German Participation Group, Harvard University, the Instituto de Astrofisica de Canarias, the Michigan State/Notre Dame/JINA Participation Group, Johns Hopkins University, Lawrence Berkeley National Laboratory, Max Planck Institute for Astrophysics, Max Planck Institute for Extraterrestrial Physics, New Mexico State University, New York University, Ohio State University, Pennsylvania State University, University of Portsmouth, Princeton University, the Spanish Participation Group, University of Tokyo, University of Utah, Vanderbilt University, University of Virginia, University of Washington, and Yale University. Facilities: SDSS, IRTF.
Object J mag H mag K mag Visits Visits RV -RV - Binary
(2MASS ID) Planned Yr 1. (km s) (km s) (km s) (km s)
2M00034394+8606422 12.307 11.738 11.485 5 3 10.80 0.28 13.20 1.50
2M00085424+6716518 11.674 11.131 10.836 5 12 10.07 0.19 27.60 1.40
2M00110613+7202521 12.247 11.660 11.414 4 12 7.64 0.24 4.20 1.70
2M00131578+6919372 8.556 7.984 7.746 4 12 13.57 0.17 6.00 0.20
2M00184520+7040399 12.185 11.620 11.389 4 12 0.05 0.15
2M00185999+5836527 11.839 11.264 11.009 6 12 7.75 0.38
2M00222083+8619567 11.564 11.018 10.675 5 3 36.70 0.10 8.10 0.60
2M00234573+5353478 12.060 11.483 11.179 3 12 5.24 0.47 10.10 1.20
2M00251480+6225017 12.306 11.777 11.461 6 12 29.55 0.26 6.90 1.60
2M00251602+5422547 11.775 11.215 10.819 3 12 63.27 0.20 9.20 0.40
2M00252974+5412240 11.656 11.018 10.790 4 12 10.34 0.36
2M00255540+5749320 11.607 11.035 10.762 6 12 26.05 0.17 5.40 0.40
2M00274401+5330504 11.486 10.891 10.606 4 12 19.48 0.11 8.90 2.10
2M00321574+5429027 9.387 8.827 8.570 4 12 14.75 0.13 5.70 0.40
2M00331747+6327504 12.284 11.758 11.489 5 12 16.55 0.10 6.90 0.50
2M00333033+7054422 11.277 10.691 10.452 4 12 78.93 0.37 6.70 0.80
2M00350487+5953079 11.039 10.401 10.166 6 12 0.40 0.17 7.40 1.10
2M00391896+5508132 10.021 9.519 9.236 4 12 29.76 0.18 5.70 0.70
2M01094190+8612302 12.026 11.327 11.089 5 3 52.30 0.08 9.90 0.70
2M01195227+8409327 9.855 9.314 9.025 5 3 41.01 0.09 5.80 0.90
2M01333457+6220188 11.500 10.916 10.645 2 3 44.19 4.30 2.80
2M01382032+6246328 12.496 11.966 11.669 2 3 47.80
2M01422966+8601414 10.865 10.241 10.022 5 3 14.24 0.19 11.00 0.70
2M02040123+4855372 10.935 10.368 10.076 4 3 31.28 0.15
2M02081366+4949023 12.043 11.476 11.136 4 3 63.77 0.27 10.10 0.80
2M02085359+4926565 8.423 7.811 7.584 4 3 SB1
2M02144781+5334438 11.814 11.272 11.036 1 3 39.39 5.80
2M02170514+5434535 10.482 10.043 9.781 1 3 43.43
2M02210709+5457023 11.812 11.158 10.907 1 3 27.04 5.60
2M02250239+6006593 11.817 11.244 10.999 3 3 15.23 0.32
2M02595985+6514530 11.901 11.274 11.010 1 3 16.67 8.70
2M03042484+6641064 12.381 11.801 11.511 1 3 8.29 7.20
2M03104313+3854093 11.607 10.975 10.748 4 3 19.35 0.38 5.80 0.30
2M03140624+5728568 11.528 10.873 10.615 2 3 27.81 7.90 1.50
2M03150691+4016231 12.204 11.635 11.355 4 3 54.22 0.18 6.10 1.20
2M03152943+5751330 11.121 10.533 10.271 2 3 76.71 6.70 0.20
2M03220945+7047486 10.913 10.284 10.007 5 3 17.52 0.10 5.90 1.90
2M03224269+7932066 11.040 10.491 10.220 11 24 0.96 0.21 9.80 0.80
2M03264491+7108292 10.877 10.268 10.022 5 3 46.42 0.12 5.90 0.30
2M03300766+4711159 11.610 11.018 10.737 8 12 13.66 0.46 5.90 1.50
2M03305285+5627325 10.191 9.531 9.287 2 3 15.67 4.20 2.10
2M03305473+7041145 9.487 8.938 8.675 5 3 21.15 0.07 4.70 1.70
2M03334490+7054444 11.337 10.742 10.460 5 3 5.56 0.25
