The GALAH Survey: Observational Overview and Gaia DR1 companion
Sarah Martell, Sanjib Sharma, Sven Buder, Ly Duong, Katharine Schlesinger, Jeffrey Simpson, Karin Lind, Melissa Ness, Jonathan Marshall, Martin Asplund, Joss Bland-Hawthorn, Andrew Casey, Gayandhi De Silva, Ken Freeman, Janez Kos, Jane Lin, Daniel Zucker, Tomaz Zwitter, Borja Anguiano, Carlos Bacigalupo, Daniela Carollo, Luca Casagrande, Gary Da Costa, Jonathan Horner, Daniel Huber, Elaina Hyde, Prajwal Kafle, Geraint Lewis, David Nataf, Dennis Stello, Chris Tinney, Fred Watson, Rob Wittenmyer
MMNRAS , ?? – ?? (2016) Preprint 13 September 2016 Compiled using MNRAS L A TEX style file v3.0
The GALAH Survey: Observational Overview and
Gaia
DR1 companion
S. L. Martell (cid:63) , S. Sharma , S. Buder , L. Duong , K. J. Schlesinger ,J. Simpson , K. Lind , , M. Ness , J. P. Marshall , , M. Asplund ,J. Bland-Hawthorn , A. R. Casey , G. De Silva , , K. C. Freeman , J. Kos ,J. Lin , D. B. Zucker , , , T. Zwitter , B. Anguiano , , C. Bacigalupo , ,D. Carollo , L. Casagrande , G. S. Da Costa , J. Horner , , D. Huber ,E. A. Hyde , , P. R. Kafle , G. F. Lewis , D. Nataf , D. Stello ,C. G. Tinney , , F. G. Watson , R. Wittenmyer , , School of Physics, University of New South Wales, Sydney NSW 2052, Australia Sydney Institute for Astronomy, School of Physics, A28, The University of Sydney, Sydney NSW 2006, Australia Max-Planck-Institut f¨ur Astronomie, K¨onigstuhl 17, 69117 Heidelberg, Germany Research School of Astronomy & Astrophysics, Australian National University, Canberra ACT 2611, Australia Australian Astronomical Observatory, North Ryde NSW 2113, Australia Department of Physics and Astronomy, Uppsala University, Box 516, SE-751 20 Uppsala, Sweden Australian Centre for Astrobiology, University of New South Wales, Sydney NSW 2052, Australia Institute of Astronomy, University of Cambridge, Cambridge, CB3 0HA, UK Department of Physics and Astronomy, Macquarie University, Sydney NSW 2109, Australia Research Centre in Astronomy, Astrophysics and Astrophotonics, Macquarie University, Sydney NSW 2109, Australia Faculty of Mathematics and Physics, University of Ljubljana, Jadranska 19, 1000 Ljubljana, Slovenia Department of Physics and JINA Center for the Evolution of the Elements, University of Notre Dame, Notre Dame, IN 46556, USA Computational Engineering and Science Research Centre, University of Southern Queensland, Towoomba QLD 4350, Australia Western Sydney University, Locked Bag 1797, Penrith South DC, NSW 1797, Australia International Centre for Radio Astronomy Research,The University of Western Australia, WA 6009, Australia
Accepted; Received
ABSTRACT
The Galactic Archaeology with HERMES (GALAH) Survey is a massive ob-servational project to trace the Milky Way’s history of star formation, chem- c (cid:13) a r X i v : . [ a s t r o - ph . I M ] S e p S. L. Martell et al. ical enrichment, stellar migration and minor mergers. Using high-resolution(R (cid:39) eff ,log(g), [Fe/H], [ α /Fe]), radial velocity, distance modulus and reddening for10680 observations of 9860 Tycho-2 stars that may be included in the first
Gaia data release.
Key words: stars: abundances – Galaxy: disc – Galaxy: formation – Galaxy:evolution – Galaxy: stellar content
Massive observational surveys are an increasingly important force in astronomy. In particu-lar, spectroscopic stellar surveys are revolutionising our understanding of Galactic structureand evolution (e.g., Helmi 2008; Rix & Bovy 2013; Hayden et al. 2014; Hayden et al. 2015;Martig et al. 2016). As in many areas of astronomical research, this development is drivenby technology. Efficient methods for accurately positioning many optical fibres at telescopefocal planes are enabling an increasing number of observatories to add highly multiplexedhigh-resolution spectrographs to their instrument suites (e.g., Cui et al. 2012; Sugai et al.2015).The Galactic Archaeology with HERMES (GALAH) Survey is a high-resolution spec-troscopic survey that is exploring the chemical and dynamical history of the Milky Way, withparticular focus on the disk. GALAH aims to collect a comprehensive data set, in terms ofboth sample size and detail, with abundances for as many as 29 elements (Li, C, O, Na, Mg, (cid:63) email: [email protected] http://galah-survey.org MNRAS , ?? – ?? (2016) ALAH Observational Overview stars can expect toobserve 10 stars per group down to an initial mass limit of ∼ M (cid:12) , while a survey of 10 stars would capture 10 stars per group down to a group mass of ∼ M (cid:12) . Ting et al. (2016)took data for 13,000 stars from the Apache Point Observatory Galaxy Evolution Experiment(APOGEE; Majewski et al. 2015; Holtzman et al. 2015) Survey from the twelfth data releaseof the Sloan Digital Sky Survey (DR12, Alam et al. 2015). By analysing the “clumpiness”of the chemical abundance data rather than carrying out strict chemical tagging, they wereable to rule out the presence of an initial star-forming group in the thick disk with a massgreater than 10 M (cid:12) .Our observational program must therefore collect enough stars from each initial star-forming group, and derive precise enough stellar parameters and elemental abundances, toconfidently apply chemical tags to them. Since the observing time for GALAH is allocatedthrough the competitive time allocation process of the 3.9m Anglo-Australian Telescope(AAT), our observing strategy must provide this large, high-quality sample in a reasonableamount of observing time. This paper describes the balance between sample size, signal-to-noise ratio (SNR) and observing time that has been designed into our observational program.Section 2 outlines the capabilities of the HERMES spectrograph and Two Degree Field(2dF) fibre positioner, Section 3 discusses our target selection for the main survey, Section 4 MNRAS , ?? – ????
Massive observational surveys are an increasingly important force in astronomy. In particu-lar, spectroscopic stellar surveys are revolutionising our understanding of Galactic structureand evolution (e.g., Helmi 2008; Rix & Bovy 2013; Hayden et al. 2014; Hayden et al. 2015;Martig et al. 2016). As in many areas of astronomical research, this development is drivenby technology. Efficient methods for accurately positioning many optical fibres at telescopefocal planes are enabling an increasing number of observatories to add highly multiplexedhigh-resolution spectrographs to their instrument suites (e.g., Cui et al. 2012; Sugai et al.2015).The Galactic Archaeology with HERMES (GALAH) Survey is a high-resolution spec-troscopic survey that is exploring the chemical and dynamical history of the Milky Way, withparticular focus on the disk. GALAH aims to collect a comprehensive data set, in terms ofboth sample size and detail, with abundances for as many as 29 elements (Li, C, O, Na, Mg, (cid:63) email: [email protected] http://galah-survey.org MNRAS , ?? – ?? (2016) ALAH Observational Overview stars can expect toobserve 10 stars per group down to an initial mass limit of ∼ M (cid:12) , while a survey of 10 stars would capture 10 stars per group down to a group mass of ∼ M (cid:12) . Ting et al. (2016)took data for 13,000 stars from the Apache Point Observatory Galaxy Evolution Experiment(APOGEE; Majewski et al. 2015; Holtzman et al. 2015) Survey from the twelfth data releaseof the Sloan Digital Sky Survey (DR12, Alam et al. 2015). By analysing the “clumpiness”of the chemical abundance data rather than carrying out strict chemical tagging, they wereable to rule out the presence of an initial star-forming group in the thick disk with a massgreater than 10 M (cid:12) .Our observational program must therefore collect enough stars from each initial star-forming group, and derive precise enough stellar parameters and elemental abundances, toconfidently apply chemical tags to them. Since the observing time for GALAH is allocatedthrough the competitive time allocation process of the 3.9m Anglo-Australian Telescope(AAT), our observing strategy must provide this large, high-quality sample in a reasonableamount of observing time. This paper describes the balance between sample size, signal-to-noise ratio (SNR) and observing time that has been designed into our observational program.Section 2 outlines the capabilities of the HERMES spectrograph and Two Degree Field(2dF) fibre positioner, Section 3 discusses our target selection for the main survey, Section 4 MNRAS , ?? – ???? (2016) S. L. Martell et al. describes the observing procedure, Section 5 discusses the Pilot Survey, Section 6 describesthe K2-HERMES program, Section 7 presents observing progress through January 2016 (theend of AAT observing semester 15B), Section 8 discusses our potential synergies with otherlarge Galactic survey programs, and Section 9 presents the GALAH-TGAS catalogue. Theoverlap between GALAH and
Gaia is an extremely important data set. GALAH stars areall in the magnitude range (12 (cid:54) V (cid:54)
14) for which
Gaia parallaxes and proper motionswill be at their best and most complete. Ultimately GALAH will be able to contributeelemental abundances for a large number of stars with high-precision
Gaia data, forming avery powerful resource for studying Galactic chemodynamics.
