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2018 NYC Gaia Sprint pitch slides

2018 NYC Gaia Sprint pitch slides

90-ish authors, presented jointly at the Flatiron Institute.

David W Hogg

June 04, 2018
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  1. 2018_NYC_Gaia_Sprint
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  3. Josh Peek (STScI / JHU)
    Hope to do: Statistically constrain the 3D substructure of dust, continue to maim
    the gaseous Perseus arm, study details of the velocities of young stars in the
    MW, LMC, SMC. Maybe also ultra-precision stellar color standards for reddening?
    Hope to learn: The best ways to use the results of and limitations of the Apsis
    pipeline, statistical analysis techniques relevant to Gaia.
    What I bring: Knowledge of the ISM and reddening, details of spiral structure,
    some deep learning especially in image analysis.

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  4. L L (Princeton)
    Hope to do: Characterize the radial evolution
    of the shape of the velocity ellipsoid of the
    Milky Way’s stellar halo
    What I bring: Knowledge of
    Galactic dynamics, and a cheery
    disposition.
    Hope to learn: All the cool science that
    people are doing :) and how to best exploit
    the various parameters provided by the
    Gaia Source.
    I like to think of myself as the guy on the left...

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  5. Xiang-Xiang Xue National Astronomical Observatories, Beijing
    Hope to do:
    1. study the dynamical relations between (stellar-)halo substructures
    identified in Integral-of-Motion space using SDSS/SEGUE/LAMOST+Gaia;
    2. constrain the dark matter distribution of the Milky Way with 6D
    information of blue-horizontal-branch stars and K giants.
    Hope to learn: how to measure element abundance of stars with
    low-resolution spectra; chemo-dynamical modeling for streams.
    What I bring: code of calculating E and L and identifying groups in I.o.M space;
    SDSS BHB/SEGUE K giants X Gaia catalogs; some experience on distance
    estimation of halo K giants.

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  6. Hans-Walter_Rix
    (MPIA_Heidelberg)
    I can bring: dynamics &
    spectra & data modelling &
    opinions
    I’d like to do:
    finish 1 paper, start 2
    I’d love to learn: how to
    find (many new) stellar-mass
    BHs in the Galaxy

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  7. Daniel Hestroffer (Paris observatory, France)
    Hope to do: ad-hoc astrometric catalogue corrections based on Gaia as reference.
    Improved dynamical models from combination of Gaia and ground-based
    astrometry.
    Hope to learn: Statistical inversion for large data sets. Techniques parameteric or
    not for combining inhomogeneous data (of different variance, distributions, etc.).
    Python and visualisation tool
    What I bring: astrometry and dynamics of Solar System Objects.
    poor knowledge about much.

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  8. Natalie Hinkel (Vanderbilt -> Southwest Research Institute)
    Hope to do: Investigate stellar abundances (Hypatia Catalog) in the solar
    neighborhood via DR2 and how “well measured” stars may be, examine
    chemical+physical disparity between thin and thick disk stars (since there
    seem to be a variety of definitions on how you tell the populations apart)
    Hope to learn: New data-driven methods for exploring large datasets and
    matching methods to a problem, including the meta- or housekeeping data
    What I bring: Hypatia Catalog of stellar abundances
    (www.hypatiacatalog.com), solid knowledge of Python,
    decent grasp of XGBoost
    Find me if you want LEGO—>

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  9. Megan Bedell (Flatiron)
    Do: Science with comoving pairs (esp. ones with measured compositions
    and/or exoplanets!); planets in galactic populations??
    Learn: Galactic dynamics 101
    Bring:
    ★ Gaia x Kepler / K2 / confirmed exoplanet host catalogs (@ gaia-kepler.fun)
    ★ general knowledge about exoplanets & stellar abundances
    ★ code to (naively) find comoving pairs
    ★ moral support & an unlimited supply of puppy gifs

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  10. Jacob Hamer (Johns Hopkins University)
    Hope to do: Calculate UVW velocities for hot Jupiter hosts and a control sample,
    compare velocity dispersions, meet new people in the field!
    Hope to learn: How to select the best sample from DR2, correctly use full
    covariance info when using parallaxes
    What I bring: Experience comparing population ages with velocity dispersions,
    knowledge about exoplanets, good python knowledge