2M03355099+7140275 10.340 9.725 9.446 5 3 5.35 0.20 8.10 0.50
2M03425325+2326495 10.202 9.545 9.316 3 3 35.55 0.04 12.70 0.50
2M03425617+2515528 11.513 11.061 10.706 3 3 106.26 0.11 8.80 1.50
2M03431519+5006558 11.486 10.878 10.628 5 12 28.98 0.31 6.70 0.90
2M03441913+7126195 11.905 11.271 11.049 5 3 9.68 0.41
2M03443389+7125059 11.916 11.283 11.036 5 3 11.32 0.38 6.80 1.50
2M03494426+8027289 11.834 11.272 10.994 11 24 SB1
2M03504584+8026223 11.226 10.669 10.411 11 24 5.40 0.31
2M03515527+2356547 12.314 11.787 11.587 3 3 47.91 0.19
2M04030024+5238026 12.016 11.504 11.239 6 12 4.83 0.14 5.90 0.70
2M04063732+7916012 10.034 9.486 9.194 11 24 1.36 0.14 5.20 2.00
2M04081814+5127550 11.724 11.148 10.862 6 12 29.10 0.21
2M04104186+5124238 11.817 11.223 10.951 6 12 22.76 0.19
2M04125880+5236421 8.773 8.248 7.915 6 12 SB1
2M04234272+5605429 12.279 11.691 11.400 6 12 21.05 0.13 7.70 2.50
2M04281703+5521194 12.514 11.912 11.648 6 12 SB2
2M04293734+5455319 12.083 11.445 11.167 6 12 23.81 0.11 7.30 2.10
2M04314006+5501136 11.948 11.304 10.973 6 12 22.92 0.11 10.80 1.50
2M04422854+5818015 10.754 10.186 9.946 6 12 27.26 0.13 7.20 1.00
2M04480390+5718092 12.525 11.939 11.623 6 12 32.00 0.25 6.80 0.80
2M04480517+3732402 12.504 11.888 11.609 6 12 41.08 0.44 5.60 1.60
2M04542406+3830436 11.346 10.797 10.529 6 12 13.95 0.21 9.00 1.20
2M04572425+2149303 11.958 11.348 11.050 2 3 35.99
2M05011792+4204125 10.676 10.047 9.808 3 3 20.06 0.13 7.60 0.80
2M05011802+2237015 10.161 9.591 9.232 2 3 31.56 8.80 0.30
2M05014944+2127375 11.591 10.962 10.718 2 3 39.94 5.10 3.20
2M05030563+2122362 9.750 9.165 8.888 2 3 49.93 16.80
2M05062444+2230199 12.037 11.470 11.158 2 3 31.73 7.50 3.80
2M05104796+2410125 10.187 9.588 9.333 6 12 31.07 0.31
2M05172841+2531214 11.750 11.130 10.888 5 12 26.76 0.11 7.80 2.40
2M05210188+3425119 11.879 11.319 11.022 3 3 6.54 0.18 7.80 3.40
2M05255532+3528438 12.468 11.900 11.626 3 3 81.45 0.04 10.30 0.40
2M05320969+2754534 12.562 11.976 11.613 4 12 22.81 0.18 13.20 1.90
2M05424060+6134403 11.424 10.835 10.574 3 3 46.26 0.15 6.50 0.50
2M05445320+3018018 11.658 11.014 10.733 5 12 32.55 0.20 7.30 0.90
2M054709070512106 10.039 9.514 9.177 3 3 54.88 0.20 6.40 1.70
2M06034934+3019208 9.735 9.128 8.845 6 12 14.48 0.17 6.90 1.00
2M06070493+1403109 11.421 11.063 10.768 6 12 50.68 0.16 6.80 1.20
2M06115599+3325505 10.163 9.591 9.345 6 12 SB2
2M06205178+3145134 11.362 10.775 10.462 6 12 83.61 0.15 9.60 0.70
2M06213640+3222390 11.041 10.433 10.155 5 12 SB1
2M06215046+1554140 11.389 10.817 10.553 1 3 35.65
2M06293433+1742419 11.755 11.195 10.905 6 12 20.88 0.22 6.30 0.80
2M06293962+1723109 12.481 11.976 11.678 6 12 38.98 0.33
2M06320207+3431132 10.692 10.143 9.864 1 3 10.57
2M06362535+1830520 11.014 10.485 10.193 6 12 36.60 0.17 6.40 0.20
2M06481555+0326243 11.555 10.943 10.585 5 12 17.41 0.11 16.60 1.10
2M07015902+0456273 11.923 11.411 11.141 5 12 128.60 0.27 7.60 1.30
2M07104573+0619385 12.335 11.869 11.569 13 12 33.17 0.61 11.10 2.30
2M07125105+3707340 11.114 10.596 10.265 3 3 24.32 0.49 20.40 1.30
2M07140394+3702459 11.976 11.252 10.838 3 3 40.03 0.11 12.80 0.50
2M07382463+0948552 12.288 11.687 11.457 3 3 7.53 0.24 5.10 1.60
2M07404603+3758253 11.787 11.275 11.002 7 3 SB1
2M07454991+3716280 11.589 10.997 10.712 7 3 22.57 0.14 6.70 1.00
2M08160527+3028386 12.508 11.910 11.610 6 12 35.94 0.29 7.90 1.20
2M08501918+1056436 11.282 10.675 10.407 3 3 32.97 0.09 9.20 2.10