The GALAH survey collects all of its data with the HERMES spectrograph at the AAT.While HERMES is an AAT facility instrument, it was specifically designed to undertakea large Galactic archaeology survey (Freeman 2012). The instrumental requirements forefficiency, wavelength range and spectral resolution were therefore focused on producingspectra rich in information about stellar parameters and chemical abundances, across awide range of stellar effective temperature, surface gravity and overall metallicity. Details ofHERMES design and integration can be found in Barden et al. (2010), Brzeski et al. (2011),Heijmans et al. (2012) and Farrell et al. (2014), and the as-built performance is discussedin Sheinis et al. (2015).HERMES has four non-contiguous optical bandpasses covering a total of ∼ R ∼ , MNRAS , ?? – ?? (2016) ALAH Observational Overview Table 1.
HERMES bandpassesChannel Wavelength range (˚A)Blue 4713 − − − − Light is directed into HERMES from the 2dF fibre positioner (Lewis et al. 2002), whichcan place 400 magnetic “buttons” carrying optical fibres across a circular field of view with adiameter of two degrees. It has two field plates with independent fibres, allowing one plate tobe configured while the other is being used to observe. Eight of the buttons carry small fibrebundles that are used to maintain field alignment and telescope guiding, and the remaining392 are single fibres that can be allocated to science targets and sky subtraction apertures.Twenty-five fibres are used as sky apertures, and a further 5-10 are typically unavailable forvarious engineering reasons. As a result, observed GALAH fields usually deliver spectra foraround 360 science targets.2dF is installed at the AAT prime focus, and the fibres run from the telescope top endto the HERMES enclosure on a lower floor of the AAT dome. The fibres are arranged ina pseudoslit at the spectrograph entrance, resulting in spectra on the detector with verysimilar wavelength range and dispersion. Figure 1 shows a zoomed-in region of typical rawdata from the red channel: a 20-minute exposure in GALAH survey field 2235, observed on9 August 2014. The dispersion direction is horizontal, and the fibres are separated vertically.The point spread function (PSF) in HERMES varies across the spatial and spectraldirections in all four cameras, with the smallest and most symmetric PSF in the centreof the detector and both ellipticity and tilt increasing toward the edges. This produces asmall amount of crosstalk between spectra that are adjacent on the detector, which can beremoved in data reduction (Kos et al. 2016). In each wavelength channel, HERMES returnsspectra with a SNR of 100 per resolution element in one hour of exposure time in median(1 . (cid:48)(cid:48)
5) seeing, for stars with a magnitude near 14 in the corresponding filter (the exact limitsare B = 14 . V = 13 . R = 14 . I = 13 . ∼ MNRAS , ?? – ????
5) seeing, for stars with a magnitude near 14 in the corresponding filter (the exact limitsare B = 14 . V = 13 . R = 14 . I = 13 . ∼ MNRAS , ?? – ???? (2016) S. L. Martell et al.
Figure 1.
A portion of a raw HERMES data frame from the red camera. The strong absorption feature near the centre of theimage is H α . The random scatter of anomalous pixels is due to unwanted charged particle hits. atically higher throughput from targets on the northern half of both field plates, randomlydistributed saturated points associated with long vertical readout streaks in three of the fourcameras, and an inability to bring the red camera (which covers 6478-6757˚A) entirely intofocus. The North-South asymmetry in throughput, and smaller-scale throughput variationsbetween fibres, are described in detail in Simpson et al. (2016). It is not immediately clearwhat drives the North-South asymmetry, though it does not appear to be an issue in thefibres themselves.The vertical streaks are present in the blue, green and red cameras, but more common inthe blue and green. They are believed to be caused by high-energy particles striking the de-tectors and freeing enough electrons to saturate a small number of pixels. These electrons aretrapped low enough in the silicon layer that reading out the detector only partially flushesthem out, so that the saturated pixels spawn a perfectly vertical feature that fades over thecourse of several exposures. The first time a given streak appears it runs away from the read-out amplifier, and in all subsequent images it runs toward the readout amplifier. Laboratorytesting by the Instrumentation group at the Australian Astronomical Observatory (AAO)has demonstrated that the high index-of-refraction glass in each camera’s field flatteninglens is likely to be the particle source. Most of the pixels affected by vertical streaks can MNRAS , ?? – ?? (2016) ALAH Observational Overview S/N . . . . . . C u m u l a t i v e f r a c t i on Figure 2.
Cumulative histograms of SNR per resolution element for the example data set, with the four HERMES channelsdrawn in different colours and line styles as described in the text. be handled by the ordinary cosmic ray removal techniques employed in the GALAH datareduction process (Kos et al. 2016).In all four cameras, focus is achieved by adjusting the detector using actuators that movepiston and tip the wavelength (“spectral”) axis. The perpendicular (“spatial”) axis was setduring HERMES installation and commissioning, and is not movable through instrumentsoftware control. During HERMES downtime in June 2014, the detector in the red camerawas tipped noticeably on its spatial axis, and engineering intervention was required. Thespatial axis was returned to its original alignment and the piston was returned to its previousrange. However, the new range of motion for the spectral axis was offset from the originalrange, and as a result it was no longer possible the actuators to move it sufficiently far tobring the red camera fully into focus. This issue was resolved on 10 August 2016 by AAOengineering staff, and the red camera can now be brought into focus as well as it could beforeJune 2014.While HERMES does return spectra with SNR of 100 per resolution element in eachcamera for stars with apparent magnitudes near 14 in the appropriate Johnson-Cousins filter(as described above), only A-type stars, which are rare in the GALAH data set, have coloursof zero and could have apparent magnitudes of 14.0 in B , V , R and I simultaneously. GALAHtargets are selected based on a V magnitude calculated from 2MASS J and K (as describedin Section 3 below), and so we use the mean SNR per resolution element in the green channelspectrum as our figure of merit. As a result, the SNR for each star in each HERMES channelwill be a function of its spectral energy distribution. Recent work within our team (Ting et al. MNRAS , ?? – ????
Cumulative histograms of SNR per resolution element for the example data set, with the four HERMES channelsdrawn in different colours and line styles as described in the text. be handled by the ordinary cosmic ray removal techniques employed in the GALAH datareduction process (Kos et al. 2016).In all four cameras, focus is achieved by adjusting the detector using actuators that movepiston and tip the wavelength (“spectral”) axis. The perpendicular (“spatial”) axis was setduring HERMES installation and commissioning, and is not movable through instrumentsoftware control. During HERMES downtime in June 2014, the detector in the red camerawas tipped noticeably on its spatial axis, and engineering intervention was required. Thespatial axis was returned to its original alignment and the piston was returned to its previousrange. However, the new range of motion for the spectral axis was offset from the originalrange, and as a result it was no longer possible the actuators to move it sufficiently far tobring the red camera fully into focus. This issue was resolved on 10 August 2016 by AAOengineering staff, and the red camera can now be brought into focus as well as it could beforeJune 2014.While HERMES does return spectra with SNR of 100 per resolution element in eachcamera for stars with apparent magnitudes near 14 in the appropriate Johnson-Cousins filter(as described above), only A-type stars, which are rare in the GALAH data set, have coloursof zero and could have apparent magnitudes of 14.0 in B , V , R and I simultaneously. GALAHtargets are selected based on a V magnitude calculated from 2MASS J and K (as describedin Section 3 below), and so we use the mean SNR per resolution element in the green channelspectrum as our figure of merit. As a result, the SNR for each star in each HERMES channelwill be a function of its spectral energy distribution. Recent work within our team (Ting et al. MNRAS , ?? – ???? (2016) S. L. Martell et al.
Figure 3.
Apparent ( B − V ) , V colour-magnitude diagram for the example data set, binned into hexagons and colour-codedby mean green channel signal-to-noise ratio per resolution element in each bin (left panel) and mean E ( B − V ) reddening ineach bin (right panel). >
100 per resolution element), the solid green line the green channel (59%),the dashed red line the red channel (82%) and the dotted black line the IR channel (75%).In this “example data set” there are far more red stars than blue stars, and this will also betrue of the full GALAH Survey. Therefore the SNR in the blue channel spectra will typicallybe lower than in the other three, while the SNR in the red and IR channel spectra aretypically similar to each other and higher than in the green channel.Figure 3 shows the apparent (non-dereddened) Johnson-Cousins ( B − V ) , V colour-magnitude diagram for the example data set. These data have been binned into hexagonsand colour-coded by mean green channel SNR in the bin (left panel) and by mean E ( B − V )reddening in the bin (right panel). Reddening is derived for each star as described in Section9 below. There are three clear effects to be seen in this figure: first, that redder stars have ahigher SNR at a fixed V magnitude; second, that some of the redder stars are simply more MNRAS , ?? – ?? (2016) ALAH Observational Overview Figure 4.