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  11. Jose Hernandez (ESAC, DPAC)
    Hope to do: Learn how to identify, classify and understand unknown cases where
    the DR2 astrometric solution is odd, apply ML to this. Learn how to use other
    catalogues.
    Hope to learn: New ways of validating and improving future Gaia astrometric
    solutions, find coherences and incoherences in the data, see how people use the
    data and find out what we can try to improve in future releases (what statistics are
    we missing for example). Python, statistics.
    What I bring: Experience in Gaia astrometric solution, limitations, errors, gaia
    source statistics. Knowledge of the data model, filters applied to DR2, DPAC
    internal processing, Java, catalogue Xmatch. Working with large datasets.

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  12. Ronald Drimmel (DPAC member, INAF astronomer)
    What I bring:


    Hope to do:
    ★ great discoveries

    Hope to learn:


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  13. Cicero Lu (Johns Hopkins University)
    Hope to do: Produce a (V - K
    s
    )-M
    ks
    color-magnitude diagram for K2 exoplanet
    hosting candidate sample. (V - K
    s
    )-M
    ks
    color magnitude diagram is correlated with
    metallicity. I am curious to know if there exists a significant metallicity offset for
    exoplanet hosts. & Get to know other awesome research topics!
    Hope to learn: Statistics related to Gaia measurement bias, using ML on big data
    in astronomy, general familiarity with other databases, major differences between
    Gaia DR1 and DR2 measurements
    What I bring: Familiarity with MAST database, knowledge of broadband
    photometry related to low mass stars and exoplanet formation theory.

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  14. David W. Hogg (NYU) (MPIA) (Flatiron)
    Hope to do: Determine the kinematic age of the high-metallicity halo, and find
    substructures therein! (Also maybe make spectroscopic parallaxes?)
    Hope to learn: How to understand (and exploit!) the Gaia noise model and excess
    noise outputs, and other housekeeping data.
    What I bring: Expertise in hierarchical modeling and probabilistic models,
    self-calibration of surveys and instruments, The Cannon. I love to consult talk.

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  15. Carles Badenes (University of Pittsburgh)
    Hope to do: Use Gaia DR2 data to improve our understanding of short-period
    stellar multiplicity. I want to (a) use the RV dispersions from Gaia as a tracer of
    stellar multiplicity and (b) cross-correlate Gaia with APOGEE and other data sets
    to refine multiplicity constraints and single out interesting systems for follow up.
    Hope to learn: How to take advantage of parallaxes and proper motions (and RVs,
    when available) to pin down stellar models.
    What I bring: Some familiarity with APOGEE and statistical inferences from
    sparsely-sampled RV curves. Quirky, unsystematic knowledge of stellar evolution
    and chemical enrichment.

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  16. Merce Romero-Gomez (Institut de Ciencies del Cosmos-Universitat de Barcelona, IEEC)
    Hope to do: Study Young Local Associations: from selection/detection to
    estimation of a dynamical age.
    Hope to learn: Population selection based on Gaia DR2 or crossmatch with other
    catalogues. (Python) tools to manage large data sets.
    What I bring: Familiarity with Gaia DR2 data and archive. Experience in exploring
    disc kinematics, effects of the galactic bar, spirals, warp. Experience using orbit
    integration and coordinate transformation from the observables to galactocentric
    using correlations.

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  17. Francisca Concha-Ramírez (Leiden Observatory)
    Hope to do: Characterize and compare observed and simulated young star clusters
    and star forming regions; dip my toes in observational astronomy.
    Hope to learn: How to find star clusters in Gaia DR2; how observed clusters are
    characterized dynamically and in other ways (color, magnitudes, etc.).
    What I bring: Knowledge of N-body simulations (esp. using the AMUSE framework),
    galactic dynamics, and protoplanetary disks; python skills;
    some simulated star clusters with different initial conditions.
    + Portegies Zwart & Concha-Ramírez 2017
    + Concha-Ramírez et al 2018 (submitted)