2M08505983+1130493 12.374 11.795 11.533 3 3 51.93 0.27 11.00 1.50
2M08584396+3727389 12.137 11.585 11.341 2 3 4.19 6.20 0.80
2M09031291+3739077 12.578 11.956 11.709 2 3 16.24 9.80 2.00
2M09120266+3636314 12.230 11.647 11.342 2 3 28.72
2M09301445+2630250 8.866 8.284 8.020 2 3 20.84 6.70 1.50
2M09321296+2745465 11.722 11.101 10.799 2 3 20.14 10.40 0.80
2M09391173+3837561 11.921 11.335 11.037 2 3 20.73 9.00 1.10
2M10150280+0140004 11.595 10.986 10.767 1 3 42.04
2M10162955+0318375 10.859 10.264 10.007 1 3 2.49
2M10164852+0041408 12.357 11.807 11.481 1 3 41.03 9.50
2M10245696+1721531 11.966 11.402 11.064 3 3 41.00 0.05 9.80 1.80
2M10304397+1624207 11.783 11.174 10.875 3 3 38.00 0.01 5.10 2.20
2M10345281+3911043 10.863 10.228 9.989 2 3 33.81
2M10393463+3809488 11.616 11.051 10.794 2 3 13.86 6.10 0.60
2M10464238+1626144 11.497 10.835 10.617 3 3 SB2
2M10540048+1606059 11.606 11.077 10.731 3 3 23.93 0.05 10.10 0.80
2M11005043+1204108 10.676 10.117 9.782 3 3 10.07 0.13 26.50 0.80
2M11014478+1227162 10.986 10.425 10.162 3 3 27.14 0.13 11.60 0.80
2M11045698+1026411 9.368 8.712 8.492 3 3 8.45 0.15 4.70 2.10
2M11054316+1014093 8.643 8.049 7.797 3 3 56.59 0.16 5.50 2.20
2M110912250436249 8.201 7.595 7.330 1 3 10.23 6.30
2M11285879+5205580 11.225 10.612 10.332 2 3 7.41 2.90 0.50
2M11463262+0130524 12.240 11.673 11.382 4 12 28.35 0.17 3.50 2.80
2M11474074+0015201 8.991 8.399 8.098 4 12 7.02 0.32 5.60 1.40
2M11564308+1639541 11.164 10.610 10.332 2 3 30.36
2M11593840+1545481 11.423 10.784 10.504 2 3 18.61
2M12003311+1814555 12.010 11.398 11.139 9 6 4.40 0.42 7.20 2.90
2M12033893+1527533 11.222 10.631 10.372 2 3 11.23 5.90 0.10
2M12045611+1728119 9.793 9.183 8.967 2 3 SB2
2M12045619+1757409 11.568 11.014 10.710 9 6 2.36 0.22 4.30 3.10
2M12054224+1844354 12.209 11.576 11.386 9 6 20.96 0.18
2M12081374+1747306 12.433 11.925 11.654 9 6 15.11 0.25
2M12110614+1846153 11.117 10.545 10.281 9 6 20.61 0.26
2M12151947+0537224 12.324 11.767 11.454 1 3 29.78 5.20
2M12200119+2633419 12.294 11.736 11.471 5 6 8.66 0.49
2M12211284+0031320 12.063 11.509 11.281 9 12 21.77 0.21
2M12214665+0007205 11.842 11.255 10.969 9 12 6.06 0.13 8.40 1.40
2M12222073+0011020 11.788 11.273 11.018 9 12 31.09 0.20 9.60 0.50
2M12232063+2529441 10.827 10.234 9.985 5 6 12.01 0.08
2M12243585+0001106 12.011 11.477 11.220 9 12 28.38 0.22
2M12244171+1405391 11.560 10.947 10.724 3 3 2.55 0.31
2M12253159+0011354 11.649 11.105 10.805 9 12 20.96 0.36
2M12260407+2730369 12.303 11.791 11.552 6 6 2.89 0.29 8.60 1.20
2M12265737+2700536 10.197 9.607 9.320 6 6 2.13 0.52 13.50 0.60
2M13075012+1717471 12.327 11.742 11.486 16 12 11.27 0.25
2M13085059+1622039 9.264 8.655 8.413 16 12 17.48 0.21
2M13332256+3620352 9.650 8.986 8.778 1 3 23.02 19.60
2M13345147+3746195 9.713 9.146 8.887 1 3 3.77 10.90
2M13410096+2711449 12.482 11.850 11.598 18 24 19.25 0.24
2M13451104+2852012 9.882 9.311 9.054 18 24 11.41 0.18
2M13455527+2723131 10.652 10.076 9.787 18 24 43.14 0.18 6.40 0.80
2M13491436+2637457 11.325 10.768 10.548 18 24 9.47 0.13
2M13514938+4157445 9.894 9.272 9.024 2 3 4.06 8.10 0.60
2M13532938+4416109 11.712 11.136 10.872 2 3 6.42 3.80 1.60
2M13564148+4342587 11.709 11.043 10.650 2 3 16.79 18.80 0.40
2M14035430+3008026 11.299 10.655 10.388 6 6 39.48 0.26 7.60 1.00
2M14045651+2831023 12.299 11.716 11.445 6 6 SB1
2M142648270510400 7.470 7.160 7.060 5 6 32.44 0.14 3.20 1.00
2M14545704+3714558 10.423 9.769 9.531 1 3 27.76 5.10