Signal to noise ratio per resolution element for all four HERMES channels versus apparent V magnitude for theexample data set, colour-coded by ( B − V ) colour. Bluer stars have higher blue channel SNR, but their SNR drops relative tothe redder stars in the redder channels. reddened rather than intrinsically redder; and finally, that the calculated V JK magnitude weused for target selection does not always translate directly into the true Johnson-Cousins V magnitude, but is moderated by stellar colour and by reddening. Intrinsically bluer starsmust have brighter apparent V magnitudes to be observed by GALAH than intrinsicallyredder stars. Figure 4 reinforces this point, showing SNR per resolution element in eachHERMES camera in turn versus V magnitude, colour-coded by ( B − V ) colour. In the bluechannel, the bluest stars have the highest SNR, but the SNR for these stars is clearly lowerrelative to the redder stars in the other three channels. The GALAH input catalogue is the union of the 2MASS (Skrutskie et al. 2006), APASS(Munari et al. 2014) and UCAC4 (Zacharias et al. 2013) catalogues, with selections forphotometric quality and crowding. Because APASS photometry was not available for all ofour stars at the start of GALAH observing, we calculate a V magnitude from 2MASS J and K as follows: V JK = K + 2( J − K + 0 .
14) + 0 . e (( J − K − . / . . All stars with apparent V JK magnitude brighter than 14 and Galactic latitude larger than five degrees are included MNRAS , ?? – ????
14) + 0 . e (( J − K − . / . . All stars with apparent V JK magnitude brighter than 14 and Galactic latitude larger than five degrees are included MNRAS , ?? – ???? (2016) S. L. Martell et al. in the input catalogue, provided that they have appropriate 2MASS quality flags (Q=“A”,B=“1”, C=“0”, X=“0”, A=“0”, prox (cid:62) (cid:48)(cid:48) ) and no brighter neighbours within a radius of V neighbour = (130 − (10 × V neighbour )) arcseconds. This returns 5 .
99 million stars.To choose target stars from the input catalogue, we make no selection on colour orreddening, preferring a simple selection function that can be straightforwardly inverted toallow interpretation through Galactic models (e.g., Sharma et al. 2014). However, we domake some selections in support of survey science goals: declination, δ , is limited to − <δ < +10 degrees, to maintain an airmass below 1.6 in all observations; Galactic latitude, b,is restricted to | b | > ◦ , to avoid significant and variable extinction closer to the plane;and the density of targets with 12 (cid:54) V JK (cid:54)
14 must be at least 400 per π square degrees, toensure efficient observations with 2dF.This more restricted set of 3 .
69 million targets is then divided into 6545 fixed “configura-tions” of 400 stars each, to allow efficient use of the 2dF fibre positioner. These configurationsuse the full two-degree-diameter field of view in lower-density regions, and are more compactin denser regions, to allow a more efficient tiling. In particularly dense regions, multiple con-figurations can share a single field centre. The tiling strategy will be discussed in more depthin Sharma et al. (in prep). This survey sample is strongly focused on the thin and thick disk.Using the
Galaxia software (Sharma et al. 2011), which simulates synthetic observation ofthe Milky Way using a Besan¸con model (Robin et al. 2003) and Padova isochrones (Bertelliet al. 1994; Marigo et al. 2008), we predict that 75% of these stars belong to the thin disk,24% to the thick disk, 0 .
9% to the bulge and 0 .
1% to the halo.Although we do not make any colour selections for survey science targets, we anticipatethat our spectroscopic analysis will be most accurate and successful for stars with effectivetemperature between 4000K and 7000K. Stellar parameters and abundances will be moredifficult to determine for stars outside that range: in hot stars, because of a lack of Fe and Tilines in the HERMES wavelength ranges, and in cool stars, because of an overabundance ofmolecular features. We anticipate that the ongoing development of model atmospheres forcool stars (e.g., Allard 2014) will allow us to analyse those targets in the future. The lackof colour selection will also result a small minority of stars that are observed being found atextreme points of evolution for which our analyses will not work at all, e.g., T Tauri starsand white dwarfs. , ?? – ?? (2016) ALAH Observational Overview As described above, HERMES meets the design requirement for a SNR of 100 per resolutionelement when observing a target with V JK = 14 for one hour in median seeing. This setsthe basic unit of GALAH survey observing at one hour of integration time per field, withsome adjustments as required depending on the observing conditions. The nominal GALAHobserving procedure is to take three 20-minute exposures for each configuration, with anadditional 20 minutes if the seeing is between 2 (cid:48)(cid:48) and 2 . (cid:48)(cid:48) . (cid:48)(cid:48) (cid:48)(cid:48) . We find that these adjustments to the exposure timeare typically sufficient to raise the SNR to the required level (as discussed in Sheinis et al.2015). Typical overhead is 25% of the on-target observing time for the standard 3 ×
20 minuteexposures. We spend 180 seconds each for flat-field and ThXe arc exposures (taken directlybefore or after the science data), 71 seconds per readout, and two to five minutes to slewthe telescope, tumble the 2dF top end so that the other field plate is available for observing,and acquire the next science field. It takes ∼
40 minutes to configure a full 2dF plate, whichmakes the total observation block time of ∼
60 minutes well-suited to this efficient observingstrategy, ensuring no observing time is lost due to plate reconfiguration.There are a few special requirements for GALAH survey observing. To minimise theeffects of chromatic variation and distortion in the 2dF corrector optics (Cannon et al.2008), the change in airmass during a nominal 60-minute GALAH observation will ideallybe less than 0 .
05. Because of the range of declination for GALAH targets, this translatesinto a strong preference that GALAH fields always be observed within 1 . < V JK <
12 are used as “fiducial” stars for field alignment and guidingduring normal survey observations. We have developed software to select configurations forsurvey observations, and to keep track of which of the 6545 survey configurations have beenobserved. This
ObsManager software produces a list of configurations that meet the abovecriteria at a user-supplied date and time, produces the files used to configure the 2dF fibres,and tracks observational progress.The 2dF configuration files produced by
ObsManager contain lists of science targets,
MNRAS , ?? – ????
MNRAS , ?? – ???? (2016) S. L. Martell et al. fiducial stars and sky positions, but they do not include specific allocations of targets toindividual 2dF fibres. This information is added with the Configure program (Miszalskiet al. 2006), which uses a simulated annealing algorithm to assign the fibres to targets asefficiently as possible while also respecting the limits on where in the field each individualfibre can be placed, allocating a user-determined number of fibres to sky apertures, andmaximising the number of guide fibres placed in the field of view.Observations are made semi-classically. Although
ObsManager could choose observ-able fields and produce setup files autonomously, the software controlling the 2dF fibrepositioner and the HERMES spectrograph is not amenable to scripted operations, and thehardware occasionally needs human intervention. Decisions relating to variable seeing orweather also benefit from the intuition of an experienced observer. GALAH observationstypically involve one or two astronomers from the science team, one of whom has significantexperience observing with 2dF. These observers run
ObsManager , select configurations toobserve, configure 2dF, initiate all exposures, maintain raw data organisation and keep logs.In addition to observing at the AAT, observations are also routinely conducted remotelyfrom the AAO offices in North Ryde and from remote observing facilities at Mt. StromloObservatory in Canberra and the International Centre for Radio Astronomy Research inPerth.
The GALAH Pilot Survey, which ran from 16 November 2013 until 19 January 2014, was ajoint science verification and early science program, concurrent with HERMES commission-ing. There were four main projects in the Pilot Survey:
Gaia benchmark stars, thin/thickdisk normalisation, star clusters, and asteroseismic targets observed by the CoRoT satellite.These projects covered a wide range of possible uses for HERMES, while allowing the com-missioning and science verification teams to test critical functions of both the instrumentand the GALAH software. The data set and goals for each of these projects are described be-low; results will be published separately as each project progresses. Because of the restrictedrange in target right ascension, the observing procedure was not as strict for the Pilot Sur-vey as for the main survey, and fields were observed at hour angles between − MNRAS , ?? – ?? (2016) ALAH Observational Overview Gaia benchmark stars
We have observed 26 of the 34 stars designated as benchmark stars for the
Gaia mission(Heiter et al. 2015). Since these stars are all quite bright, we observed them with a single2dF fibre rather than as part of regular survey configurations. Exposure times were short,typically less than 120 seconds, such that telescope tracking was sufficient to maintain thealignment of the star on the fibre. These stars have weakly-model-dependent measurementsof their stellar parameters based on angular diameter, bolometric flux, and parallax, whichcan be used to test the accuracy of spectroscopic stellar parameter determinations. Theyare also an excellent (if small) data set for cross-survey comparison and calibration, sincethey are well distributed across parameter space and evolutionary state, and across the sky.GALAH stellar parameters and metallicities for
Gaia benchmark stars will be discussed ina future paper on the data analysis pipeline.