2M14570070+3556471 9.758 9.089 8.890 1 3 34.76 3.00
2M14592508+3618321 10.257 9.647 9.377 1 3 19.31 9.70
2M151655760037116 9.960 9.382 9.105 1 3 12.40 11.60
2M151838420008235 9.342 8.645 8.499 1 3 9.94 54.50
2M15192613+0153284 12.133 11.610 11.329 10 12 SB2
2M16193140+5206469 11.438 10.913 10.687 1 3 58.22 5.70
2M16370146+3535456 11.135 10.545 10.240 7 12 2.18 0.15 7.00 1.80
2M16383835+3700273 11.367 10.798 10.498 7 12 14.59 0.17 8.30 1.50
2M16440030+3721597 11.918 11.334 11.066 7 12 0.66 0.12 6.80 0.40
2M16451798+3645405 12.450 11.839 11.596 7 12 76.21 0.31 8.30 1.20
2M16454410+3605496 10.569 10.039 9.801 7 12 9.12 0.05 5.30 1.20
2M16495034+4745402 9.457 8.840 8.625 12 12 35.63 0.15 6.70 0.90
2M16500047+4820372 12.509 11.921 11.624 12 12 12.34 0.20 13.00 1.20
2M17204248+4205070 9.895 9.286 9.000 13 12 SB2
2M17592886+0318233 9.474 8.830 8.633 3 3 12.26 0.13 11.00 4.60
2M18055545+0316213 11.398 10.771 10.565 3 3 14.06 0.31 6.30 1.50
2M182154160700179 9.626 8.909 8.726 2 3 16.91
2M182446890620311 9.659 9.052 8.795 2 3 20.96 9.20 1.20
2M18415473+0651285 9.921 9.336 9.050 2 3 72.71 6.50
2M18430881+0612150 12.175 11.813 11.688 2 3 20.47 5.40 0.20
2M18451027+0620158 7.656 7.043 6.806 2 3 24.48 7.10 0.20
2M18452147+0711584 12.244 11.581 11.149 2 3 46.19 16.10 0.10
2M18523373+4538317 10.493 9.937 9.673 3 2 31.01 0.15 5.80 0.30
2M18551497+4408590 12.172 11.596 11.302 3 2 10.90 0.27 4.90 2.70
2M18562628+4622532 9.598 9.010 8.717 3 2 2.51 0.04 5.30 3.90
2M19010098+4522386 11.539 10.902 10.639 3 2 27.86 0.08 5.30 0.80
2M19025183+4455465 10.058 10.017 10.016 3 2 SB1
2M19034513+4536301 8.213 8.056 8.067 3 2 0.85 0.05 4.20 0.60
2M19051739+4507161 9.850 9.300 9.027 3 2 48.22 0.23 2.40
2M19071270+4416070 10.447 9.855 9.559 2 2 21.27 7.10
2M19081153+2839105 10.581 9.973 9.719 7 12 30.57 0.14 22.70 0.90
2M19081576+2635054 10.361 9.762 9.471 7 12 3.84 0.12 2.80 0.20
2M19084251+2733453 9.750 9.233 8.951 7 12 5.35 0.09 5.70 0.20
2M19121128+4316106 11.156 10.631 10.430 2 2 110.63 8.30 3.30
2M19125504+4239370 10.315 9.731 9.543 2 2 32.70
2M19142151+4309008 12.384 11.880 11.545 2 2 77.36 9.50
2M19173151+2833147 10.758 10.194 9.923 7 12 15.33 0.12 13.20 0.50
2M19185898+3812236 11.876 11.222 11.024 3 3 25.56 0.10 8.20 2.10
2M19235494+3834587 12.534 12.087 11.973 3 3 SB2
2M19241533+3638089 11.556 10.927 10.721 3 3 11.40 0.16 11.40 0.50
2M19242742+2508341 12.386 11.789 11.545 3 12 40.36 0.49
2M19265550+3844381 12.360 11.710 11.521 3 3 15.88 0.31 12.10 2.50
2M19271763+3913024 11.742 11.060 10.941 3 3 23.24 0.18 19.60 0.10
2M19272650+4758468 11.913 11.328 11.023 1 2 23.33 6.50
2M19294258+3733223 11.282 10.736 10.444 3 3 22.57 0.15 10.20 0.20
2M19302029+3723437 11.939 11.310 11.109 3 3 23.06 0.35 13.50 0.40
2M19321796+4747027 11.519 10.936 10.633 1 2 6.61 10.20
2M19322564+3917266 11.570 11.008 10.737 3 6 28.64 0.02 5.60 0.70
2M19330692+4005066 11.563 10.944 10.741 3 6 20.10 0.07 9.00 0.10
2M19332454+4515045 10.600 9.992 9.747 1 2 5.82
2M19333940+3931372 8.120 7.560 7.339 3 6 SB2
2M19335290+3900545 11.948 11.393 11.131 3 6 24.52 0.04
2M19335405+3938497 12.334 11.760 11.513 3 6 46.05 0.10 5.70 1.10
2M19395886+3950530 9.798 9.186 8.951 3 6 18.45 0.47
2M19412016+3912129 10.675 10.097 9.848 3 6 49.72 0.06 4.60 1.70
2M19420033+4038302 11.655 11.011 10.813 3 6 45.15 0.23 11.00 0.30
2M19421037+4005402 12.313 11.791 11.543 3 6 76.57 0.06 7.40 1.70
2M19430726+4518089 11.331 10.752 10.380 1 2 2.05 7.30
2M19443810+4720294 11.814 11.281 11.002 3 2 2.53 0.26
2M19445931+4812415 12.557 11.937 11.735 3 2 13.92 0.27
2M19450035+3911539 12.515 11.966 11.711 3 6 10.33 0.45 4.40 2.40
2M19450736+3947341 12.595 12.070 11.977 3 6 52.11 0.34
2M19485718+5015245 11.184 10.606 10.389 2 2 3.24 4.50 2.20
2M19504779+4816290 11.390 10.880 10.662 3 2 75.92 0.10
2M19510930+4628598 8.586 8.045 7.773 3 2 11.38 0.19 19.00 0.40
2M19541829+1738289 10.516 9.993 9.719 1 3 40.84 8.60
2M19544358+1801581 12.210 11.517 11.113 1 3 16.08 17.00
2M19560585+2205242 10.069 9.443 9.228 1 12 8.62 12.80
2M19591845+2040515 12.407 11.873 11.640 1 12 33.51 5.80
2M20184736+1901539 11.501 10.913 10.712 4 12 35.46 0.19 5.10 0.90
2M20264615+5250183 12.550 11.966 11.720 2 12 18.72 6.00
2M20351108+5426045 11.956 11.389 11.170 2 12 2.87
2M21003448+5156016 11.196 10.659 10.405 1 12 3.51
2M21095447+4729043 11.487 10.900 10.633 4 24 37.49 0.21 10.10 0.40
2M21105881+4657325 9.878 9.263 9.051 4 24 6.87 0.39 5.40 0.80
2M21160502+4759308 12.483 11.812 11.418 3 24 12.69 0.57 21.10 1.30
2M21202943+4843460 11.798 11.149 10.960 4 24 51.35 0.26 9.10 0.70
2M21203355+4554475 12.574 11.999 11.779 2 12 1.70
2M21274776+4459041 11.585 11.011 10.780 2 12 18.59
2M21311504+1219444 10.777 10.210 9.952 10 24
2M21323014+4424296 12.300 11.705 11.472 2 12 53.77
2M21335234+1150104 11.935 11.351 11.083 12 24
2M21351561+4609365 12.110 11.553 11.352 2 12 65.02 5.90 0.30
2M21353562+0009334 12.462 11.796 11.548 3 3 12.33 0.04 6.90 1.20
2M21442066+4211363 11.537 10.898 10.664 2 12 SB2
2M21451241+4225454 10.936 10.328 10.085 2 12 59.84 27.30
2M22192066+5818280 12.164 11.658 11.361 3 3 7.31 0.22 8.90 0.60
2M22284859+5738281 12.336 11.725 11.449 3 3 13.10 0.07 8.10 2.90
2M22392577+5719249 8.308 7.614 7.517 3 3 0.04 0.20 19.50 0.20
2M23070962+4647099 10.257 9.699 9.450 1 3 6.04 9.30
2M23081274+4609340 11.783 11.233 10.956 1 3 19.42 12.70
2M23082543+4813393 11.098 10.425 10.163 1 3 33.77 17.20
2M23082777+4700410 10.776 10.227 10.004 1 3 46.80
2M23110137+4653414 11.090 10.494 10.214 1 3 48.14 6.40
2M23124910+4726557 7.498 7.192 7.127 1 3 3.15

Table 1Targets observed during the first year of the APOGEE M Dwarf Survey. The table includes infrared magnitudes, absolute RVs, projected rotational velocities and estimated errors on absolute RV and .
Star Alt. Name Standard Type Reference
02085359+4926565 GJ3136 vsini (a)
05030563+2122362 vsini (b)
05470907-0512106 GJ3366 vsini (c)
14264827-0510400 HD126614 RV (d)
19051739+4507161 LHS 3429 activity (e)
19121128+4316106 activity (e)
19125504+4239370 activity (e)
19185898+3812236 activity (f)
19235494+3834587 activity (f)
19241533+3638089 activity (f)
19265550+3844381 activity (f)
19271763+3913024 activity (f)
19294258+3733223 LHS6351 activity (e)
19302029+3723437 activity (f)
19330692+4005066 activity (f)
19332454+4515045 activity (e)
19333940+3931372 activity (e)
19395886+3950530 activity (f)
19420033+4038302 activity (f)
19445931+4812415 activity (f)
19450736+3947341 activity (f)
19485718+5015245 activity (e)
19510930+4628598 GJ 1243 vsini (b)
22392577+5719249 HIP 111854 RV (d)
23124910+4726557 LTT 16823 RV (d)

References. – (a) (Gizis et al., 2002); (b) (Nutzman & Charbonneau, 2008); (c) (Jenkins et al., 2009); (d)(Chubak et al., 2012); (e)Ciardi et al. (2011); (f)(Walkowicz et al., 2011)

Table 2Standard Stars Observed During the First Year of the APOGEE M Dwarf Survey.