The largest amount of observing time in the Pilot Survey was spent on a program to in-vestigate the normalisation (that is, the ratio of thin to thick disk stars in the midplane)and rotational lag between the Galactic thin and thick disks. A clear chemical separation inthe [ α/ Fe] − [Fe / H] abundance plane can be made between these two populations (see, e.g.,Adibekyan et al. 2012; Bensby et al. 2014; Hayden et al. 2015). With HERMES spectra, wecan study the overall [ α/ Fe] − [Fe / H] plane and the behaviour of individual alpha elementsin the thin versus the thick disk, since they do not all have the same nucleosynthetic origins.The intended observational targets of this project were red giant branch stars ∼ J − K ) > .
45 for10 < K < . J − K ) > − . < K <
10 and the same quality flags as theGALAH input catalogue. This program took observations of 9847 stars in 29 fields withGalactic longitude l ∼ ◦ and latitude b of − ◦ , − ◦ , − ◦ , − ◦ and − ◦ . Becausetargets were chosen based on photometry, there was contamination by foreground dwarfs.Separating dwarfs and giants at a surface gravity of log(g)=3.8, the contamination wastypically 36%, rising for stars further from the plane. This is somewhat lower than thedwarf/giant ratio we find in regular GALAH survey observations in the disk, indicatingthat the colour selection was helpful in isolating giants. The results of this project will bepresented in Duong et al. (in prep). MNRAS , ?? – ????
10 and the same quality flags as theGALAH input catalogue. This program took observations of 9847 stars in 29 fields withGalactic longitude l ∼ ◦ and latitude b of − ◦ , − ◦ , − ◦ , − ◦ and − ◦ . Becausetargets were chosen based on photometry, there was contamination by foreground dwarfs.Separating dwarfs and giants at a surface gravity of log(g)=3.8, the contamination wastypically 36%, rising for stars further from the plane. This is somewhat lower than thedwarf/giant ratio we find in regular GALAH survey observations in the disk, indicatingthat the colour selection was helpful in isolating giants. The results of this project will bepresented in Duong et al. (in prep). MNRAS , ?? – ???? (2016) S. L. Martell et al.
Globular and open star clusters provide important anchor points for large stellar surveys likeGALAH (e.g., Smolinski et al. 2011; Anguiano et al. 2015). We use stars in globular and openclusters to confirm that our analysis pipelines are returning reasonable and consistent valuesfor stellar parameters and abundances, to cross-calibrate with other large survey projects,and as benchmarks for chemical tagging methods.The Pilot Survey included targeted observations of stars in four globular clusters (NGC288, NGC 362, NGC 1851 and 47 Tucanae) and the open cluster M67. These clusters wereselected to provide a broad coverage of metallicity, and for observability with HERMESduring the Pilot Survey: right ascension, α , in the range 0h < α <
9h and distance modulus,( m − M ) V , less than 15 .
5. These observations were taken differently from normal GALAHsurvey observations, with the apparent magnitude range extended as faint as V = 16 andthe total exposure times extended as long as 6 hours per field for the more distant clustersto capture as many stars as possible from the red giant branch, red clump and horizontalbranch. The globular clusters ω Centauri and NGC 7099 were also specifically targeted afterthe end of the Pilot Survey, to provide additional well-studied anchors for our analysis.Similar to the Pilot Survey clusters, the apparent magnitude range extended to V = 17 andthe exposure times were as long as 6.3 hours.Targets in the Pilot Survey clusters were chosen from cluster members identified inprevious studies (Stetson, priv. comm.; Da Costa, priv. comm.; Carretta et al. 2009; Yonget al. 2009; Simpson & Cottrell 2013; Marino et al. 2014; Navin et al. 2015; Da Costa 2016).Targets in ω Cen were taken from Bellini et al. (2009), and in NGC 7099, targets were takenfrom Da Costa (2016). We were only able to observe between 10 and 173 cluster membersin any single configuration, given the magnitude limits and the limitations of the fibrepositioner (2dF fibres cannot be placed closer together on the sky than 30 (cid:48)(cid:48) ). All together,we observed between 10 and 394 stars total per cluster, typically in the outer regions. Table2 lists coordinates, distance moduli, metallicity (taken from Harris 1996, 2010 edition for theglobular clusters and Heiter et al. 2014 for M67), number of stars observed, V magnituderange, exposure time, and dates of observation for all of the globular and open clustersobserved in this targeted fashion. Figure 5 shows colour-magnitude diagrams for all of theseclusters, with stars observed by GALAH highlighted as red circles and stars from the 2MASSPoint Source Catalogue within 10 (cid:48) of cluster centre shown as smaller grey circles. MNRAS , ?? – ?? (2016) ALAH Observational Overview K S M67 K S
47 Tuc NGC288 K S NGC362 − . . . . NGC1851 − . . . . J − K S K S ω Cen − . . . . J − K S NGC7099
Figure 5.
Near-infrared colour-magnitude diagrams for the seven open and globular clusters observed intentionally. Red pointsare the cluster members, and smaller grey points are all stars in the 2MASS Point Source Catalogue within 10 (cid:48) of cluster centre.
Figure 6 shows the (
V, B − V ) colour-magnitude diagram for ω Centauri. All stars within10 (cid:48) with a membership probability above 0.9 are shown as small grey circles, and starsobserved by GALAH are highlighted as larger coloured circles. In the left panel they arecolour-coded by our derived effective temperature, and in the right panel they are colour-
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Table 2.
Data for globular and open clusters observed intentionally by GALAH
Cluster α δ (m-M) V [Fe/H] N stars V t exp (s) Obs. datesM67 08:51:18 +11:48:00 9.97 0.0 140 8.8 − − − − − − − − ω Cen 13:26:47.24 -46:28:46.5 13.94 -1.53 394 12.0 − − − Figure 6.
The (V,B-V) colour-magnitude diagram for ω Centauri, colour-coded by GALAH effective temperature (left panel)and metallicity (right panel). All stars within 10 (cid:48) of the cluster centre, with membership probability from Bellini et al. (2010)above 0.9, are shown as smaller grey circles. Both T eff and [Fe/H] behave as expected, both in terms of range and trends. coded by our derived metallicity. The optical photometry is taken from Bellini et al. (2010),which we also used for spectroscopic target selection. Our derived T eff follows exepctedtrends, and our derived [Fe/H] values show an overall similarity to the complex morphologydescribed in Johnson & Pilachowski (2010), with the reddest giant branch being the mostmetal-rich.In addition to the stars observed intentionally during the Pilot Survey, a number ofcluster members have been observed serendipitously in GALAH survey fields. The upperpanel of Figure 7 shows a colour-magnitude diagram for the 318 stars observed in surveyfield 51 (red circles), and the lower panel shows the spatial distribution of targets for thatfield, with a circle marking the field of view of 2dF. The concentration of targets near 47Tuc is clear in the south-western quadrant of the field, and in the colour-magnitude planethe cluster red giant branch can be seen mixed together with the broader distribution offield stars. 2MASS photometry for all stars within 10 (cid:48) of the centre of 47 Tuc is also shownas small grey circles to guide the eye. Membership for serendipitously observed cluster starscan be verified with radial velocity and proper motion. In addition to these serendipitouslyobserved 47 Tuc stars, we have identified stars belonging to NGC 362, M67, NGC 2516, NGC MNRAS , ?? – ?? (2016) ALAH Observational Overview . . . . . . . . J − K S K S RA (degrees) − . − . − . − . − . D e c ( d e g r ee s ) Figure 7.
Near-infrared colour-magnitude diagram for the stars in GALAH survey field 51. Red points are all stars observedin the field, and smaller grey points are all stars in the 2MASS Point Source Catalogue within 10 (cid:48) of the centre of 47 Tuc,similar to Fig. 5. Stars that are likely cluster members based on their photometry can be confirmed using radial velocities,stellar parameters and abundances determined from the spectra.