4546
Star [M/H] [M/H] T log g T log g
(2MASS) (Model) (Observed) (K) (cgs) (K) (cgs)
00251602+5422547
04125880+5236421
13451104+2852012
19081153+2839105
Table 3M Dwarf Stellar Properties Derived from Model Fits
Star PA mag Instrument
(2MASS) (mas) (degrees) (Mag)
03305473+7041145 NIRC2
03425325+2326495 NIRC2
12122940+3940281 PHARO
Table 4M Dwarf Stellar Properties Derived from Model Fits

Footnotes

  1. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  2. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  3. affiliation: Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
  4. affiliation: Department of Astrophysical Sciences, Princeton University, Peyton Hall, Ivy Lane, Princeton, NJ 08544, USA
  5. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  6. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  7. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  8. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  9. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  10. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  11. affiliation: Department of Terrestrial Magnetism, Carnegie Institution of Washington, 5241 Broad Branch Road NW, Washington, DC 20015, USA
  12. affiliation: University of Virginia, 530 McCormick Road, Charlottesville, VA 22904
  13. affiliation: University of Notre Dame
  14. affiliation: Institut UTINAM, CNRS UMR 6213, Observatoire des Sciences de l’Univers THETA Franche-Comté-Bourgogne, Université de Franche Comté
  15. affiliation: Institut UTINAM, CNRS UMR 6213, Observatoire des Sciences de l’Univers THETA Franche-Comté-Bourgogne, Université de Franche Comté
  16. affiliation: Observatoire de Besançon, Institut Utinam, UMR 6213 CNRS, BP 1615,F-25010 Besançon Cedex, France
  17. affiliation: Observatoire de Besançon, Institut Utinam, UMR 6213 CNRS, BP 1615,F-25010 Besançon Cedex, France
  18. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  19. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  20. affiliation: Instituto de Astrofísica de Canarias, 38205 La Laguna, Tenerife, Spain
  21. affiliation: Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain
  22. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  23. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  24. affiliation: Center for Exoplanets and Habitable Worlds, The Pennsylvania State University, University Park, PA 16802
  25. affiliation: Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802
  26. affiliation: Department of Physics & Astronomy, Texas Christian University, TCU Box 298840, Fort Worth, TX 76129
  27. affiliation: Department of Astronomy, University of Florida, 211 Bryant Space Science Center, Gainesville, FL, 32611-2055, USA
  28. affiliation: University of Virginia, 530 McCormick Road, Charlottesville, VA 22904
  29. affiliation: Instituto de Astrofísica de Canarias, 38205 La Laguna, Tenerife, Spain
  30. affiliation: Departamento de Astrofísica, Universidad de La Laguna, 38206 La Laguna, Tenerife, Spain
  31. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  32. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  33. affiliation: University of Virginia, 530 McCormick Road, Charlottesville, VA 22904
  34. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  35. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  36. affiliation: Astrophysics Research Institute, Liverpool John Moores University, Wirral, CH41 1LD, UK
  37. affiliation: McDonald Observatory, The University of Texas at Austin, Austin, TX, 78712, USA
  38. affiliation: Apache Point Observatory, P.O. Box 59, Sunspot, NM 88349-0059, USA
  39. affiliation: Department of Physics and Astronomy, Vanderbilt University, Nashville, TN 37235, USA; Department of Physics, Fisk University, Nashville, TN, USA)
  40. affiliation: University of Virginia, 530 McCormick Road, Charlottesville, VA 22904
  41. affiliation: Astronomy Department, University of Washington, Box 351580, Seattle, WA 98195, USA
  42. affiliationtext: Department of Astronomy, University of Michigan, Ann Arbor, MI, 48109, USA
  43. One fiber hour is an hour long exposure of a single target.
  44. http://phoenix.ens-lyon.fr/Grids/BT-Settl/AGSS2009/
  45. footnotetext: Emperical low resolution ( 2000) H-band spectroscopic measurements.
  46. footnotetext: Automated APOGEE pipeline values.

References

  1. Allard, N. F., Kielkopf, J. F., Spiegelman, F., Tinetti, G., & Beaulieu, J. P. 2012, A&A, 543, A159
  2. Allard, F., Homeier, D., Freytag, B., ArXiv 1011.5405
  3. Allard, F., Hauschildt, P. H., Alexander, D. R., & Starrfield, S. 1997, ARA&A, 35, 137
  4. Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481
  5. Bailer-Jones, C. A. L. 2004, A&A, 419, 703
  6. Bean, J. L., Seifahrt, A., Hartman, H., et al. 2010, ApJ, 713, 410
  7. Bender, C. F., & Simon, M. 2008, ApJ, 689, 416
  8. Blake, C. H.,Charbonneau, D., & White, R. J. 2010, ApJ, 723, 68
  9. Blake, C. H., Charbonneau, D., White, R. J., Marley, M. S., & Saumon, D. 2007, ApJ, 666, 1198
  10. Blake, C. H., & Shaw, M. M. 2011, PASP, 123, 1302
  11. Browning, M. K., Basri, G., Marcy, G. W., West, A. A., & Zhang, J. 2010, AJ, 139, 504
  12. Browning, M. K. 2008, ApJ, 676, 1262
  13. Bonfils, X., Delfosse, X., Udry, S., et al. 2013, A&A, 549, A109
  14. Bouchez, Antonin H., Dekany, Richard G., Angione, John R., et al. 2009, SPIE Conference Series
  15. Bowler, B. P., Liu, M. C., Shkolnik, E. L., & Tamura, M. 2012, ApJ, 756, 69
  16. Butler, R.P. & Marcy, G.W. 1996, PASP, 108, 500
  17. Caffau, E., Ludwig, H.-G., Steffen, M., Freytag, B., & Bonifacio, P. 2011, Sol. Phys., 268, 255
  18. Chabrier, G., Gallardo, J., & Baraffe, I. 2007, A&A, 472, L17
  19. Chubak, C., Marcy, G., Fischer, D.A., Howard, A.W., Isaacson, H., Johnson, J.A., & Wright, J.T. 2012, ArXiv 1207.6212
  20. Ciardi, D. R., von Braun, K., Bryden, G., et al. 2011, AJ, 141, 108
  21. Claret, A., Hauschildt, P. H., & Witte, S. 2012, A&A, 546, A14
  22. Claret, A. 2000, A&A, 363, 1081
  23. Crepp, J. R., Johnson, J. A., Howard, A. W., et al. 2012, ApJ, 761, 39
  24. Crepp, J. R., Johnson, J. A., Fischer, D. A., et al. 2012, ApJ, 751, 97
  25. Delfosse, X., Beuzit, J.-L., Marchal, L., et al. 2004, Spectroscopically and Spatially Resolving the Components of the Close Binary Stars, 318, 166
  26. X. Delfosse, X., Bonfils, T. Forveille, et al. 2012, ArXiv 1202.2467
  27. Deshpande, R., Martín, E. L., Montgomery, M. M., et al. 2012, AJ, 144, 99
  28. Dressing, C. D., & Charbonneau, D. 2013, ApJ, 767, 95
  29. Duquennoy, A., & Mayor, M. 1991, A&A, 248, 485
  30. Esposito, S., Pinna, E., Quirós-Pacheco, F., et al. 2012, Proc. SPIE, 8447
  31. Eisenstein, D. J., Weinberg, D. H., Agol, E., et al. 2011, AJ, 142, 72
  32. Endl, M., Cochran, W. D., Kürster, M., et al. 2006, ApJ, 649, 436
  33. Endl, M., Cochran, W. D., Tull, R. G., & MacQueen, P. J. 2003, AJ, 126, 3099
  34. Feiden, G. A., & Chaboyer, B. 2012, ApJ, 757, 42
  35. Figueira, P., Pepe, F., Melo, C. H. F., et al., 2010, A&A, 511, A55
  36. Fischer, D. A., & Marcy, G. W. 1992, ApJ, 396, 178
  37. Freytag, B., Allard, F., Ludwig, H.-G., Homeier, D., & Steffen, M. 2010, A&A, 513, A19
  38. Gizis, J. E., Reid, I. N., & Hawley, S. L. 2002, AJ, 123, 3356
  39. Gray, D. F. 1992, The observation and analysis of stellar photospheres, ed. 2 (Cambridge: Cambridge University Press)