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The intersection of asteroseismic and spectroscopic data opens a number of new possibilitiesfor Galactic archaeology. Prior to 2015, the only large-scale asteroseismic mission with targetsthat could be observed from the Southern hemisphere was CoRoT (Auvergne et al. 2009).CoRoT observed one large region in the direction of the Galactic centre and one toward theanticentre, both at declination near zero, potentially providing common targets for GALAHand other ongoing Galactic archaeology surveys. We observed 2218 stars in six configurationsin the CoRoT anticentre fields LRa01, LRa05 and LRa07 as part of the pilot survey, with asimple 12 < V JK <
14 magnitude selection to match the target selection in the main GALAHsurvey. Of these, 1526 have successfully been processed through the GALAH analysis pipeline(as described in Section 9 below). We find that 737 of these stars have surface gravity below3.5, making them ideal for asteroseismic interpretation. Results from this project will bepresented in Anguiano et al. (in prep).
Following the failure of a second reaction wheel onboard the Kepler spacecraft in 2013, theextremely precise pointing that enabled its photometric monitoring work in a single Northernfield was lost, and the spacecraft was re-purposed to an observational program along theecliptic that enabled it to regain its fine pointing precision using only the two remainingreaction wheels and regular thruster firings. A series of 80-day observing “campaigns” alongthe ecliptic were laid out, and the community was invited to propose targets for this “K2”mission. The data acquired by K2 are useful both for asteroseismology and for transitingexoplanet surveys.There is tremendous potential in combining asteroseismic information with stellar sur-face temperature and composition data from photometry and spectroscopy (e.g., Miglioet al. 2013; Casagrande et al. 2016), bringing a new level of precision to determinations ofstellar age, mass, radius and surface gravity for red giant stars. Combined asteroseismic andspectroscopic data sets allow us to study stellar populations on a Galactic scale (e.g., Stelloet al. 2015; Sharma et al. 2016; Martig et al. 2016). They also make asteroseismic data usefulacross a broader range of stellar metallicity by providing crucial calibrations for the scalingrelations used to interpret stellar oscillations (Epstein et al. 2014). In addition, stellar pa-rameters obtained from spectroscopy are critical for determining the sizes of the transiting
MNRAS , ?? – ?? (2016) ALAH Observational Overview ∼
40% for Solar-type stars (e.g., Verner et al. 2011; Everett et al.2013; Bastien et al. 2014), and similar uncertainties apply for the majority of K2 targetsthat have been classified in the Ecliptic Plane Input Catalogue (Huber et al. 2016). Whenhigh-resolution, high S/N spectra are used in combination with transit measurements, plan-etary radii can be determined to precisions of 10 −
15% (e.g., Silva Aguirre et al. 2015; Weisset al. 2016).Galactic archaeology target proposals for K2, spearheaded by GALAH team membersS. Sharma and D. Stello, have been very successful, with typically 5000 targets in each K2observing campaign (though not all of these targets will turn out to be giants). Through aseparate K2-HERMES observing program at the AAT (AAT 15A/03, 15B/01, PI Witten-myer; AAT 15B/03, 16A/22, PI Sharma), many of these targets as well as potential exoplanethosts, are now being observed using similar procedures as for GALAH, enabling beneficialcollaboration between GALAH and the K2-HERMES program. In exchange for data reduc-tion and processing with the GALAH pipeline, K2-HERMES data are incorporated into theGALAH Survey database. K2-HERMES stars with asteroseismically derivable parameterswill be quite helpful in the testing and refinement of the GALAH analysis pipeline.The K2 field of view consists of nineteen separate square “CCD modules” covering foursquare degrees each, and the K2-HERMES fields lie at the centre of each CCD module’s fieldof view. The spectroscopic target selection is different in each K2-HERMES field based onits Galactic coordinates, targeting different stellar populations in different lines of sight. K2-HERMES configurations typically cover a wider range in apparent magnitude than GALAHsurvey fields. As with the survey fields, K2 fields are observed within 90 minutes of themeridian. As of 30 January 2016, the K2-HERMES program has observed 31,365 stars.
With a large allocation of time (26 nights for the Pilot Survey in Semester 13B and 70 nightsper year for the full survey starting in Semester 14A) and a highly multiplexed spectrograph,GALAH observing progress has moved quickly despite poorer-than-average weather. Ourdata rate is 4.2 stars per minute spent on-sky, yielding roughly 50,000 stars per semester.
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22h 20h 18h 16h 14h 12h 10h 8h 6h 4h 2h-75°-60°-45°-30°-15°0°15°30°45° 60° 75°
Figure 8.
Map of GALAH Survey progress through 30 Jan 2016. Grey circles are unobserved survey fields, pink are regularsurvey fields that have been observed, cyan are fields observed during the Pilot Survey, blue are fields observed by the K2-HERMES program, and purple are fields observed for the targeted
Tycho-2 bright star subproject.
Figure 8 is an equatorial-projection map of observing progress through 30 January 2016. Inthis map, grey circles are unobserved survey fields, pink are regular survey fields that havebeen observed, purple are fields observed for the Tycho-2 bright star subproject (describedin Section 9 below), blue are fields observed by the K2-HERMES program, and cyan arefields observed during the Pilot Survey. The number of observable regular survey fieldsvaries strongly with right ascension, with all survey fields in the range 23h (cid:54) α (cid:54)
4h alreadyobserved once.Figure 9 is a cumulative histogram of the number of stars observed from the start of thePilot Survey through 30 January 2016 in each of those programs, in fortnightly bins. Sincethere are significantly more stars that have been observed for the regular survey than theother programs, the y axis on the left is for the regular survey, and the y axis on the rightis for the Pilot Survey, K2-HERMES stars and
Tycho-2 bright stars. The number of regularsurvey stars is shown with a pink dashed line, the number of Pilot Survey stars is shown
MNRAS , ?? – ?? (2016) ALAH Observational Overview Date (MJD) N u m be r o f s t a r s ( m a i n s u r v e y ) N u m be r o f s t a r s ( p il o t s u r v e y , b r i gh t s t a r s , K - H E R M ES ) Figure 9.
Cumulative histogram of the number of stars observed versus MJD. with colours denoting different survey subsets(dashed pink: main survey; dash-dot dark blue: K2-HERMES; dotted cyan: pilot survey; dashed purple: targeted
Tycho-2 stars;solid purple: serendipitous
Tycho-2 stars. The vertical axis on the left is for the main survey, and the vertical axis on the rightis for the other projects. with a cyan dotted line, the number of K2-HERMES stars is shown with a blue dash-dotline, and the number of
Tycho-2 bright stars is shown with a purple solid line (
Tycho-2 stars observed serendipitously during other observations) and a purple dashed line (targetedbright-star fields). The Pilot Survey starts first and runs for a few months, the regular surveyand the K2-HERMES program start shortly before the Pilot Survey ends, and the targeted
Tycho-2 bright star observations begin later. Through 30 January 2016 we have observed209,345 stars in the main survey, 12,910 stars in the various Pilot Survey programs, and11034
Tycho-2 stars (4448 targeted and 6586 observed serendipitously), and an additional31,365 stars have been observed by the K2-HERMES program.
The wide sky coverage of the GALAH Survey provides significant overlap with several otherlarge-scale surveys. This creates important synergies, allowing us to link our thorough localsample with the astrometric measurements from the
Gaia mission, the pencil-beam in situ halo samples of the
Gaia -ESO and APOGEE surveys, the thorough
Gaia -ESO coverage ofopen clusters, the low-latitude disk sample from APOGEE and a significant fraction of thevery large sample of the RAVE survey.The
Gaia satellite (Prusti 2012; Lindegren & Perryman 1996), launched in late 2013,is collecting high-precision astrometry and photometry for stars with apparent magnitudes5 . < V <
20 as well as moderate-resolution spectroscopy near the near-infrared calcium
MNRAS , ?? – ????
MNRAS , ?? – ???? (2016) S. L. Martell et al. triplet and low-resolution spectrophotometry for stars down to V = 17. Gaia ’s full catalogueswill be revolutionary for our understanding of the phase-space structure of the Galaxy, aswell as providing spectrophotometry and basic stellar parameters for as many as one billionstars. Perhaps the most important synergy we have is with
Gaia , as the entire GALAH inputcatalogue is within the brightest 1% of
Gaia targets, which will have parallax uncertaintiesless than 10 µ as and proper motion uncertainties of less than 10 µ as per year, correspondingto 1% distance errors and 0 . − velocity errors at 15 kpc. Coupling the unprecedentedabundance detail of GALAH with the 6-dimensional phase-space positions and velocitiesthat can only be measured by Gaia will allow us to identify chemically homogeneous groupsof stars that also match in age and orbital properties, revealing the process of star formationand chemical evolution in the Galaxy.The
Gaia -ESO Survey (GES; Gilmore et al. 2012; Randich et al. 2013) is another ongoingGalactic archaeology survey project, using the GIRAFFE spectrograph (Pasquini et al.2000) at the Very Large Telescope at the European Southern Observatory in Chile to collecthigh-resolution ( R ∼ , ,
000 stars, primarily in the halo and in starclusters. A smaller sample of brighter stars is also being observed at higher resolution ( R ∼ , . µ m − . µ m), reducing the line-of-sight extinctionand allowing observations of stars much closer to the Galactic plane, including stars on thefar side of the bulge. APOGEE spectra have a resolution of R ∼ includes abundances for up to 21 elements per star (Garc´ıa P´erez et al. 2016). , ?? – ?? (2016) ALAH Observational Overview insitu halo, albeit with a pencil-beam distribution. APOGEE also typically targets stars atlarger distances than GALAH does, but perhaps more importantly it includes a significantsample of stars in and near the plane of the Galaxy. The combination of GALAH, GES andAPOGEE data will enable science that cannot be done by any one of the surveys alone.Potential examples are studies of radial and vertical trends in the thin disk that use thelocal GALAH sample as an anchor and the more distant APOGEE and GES samples asprobes. It will be critical to bring the abundance results of these different projects onto thesame scale to allow this type of cross-survey study.There is some observational overlap designed in to GALAH, GES and APOGEE, despitetheir different selection functions, to facilitate this cross-calibration. The Southern exten-sion of APOGEE-2 will make cross-calibration between GALAH and APOGEE much morestraightforward, and APOGEE-2 observations are planned to provide a set of stars thatcomprehensively cover the parameter space of GALAH and APOGEE stars. We have al-ready identified a serendipitous survey overlap of 185 stars with GES, evenly split betweenUVES and GIRAFFE observations, and a serendipitous overlap of 664 stars with APOGEE,mainly in the K2 ecliptic campaign fields and CoRoT Galactic anticentre regions. The data-driven approach of The Cannon (Ness et al. 2015) will be central to the cross-calibrationeffort (e.g., Ho et al. 2016), and its capabilities in this area have already been demonstratedin Ness et al. (2016).The Radial Velocity Experiment (RAVE, Kordopatis et al. 2013) survey is an importantprecursor to the current generation of Galactic archaeology surveys. RAVE took R ∼ < I <
12. While the original plan was to determine radial velocities and basic stellar param-eters from these data, the RAVE team has shown that they can also derive several elementalabundances and probabilistic distances (Binney et al. 2014; Boeche et al. 2011; Kordopatiset al. 2011; Zwitter et al. 2010). The development of automated spectrum analysis pipelineshas benefited from the work of the RAVE team and their goal of maximising the amount ofinformation to be derived from their spectra. A large fraction of the RAVE sample falls intoGALAH’s input catalogue, since both are Southern-sky surveys primarily using apparentmagnitude for target selection. There are 9388 RAVE stars in the data set considered in thispaper. Having GALAH observations of a large number of RAVE stars provides an extremely
MNRAS , ?? – ????
MNRAS , ?? – ???? (2016) S. L. Martell et al. large comparison set for GALAH radial velocities, and will enable detailed followup andextension of important RAVE studies of Galactic dynamics and structure (e.g., Williamset al. 2013; Antoja et al. 2012, Siebert et al. 2012; Ruchti et al. 2011).SkyMapper (Keller et al. 2007) is an Australian synoptic survey project imaging theSouthern sky in 6 photometric bands. Its particular advantage is the inclusion of a Str¨omgren-like u filter that captures the Balmer jump and a narrow v filter that spans the Ca II Hand K lines, similar to the DDO38 filter. Colour indices including these filters can be con-structed to be quite sensitive to either surface gravity or metallicity (e.g., Keller et al. 2014;Howes et al. 2014). SkyMapper photometry will be a useful tool for a number of GALAH sci-ence goals, including the identification of very metal-poor stars, confirmation of star clustermembership, and the study of interstellar reddening through comparison of stellar effec-tive temperatures derived photometrically and spectroscopically. We have already identifiedroughly 60,000 stars in common between GALAH and the SkyMapper Early Data Release,which includes objects from their “short survey” of relatively bright targets. We expect thatultimately all GALAH stars will be in the SkyMapper catalogue. TYCHO-2
STARS AND
GAIA
DR1
The
Tycho-2 catalogue (Høg et al. 2000) contains positions and magnitudes for 2.5 millionstars. Although the full precision of the astrometric solution for the full
Gaia dataset canonly be reached with several years of data, combining the
Tycho-2 catalogue with the firstyear of
Gaia data (at an epoch 24 years later) allows a precise solution for positions ( σ (cid:54) . σ (cid:54) .
64 mas) and proper motions ( σ (cid:54) .
19 mas yr − ) for all the Tycho-2 stars (the “Tycho-Gaia Astrometric Solution”, TGAS), as described in Michalik et al. (2014)and Michalik et al. (2015).In anticipation of the first
Gaia data release and the TGAS work, GALAH has prioritisedobservations of
Tycho-2 stars, generating 330 special configurations for fields within thefootprint of the main GALAH survey that contain at least 225 stars from
Tycho-2 in therange 9 < V JK <
12. These configurations are suggested by the
ObsManager softwarefor observation during evening and morning twilight. Because these stars are brighter thanGALAH survey targets, the standard exposure times are shortened to 3 × ×
20 minutes. As of 30 January 2016 we have observed 4448
Tycho-2 stars in 26 of these
MNRAS , ?? – ?? (2016) ALAH Observational Overview Table 3.
The GALAH-TGAS catalogue. The full catalogue is available online; a portion of the table is published here forguidance as to form and content.
GALAH ID Tycho-2 ID 2MASS ID α δ T eff (K) log(g) [Fe/H] [ α /Fe] v rad (km s − ) ( m − M ) V E ( B − V )22245 9512-01937-1 J13593210-8450329 13h59m32.11s -84d50m32.9s 6411 3.98 -0.35 0.03 19.422 9.075 0.06326942 9508-02667-1 J13373358-8420456 13h37m33.58s -84d20m45.6s 5832 4.07 -0.32 -0.02 39.962 8.094 0.02227265 9509-01044-1 J14203533-8418486 14h20m35.34s -84d18m48.6s 6162 3.94 -0.55 0.01 34.000 8.141 0.08328459 9508-02321-1 J13383428-8411192 13h38m34.28s -84d11m19.2s 6006 4.21 -0.28 0.02 8.263 7.934 -0.02228516 9508-02638-1 J13534492-8410566 13h53m44.92s -84d10m56.7s 4207 1.73 -0.56 0.39 32.238 11.894 0.08829248 9509-00704-1 J14072550-8406074 14h07m25.51s -84d06m07.4s 5813 4.45 -0.00 -0.04 22.343 7.596 0.08735133 9509-02342-1 J14031173-8332020 14h03m11.73s -83d32m02.1s 5086 3.53 -0.38 0.13 -23.160 9.190 0.05235890 9508-02273-1 J13594214-8327377 13h59m42.14s -83d27m37.8s 4858 2.72 -0.01 0.13 -16.954 11.006 0.04636337 9508-01621-1 J13463498-8325184 13h46m34.99s -83d25m18.5s 5763 4.21 -0.46 0.12 1.803 7.134 0.05650312 9440-00171-1 J15071754-8214018 15h07m17.54s -82d14m01.9s 6000 3.72 -0.20 0.03 5.900 8.363 0.170 targeted fields. An additional 6586 stars from the Tycho-2 catalogue have been observed aspart of our regular survey fields.Although we do not know exactly which
Tycho-2 stars will be included in
Gaia
DR1 orTGAS, we have made a portion of the current GALAH derived quantities for
Tycho-2 starspublicly available ahead of the first
Gaia data release, which will take place on 14 September2016. Our goal in publishing this GALAH-TGAS catalogue is to facilitate the exploitationof
Gaia
DR1 and to demonstrate the quality of GALAH derived quantities with a dataset that will be extremely well studied in the near future. Table 3 lists ID numbers fromGALAH,
Tycho-2 and 2MASS, right ascension and declination from UCAC4, T eff , log(g),[Fe/H], [ α /Fe], radial velocity, distance modulus and E ( B − V ) reddening for the first tenstars in the catalogue; the full table is available on the Vizier catalogue service. The fulltable includes analysis results for 3801 observations of 3675 Tycho-2 stars in targeted fieldsand 6879 observations of 6185 serendipitiously observed
Tycho-2 stars for which we havesuccessfully determined stellar parameters.Barycentric-corrected radial velocities are determined through cross-correlation againsta grid of AMBRE model spectra (de Laverny et al. 2012), as described in Kos et al. (2016).We use the HERMES blue, green, and red arm spectra for radial velocity determination,but not the IR arm spectra due to a relative lack of stellar features and a large numberof telluric features. Adopted radial velocities are the mean of the values in the three arms,and the reported uncertainty is the standard deviation. Note that if the radial velocitymeasured from one arm is notably discrepant, e.g., is further from the mean than two timesthe difference between the measurements from the other two arms, it is excluded from thefinal radial velocity estimate. 98% of all of our GALAH stars have a standard deviation ofless than 0.6 km s − .The typical error on the radial velocity combined from the measurements in the three MNRAS , ?? – ????