  40. Grether, D., & Lineweaver, C. H. 2006, ApJ, 640, 1051
  41. Gomes da Silva, J., Santos, N. C., Bonfils, X., et al. 2012, A&A, 541, A9
  42. Gunn, J. E., Siegmund, W. A., Mannery, E. J., et al. 2006, AJ, 131, 2332
  43. Hayward, T. L., Brandl, B., Pirger, B., et al. 2001, PASP, 113, 105
  44. Homeier, N. L., Blum, R. D., Pasquali, A., Conti, P. S., & Damineli, A. 2003, A&A, 408, 153
  45. Howard, A. W., Johnson, J. A., Marcy, G. W., et al. 2010, ApJ, 721, 1467
  46. Howell, S. B., Rowe, J. F., Bryson, S. T., et al. 2012, ApJ, 746, 123
  47. Jenkins, J. S., Ramsey, L. W., Jones, H. R. A., et al. 2009, ApJ, 704, 975
  48. Jódar, E., Pérez-Garrido, A., Díaz-Sánchez, A., et al. 2013, MNRAS, 429, 859
  49. Kane, S. R., Henry, G. W., Dragomir, D., et al. 2011, ApJ, 735, L41
  50. Kaüfl et al. 2004, SPIE 5492, 1218
  51. Kirkpatrick, J. D., Reid, I. N., Liebert, J., et al. 1999, ApJ, 519, 802
  52. Kopparapu, R. K. 2013, ApJ, 767, L8
  53. Lafrenière, D., Doyon, R., Marois, C., et al. 2007, ApJ, 670, 1367
  54. Lada, C. J. 2006, ApJ, 640, L63
  55. Latham, D. W., Stefanik, R. P., Mazeh, T., Mayor, M., & Burki, G. 1989, Nature, 339, 38
  56. Lépine, S., & Gaidos, E. 2011, AJ, 142, 138
  57. Lépine, S., & Shara, M. M. 2005, AJ, 129, 1483
  58. Ludwig, H.-G., Allard, F., & Hauschildt, P. H. 2006, A&A, 459, 599
  59. Mahadevan, S., Ramsey, L., Bender, C., et al. 2012, arXiv:1209.1686
  60. Majewski, S. R., Wilson, J. C., Hearty, F., Schiavon, R. R., & Skrutskie, M. F. 2010, IAU Symposium, 265, 480
  61. Marcy, G. W., & Butler, R. P. 2000, PASP, 112, 137
  62. Marcy, G. W., Cochran, W. D., & Mayor, M. 2000, Protostars and Planets IV, 1285
  63. Marois, C., Lafrenière, D., Macintosh, B., & Doyon, R. 2006, ApJ, 647, 612
  64. Marchal, L., Delfosse, X., Forveille, T., et al. 2003, Brown Dwarfs, 211, 311
  65. Mayor, M. et al. 2003, The Messenger 114, 20
  66. Mermilliod, J.-C., Grenon, M., & Mayor, M. 2008, A&A, 491, 951
  67. Metchev, S. A., & Hillenbrand, L. A. 2009, ApJS, 181, 62
  68. McLean, I., Becklin, E. E., Bendiksen, O., et al. 1998, Proc. SPIE, 3354, 566
  69. McQuillan, A., Aigrain, S., & Mazeh, T. 2013, MNRAS, 1203
  70. Metchev, S. A., & Hillenbrand, L. A. 2009, ApJS, 181, 62
  71. Montet, B. T., Crepp, J. R., Johnson, J. A., Howard, A. W., & Marcy, G. W. 2013, arXiv:1307.5849
  72. Montet, B. T., & Johnson, J. A. 2013, ApJ, 762, 112
  73. Morin, J., Donati, J.-F., Petit, P., et al. 2008, MNRAS, 390, 567
  74. Neves, V., Bonfils, X., Santos, N. C., et al. 2013, A&A, 551, A36
  75. Nutzman, P., & Charbonneau, D. 2008, PASP, 120, 317
  76. ]Nelder, J.A., Mead, R., 1965. Computer Journal 7,308
  77. Noyes, R. W. 1984, Advances in Space Research, 4, 151
  78. Prandtl, L.,1926, Proc. second int. Congr. appl. Mech.
  79. Quirrenbach, A.,Amado, P. J., Mandel, H., et al. 2010, Proc. SPIE, 7735,
  80. Rajpurohit, A. S., Reylé, C., Schultheis, M., et al. 2012, A&A, 545, A85
  81. Raghavan, D., McAlister, H. A., Henry, T. J., et al. 2010, ApJS, 190, 1
  82. Randich, S., Schmitt, J. H. M. M., & Prosser, C. 1996, A&A, 313, 815