Tycho-2 stars for which we havesuccessfully determined stellar parameters.Barycentric-corrected radial velocities are determined through cross-correlation againsta grid of AMBRE model spectra (de Laverny et al. 2012), as described in Kos et al. (2016).We use the HERMES blue, green, and red arm spectra for radial velocity determination,but not the IR arm spectra due to a relative lack of stellar features and a large numberof telluric features. Adopted radial velocities are the mean of the values in the three arms,and the reported uncertainty is the standard deviation. Note that if the radial velocitymeasured from one arm is notably discrepant, e.g., is further from the mean than two timesthe difference between the measurements from the other two arms, it is excluded from thefinal radial velocity estimate. 98% of all of our GALAH stars have a standard deviation ofless than 0.6 km s − .The typical error on the radial velocity combined from the measurements in the three MNRAS , ?? – ???? (2016) S. L. Martell et al. arms is a combination of systematic errors. One main contributor is the uncertainty thatcomes from the wavelength calibration itself. Spectra have been wavelength calibrated usinga spectrum of a Thorium-Xenon arc lamp. Xenon lines dominate these spectra and we hadto calibrate their wavelengths from the HERMES spectra themselves because of a lack ofreliable linelist information in the literature. The wavelength calibration is therefore onlyaccurate to 0 . . − , as can be seen in Figure 12 of Kos et al. (2016). The systematicoffset in radial velocity between different arms is very low on average, typically − − between the green and blue arms and − − between the red and blue arms. Forany given star there is a 1 σ probability that the difference in radial velocity between anytwo arms will be as large as 0 . .
75 km s − , depending on the arms. This can be seen inFigure 18 of Kos et al. (2016).We have compared GALAH radial velocities to a number of sources in the literature.As presented in Kos et al. (2016), the values show good agreement with literature valuesfor four clusters, M67, NGC 1851, NGC 288, and 47 Tuc. We can also verify our radialvelocity accuracy by comparing GALAH values with those from other surveys. Throughthe end of January 2016 (the time period discussed in this study), there are 9388 and 664targets that have also been observed by RAVE and APOGEE (RAVE DR4: Kordopatis et al.2013; SDSS DR10: Ahn et al. 2014), respectively. As the survey continues, this will proveto be an invaluable sample for database cross-comparison. Currently, it provides a usefulcomparison set for our radial velocities. The left panel of Figure 10 shows the distributionof the difference in velocities between RAVE and GALAH. For this comparison, we havetrimmed the GALAH-RAVE overlap sample to 3434 stars, based on the following qualitycriteria from the RAVE catalogue (M. Steinmetz, priv. comm.): • logg K > • SNR K > • eHRV <
10 km/s • Teff K > • CHISQ c < • c1, c2, c3 = n • Algo Conv K = 0The mean offset between GALAH and RAVE is 0.45 km s − with a standard deviationof 1.75 km s − . Since RAVE uses lower resolution spectra than GALAH and reports a MNRAS , ?? – ?? (2016) ALAH Observational Overview −50 0 50GALAH RV−2024 ∆ R V ∆ R V Figure 10.
A comparison of GALAH radial velocities with values from RAVE ( left panel ) and APOGEE ( right panel ). Thex-axis is the GALAH radial velocity in km s − while the y-axis is the difference between the GALAH value and that from theother survey, in the sense (GALAH-other). Color, as denoted by the bar, indicates the number density of stars. The right handportion of each figure shows the distribution of the difference in radial velocity. The top left corner lists the mean and standarddeviation in radial velocity difference. typical radial velocity uncertainty of 2 km s − , this is very good agreement. APOGEE isalso consistent with GALAH, showing a mean offset of 0.05 ± − (Figure 10, rightpanel).For the stellar parameter determination, we use a combination of the spectral synthesisprogram Spectroscopy Made Easy (SME) (Valenti & Piskunov 1996; Piskunov & Valenti2016) and the data-driven Cannon by Ness et al. (2015). This approach delivers both accu-rate and precise parameters and is computationally inexpensive, as
The Cannon takes only0.13 seconds to compute seven stellar labels for one spectrum.We first use SME to determine stellar parameters and [ α /Fe] abundances for a subsetof 2576 GALAH stars spanning the entire range of parameters covered by the survey. Thissubsample is then used as the training data set for The Cannon . To obtain the highest pre-cision and accuracy, this representative training set is comprised of only high quality spectra(SNR >
95 per resolution element), as well as high-fidelity validation targets including ob-served benchmark stars with reliable, independent stellar parameters (Heiter et al. 2015),well studied open and globular cluster stars, and stars with confirmed asteroseismic surfacegravities.Our initial estimates for T eff , log(g) and [Fe/H] are determined through cross-correlationagainst a grid of AMBRE model spectra that is larger and more finely sampled than thegrid used for radial velocity determination, as decribed in (Kos et al. 2016). SME takes theseas input and determines the stellar parameters by fitting synthetic spectra to observations,returning optimal parameters corresponding to the minimum χ (Piskunov & Valenti 2016).The SME synthesis employs MARCS model atmospheres (Gustafsson et al. 2008), and in-cludes NLTE corrections for Fe (Lind et al. 2012). The global parameters T eff , log(g), [Fe/H], v mic , V sin i , and v rad are optimized for unblended lines in the spectra, including the H α , H β , MNRAS , ?? – ????
95 per resolution element), as well as high-fidelity validation targets including ob-served benchmark stars with reliable, independent stellar parameters (Heiter et al. 2015),well studied open and globular cluster stars, and stars with confirmed asteroseismic surfacegravities.Our initial estimates for T eff , log(g) and [Fe/H] are determined through cross-correlationagainst a grid of AMBRE model spectra that is larger and more finely sampled than thegrid used for radial velocity determination, as decribed in (Kos et al. 2016). SME takes theseas input and determines the stellar parameters by fitting synthetic spectra to observations,returning optimal parameters corresponding to the minimum χ (Piskunov & Valenti 2016).The SME synthesis employs MARCS model atmospheres (Gustafsson et al. 2008), and in-cludes NLTE corrections for Fe (Lind et al. 2012). The global parameters T eff , log(g), [Fe/H], v mic , V sin i , and v rad are optimized for unblended lines in the spectra, including the H α , H β , MNRAS , ?? – ???? (2016) S. L. Martell et al. T he C annon :t e ff Bias: 5.0Scatter: 51.0RMS: 51.0 G r een c hanne l S NR SME input: teff − − − S M E - T he C annon T he C annon : l ogg Bias: 0.01Scatter: 0.17RMS: 0.17 G r een c hanne l S NR SME input: logg − . − . . . . . S M E - T he C annon − . − . − . − . . T he C annon :f eh Bias: 0.005Scatter: 0.056RMS: 0.057 G r een c hanne l S NR − . − . − . − . . SME input: feh − . − . − . . . . . S M E - T he C annon Figure 11.
Results from 20% leave-out cross validation tests for T eff (upper left), log(g) (upper right) and [Fe/H] (lower left),as described in the text. These tests were repeated five times, and data from all five tests are plotted together in this figure,colour-coded by the green channel signal to noise ratio per resolution element. For each parameter, the upper panel shows C annon versus SME parameters with a 1:1 correspondence line drawn in solid black, and the lower panel shows the differencebetween the two as a function of the SME values. FeI/II, ScI/II, and TiI/II lines which have reliable atomic data. The optimal global param-eters returned by SME are subsequently fixed, and an error weighted [ α /Fe] is calculatedfrom χ optimization for selected lines of α -process elements Mg, Si, and Ti. The Cannon then uses the normalised spectra, SME-determined stellar parameters and α -abundances as labels for the reference set of stars and generates a spectral model ofthe GALAH spectra at rest-frame wavelength. This generative Cannon model relates theobserved flux to the labels provided (the training step) and is used to determine thosesame labels for all stars in the survey. We find that a second order polynomial model workswell for GALAH spectra. In addition to the SME stellar parameters and abundances, wealso include extinction values as a label for
The Cannon , allowing it to take into accountthe effect of diffuse interstellar bands on some α -element lines, and thus providing a moreaccurate final α -abundance. The extinction, A K , is derived as described by Zasowski et al.(2013), using the 2MASS H -band and WISE 4.5 µ m photometry (Skrutskie et al. 2006;Wright et al. 2010). For each star, The Cannon delivers a set of seven labels consisting of:
MNRAS , ?? – ?? (2016) ALAH Observational Overview Figure 12.