  83. Rayner, J. T., Toomey, D. W., Onaka, P. M., et al. 2003, PASP, 115, 362
  84. Redman, S. L., Ycas, G. G., Terrien, R., et al. 2012, ApJS, 199, 2
  85. Redman, S. L., Lawler, J. E., Nave, G., Ramsey, L. W., & Mahadevan, S. 2011, ApJS, 195, 24
  86. Reid, I. N., Gizis, J. E.,& Hawley, S. L. 2002, AJ, 124, 2721
  87. Reiners, A., Joshi, N., & Goldman, B. 2012, AJ, 143, 93
  88. Reiners, A., Bean, J. L., Huber, K. F., et al. 2010, ApJ, 710, 432
  89. Reiners, A., & Basri, G. 2008, ApJ, 684, 1390
  90. Reiners, A., & Basri, G. 2009, ApJ, 705, 1416
  91. Reiners, A., & Basri, G. 2010, ApJ, 710, 924
  92. Rodigas, T. J., Males, J. R., Hinz, P. M., Mamajek, E. E., & Knox, R. P. 2011, ApJ, 732, 10
  93. Rodler, F., Deshpande, R., Zapatero Osorio, M. R., et al., 2012, A&A, 538, A141
  94. Rojas-Ayala, B., Covey, K. R., Muirhead, P. S., & Lloyd, J. P. 2012, ApJ, 748, 93
  95. Rojas-Ayala, B., Covey, K. R., Muirhead, P. S., & Lloyd, J. P. 2010, ApJ, 720, L113
  96. Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163
  97. Southworth, J., Pavlovski, K., Tamajo, E., et al. 2011, MNRAS, 414, 3740
  98. Terrien, R. C., Fleming, S. W., Mahadevan, S., et al. 2012, ApJ, 760, L9
  99. Terrien, R. C., Mahadevan, S., Bender, C. F., et al. 2012, ApJ, 747, L38
  100. Tonry, J., & Davis, M. 1979, AJ, 84, 1511
  101. Torres, G., Clausen, J. V., Bruntt, H., et al. 2012, A&A, 537, A117
  102. Udry, S., Bonfils, X., Delfosse, X., et al. 2007, A&A, 469, L43
  103. Torres, G. 2012, arXiv:1209.1279
  104. Unsöld, A. 1968,QJRAS, 9, 294
  105. Valenti, J. A., & Piskunov, N. 1996, A&AS, 118, 595
  106. van Eyken, J. C., Ciardi, D. R., von Braun, K., et al. 2012, ApJ, 755, 42
  107. Walkowicz, L. M., Basri, G., Batalha, N., et al. 2011, AJ, 141, 50
  108. Wang, J., & Ge, J. 2011, arXiv:1107.4720
  109. Wilson, J. C., Hearty, F., Skrutskie, M. F., et al. 2012, Proc. SPIE, 8446
  110. Wilson, J.C. et al. 2010. Proc. SPIE, 7735, 77351C-1
  111. Wizinowich, P., Acton, D. S., Shelton, C., et al. 2000, PASP, 112, 315
Comments 0
Request Comment
You are adding the first comment!
How to quickly get a good reply:
  • Give credit where it’s due by listing out the positive aspects of a paper before getting into which changes should be made.
  • Be specific in your critique, and provide supporting evidence with appropriate references to substantiate general statements.
  • Your comment should inspire ideas to flow and help the author improves the paper.

The better we are at sharing our knowledge with each other, the faster we move forward.
""
The feedback must be of minimum 40 characters and the title a minimum of 5 characters
   
Add comment
Cancel
Loading ...
64073
This is a comment super asjknd jkasnjk adsnkj
Upvote
Downvote
""
The feedback must be of minumum 40 characters
The feedback must be of minumum 40 characters
Submit
Cancel

You are asking your first question!
How to quickly get a good answer:
  • Keep your question short and to the point
  • Check for grammar or spelling errors.
  • Phrase it like a question
Test
Test description