Stellar parameters T eff and log(g) for stars in the GALAH-TGAS catalogue, colour-coded by metallicity (leftpanel), and binned into hexagons and colour-coded by the number of stars per bin (right panel). T eff , log(g), [Fe/H], v mic , V sin i , [ α /Fe] and A K . Figure 11 shows the results of 20% leave-outcross-validation tests demonstrating that The Cannon is well able to determine the stellarlabels to high precision. This test involves omitting a random 20% of the training set, thencomparing the parameter values predicted for those omitted stars by
The Cannon with thevalues determined using SME. We find the following biases and precisions: ∆ T eff = 5 ±
41 K,∆ log ( g ) = 0 . ± .
17 dex, ∆[Fe / H] = 0 . ± .
056 dex. We have provided here a summaryof the GAALH spectroscopic analysis pipeline, the details of which will be given in Asplundet al. (in prep).Distances are determined using theoretical isochrones, as discussed in Zwitter et al.(2010), assuming that each star undergoes a standard stellar evolution and that its spectrumshows no peculiarities. The latter is checked by morphological classification of spectra whichis based on a t-distributed stochastic neighbor embedding algorithm (Traven et al. 2016, inpreparation; for description of the algorithm see van der Maaten 2013 and references therein).Absolute magnitudes in Johnson V and 2MASS J bands are estimated from theoreticalPadova isochrones (Bertelli et al. 2008) with weights determined (as described in Zwitteret al. 2010) using a mass function from Chabrier (2003), a flat prior on ages between 0.5and 12 Gyr and a flat prior on space density. Stellar parameter values determined fromGALAH spectra by the Cannon algorithm (Ness et al. 2015) are assumed to have a standarddeviation of 100 K in temperature, 0.25 dex in gravity and 0.1 dex in metallicity. These errorestimates are compatible with differences between parameter values determined by GALAHand APOGEE (Holtzman et al. 2015) for stars observed by both surveys.Comparison of absolute magnitudes with the apparent V magnitude from the latest MNRAS , ?? – ????
056 dex. We have provided here a summaryof the GAALH spectroscopic analysis pipeline, the details of which will be given in Asplundet al. (in prep).Distances are determined using theoretical isochrones, as discussed in Zwitter et al.(2010), assuming that each star undergoes a standard stellar evolution and that its spectrumshows no peculiarities. The latter is checked by morphological classification of spectra whichis based on a t-distributed stochastic neighbor embedding algorithm (Traven et al. 2016, inpreparation; for description of the algorithm see van der Maaten 2013 and references therein).Absolute magnitudes in Johnson V and 2MASS J bands are estimated from theoreticalPadova isochrones (Bertelli et al. 2008) with weights determined (as described in Zwitteret al. 2010) using a mass function from Chabrier (2003), a flat prior on ages between 0.5and 12 Gyr and a flat prior on space density. Stellar parameter values determined fromGALAH spectra by the Cannon algorithm (Ness et al. 2015) are assumed to have a standarddeviation of 100 K in temperature, 0.25 dex in gravity and 0.1 dex in metallicity. These errorestimates are compatible with differences between parameter values determined by GALAHand APOGEE (Holtzman et al. 2015) for stars observed by both surveys.Comparison of absolute magnitudes with the apparent V magnitude from the latest MNRAS , ?? – ???? (2016) S. L. Martell et al.
Figure 13.
Absolute colour-magnitude diagram for stars in the GALAH-TGAS catalogue, colour-coded by metallicity (leftpanel) and distance (right panel). version of the APASS survey (Henden & Munari 2014) and J magnitude from 2MASS (Cutriet al. 2003) leads to an estimate of the distance modulus as well as reddening along the lineof sight, if standard relations A V = 3 . E ( B − V ) and A J = 0 . E ( B − V ) are used. Thetypical accuracy of derived distance modulus is 0.4 mag (implying a distance uncertaintyof ∼ ∼ .
04 mags. Such errors apply tomain sequence (MS) and to red giant branch stars, but for the transition region between theMS turn-off and the red giant branch the errors increase considerably. Comparison of ourand literature values of distance moduli and reddenings for members of three open clusters(NGC 2243, Pleiades and NGC 2516) and one globular cluster (NGC 6362) confirm sucherror estimates. GALAH targets are located at least ten degrees from the Galactic plane,so uncertainties in reddening do not affect derived values of distance modulus significantly.This is confirmed by a median value of just 0.03 mag for the colour excess. Here we publishspectrophotometric distances for
Tycho-2 stars, which are much brighter and so closer thantypical stars observed by GALAH, where MS stars are generally within 1 kpc from the Sunand red clump stars are at distances of ∼ Tycho-2 stars observed by GALAH appear to be quitereasonable. This can be seen in Figure 12, which shows effective temperature versus surfacegravity, colour-coded by metallicity (left panel) and binned into hexagons and colour-codedby the number of stars per bin (right panel). As one might expect, there is a clear gradientin metallicity across the red giant branch and the upper main sequence. There are fewmetal-poor stars ([Fe/H] < − . B − V ) and absolute M V , MNRAS , ?? – ?? (2016) ALAH Observational Overview − . − . − . − . . . . [Fe/H] N u m be r o f s t a r s Distance (kpc) N u m be r o f s t a r s Figure 14.
Histograms of metallicity (left panel) and distance (right panel). The distance histogram is shown on a logarithmicscale to enhance the visibility of stars at larger distance, since the majority of stars in the GALAH-TGAS catalogue are quitenearby. colour-coded by metallicity (upper left panel) and distance (upper right panel), and binnedinto hexagons and colour-coded by the number of stars per bin (lower left panel).Since these stars are fairly bright, their distribution across the Milky Way is somewhatlimited relative to the full GALAH survey. This can be seen in Figure 14, which showshistograms of metallicity (left panel) and distance (right panel). Although the stars in theGALAH-TGAS catalogue do span the full sky coverage of the GALAH survey (as can beseen in Figure 15), they are mainly members of the thin disk: they have relatively highmetallicities and are located within 2 kpc of the Sun.
10 SUMMARY
The GALAH Survey has made significant progress toward its goal of observing one millionstars in the Milky Way over its first two years of survey observing. Up to 30 January 2016we have observed 209,345 stars in the main survey, 845 targeted stars in globular and openclusters, 2,218 stars in the CoRoT anticentre fields, and 9,847 stars for the thin-thick diskprogram during the Pilot Survey, and an additional 31,365 stars have been observed by theK2-HERMES program.We have also intentionally observed 4448 Tycho-2 stars in 26 fields to correspond withthe first
Gaia data release, with another 6586 stars observed serendipitously in the regularGALAH Survey fields. Of these, we are making available analysis results for 10680 observa-
MNRAS , ?? – ????
MNRAS , ?? – ???? (2016) S. L. Martell et al.
Figure 15.
Map of the GALAH-TGAS catalogue in right ascension and declination, colour-coded by radial velocity. The Solarmotion relative to the Local Standard of Rest can be clearly seen. tions of 9860 stars (3801 observations of 3675 targeted stars and 6879 observations of 6185serendipitous stars) that have successfully been processed through our parameter and abun-dance determination pipeline. A catalogue of stellar parameters, radial velocities, distancemoduli and reddening for these successfully analysed stars is presented in this publication,to support broad scientific exploitation of the first
Gaia data release. As demonstratedabove, these parameters look quite robust. We anticipate that they will improve furtherwhen we adapt our spectroscopic analysis pipeline to include the stellar distances derived bythe Tycho-Gaia Astrometric Solution (Michalik et al. 2015) and future
Gaia data releases.Combining spectroscopic datasets with
Gaia data serves many important purposes beyondimproving spectroscopic analysis. Future GALAH data releases will add elemental abun-dance information for the stars with the best
Gaia parallaxes and proper motions, enablingchemodynamic studies in the Solar neighbourhood and throughout the Galaxy, and addingkinematic information into chemical tagging.The target selection and field tiling for GALAH are fixed, and we will continue to followthe same observing rules for the duration of the survey, maintaining our straightforwardselection function. Based on Galactic models and our target selection strategy we anticipatea final data set that is dominated by the thin and thick disks, but despite the small fractionof halo and bulge stars expected ( < MNRAS , ?? – ?? (2016) ALAH Observational Overview ACKNOWLEDGMENTS
SLM and DBZ acknowledge support from Australian Research Council grants DE140100598and FT110100743. JPM is supported by a UNSW Vice-Chancellor’s Research Fellowship.K.L. and S.B. acknowledge funds from the Alexander von Humboldt Foundation in theframework of the Sofja Kovalevskaja Award endowed by the Federal Ministry of Educationand Research as well as funds from the Swedish Research Council (Grant nr. 2015-00415 3)and Marie Sklodowska Curie Actions (Cofund Project INCA 600398).This work was partlysupported by the European Union FP7 programme through ERG grant number 320360.
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