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  19. Hope to do: Classify QSOs/BHBs/WDs using Gaia-GALEX-WISE.
    Discover one thousand hypervelocity stars.
    Douglas Boubert (IoA, Cambridge -> Magdalen College, Oxford)
    Hope to learn: Machine learning 102,
    planet/star problems with Gaia, how to
    use Bayes on Gaia-scale problems.
    What I bring:
    ● Battlefield experience with the
    “features” of Stan/MultiNest.
    ● Bayesian treatment of Gaia
    correlations and parallax->distances.
    ● Single and binary stellar population synthesis.
    Hypervelocity stars
    (might...)
    come from here.

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  20. Cecilia Mateu
    What I bring:
    ● Knowledge on RR Lyraes (+data)
    ● Stream search with pole counts
    (+PyMGC3 code)
    ● GALSTREAMS library of MW
    streams' footprints
    Hope to do:
    ● Search for streams in Gaia DR2 using
    nGC3 pole counts + RR Lyrae/RC/etc.
    ● Calibrate RR Lyrae distances in G
    band (+ Oosterhoff type indicator
    = evolutionary proxy)
    Hope to learn/get help with:
    ● How to define a selection
    function for streams
    ● Bayesian Period-Luminosity
    calibration for RR Lyraes

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  21. Yuan-Sen TING
    IAS Princeton Princeton University Carnegie Observatories
    ● Constraining the vertical
    heating of the Milky Way disk
    ● Photometric/data-driven
    [α/Fe]-[Fe/H] for 20 million stars
    Galex + Gaia + WISE
    ● ● ●
    Age indicators
    “Upside down”
    formation
    Satellite
    harassment

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  22. Matthew Buckley (Rutgers University)
    Hope to do: End-goal: Understand the dark matter substructure in the Milky Way,
    measuring the number of substructure objects as a function of their mass. Turn
    this into constraints on dark matter particle physics.
    Hope to learn: Can we use the Gaia data to measure substructure’s phase-space
    volume, and relate that to its mass? Can we distinguish globular clusters from
    dwarf galaxies? What else can GAIA do for dark matter particle physics?
    What I bring: Some python skills, dark matter particle physics and astrophysics, a
    charming naivety about non-dark-matter-astronomy.

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  23. Kareem El-Badry (UC Berkeley)
    Hope to learn
    ● your projects
    ● artifacts
    ● completeness
    functions
    What I bring
    ● binaries, big and small
    ● white dwarf models
    ● short attention span
    ● scripts to submit 1000s of
    ADQL queries & bring ESA
    server to its knees
    Hope to do
    ● Binaries
    ○ MS/MS, WD/MS,
    WD/WD
    ● separation distribution
    ● [Fe/H] dependence

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  24. Daniel Michalik (post-doc@ESA, DPAC-CU3)
    Hope to do: Find new ways of looking at the DR2 data; exchange methods and
    knowledge; watch Kareem bring the ESA server to its knees; think about the
    detection of long-period binaries (50-500 yr) in astrometry data
    Hope to learn: Issues with the DR1 and DR2 datasets; how to exploit
    uncertainties astrophysically (i.e. finding RR-Lyrae from photometry uncertainties);
    error bar calculation for non-Gaussian uncertainties
    What I bring: Experience with the Gaia astrometric solution; detailed
    understanding of TGAS and astrometric catalogue combinations; experience with
    cluster membership searches in DR2

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  25. KU Leuven
    ● Density estimation of fuzzy data: what
    are the most stringent constraints we
    can put on the structure of the inner
    halo with GDR2 data, given the
    observational uncertainties?
    ● How can we quantify and visualize the
    uncertainty on 3D density
    (sub)structures?
    ● Gaia's selection function
    ● Efficiently dealing with Gaia
    samples that no longer fit in
    memory.
    ● Python, C++
    ● Hands-on experience with Bayesian
    regression, model comparison, ...
    ● Supervised classification, clustering
    ● Variable stars

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  26. Morgan Fouesneau
    Hope to do
    ● Find co-moving
    WD-WD, WD-MS
    systems to construct
    MW star formation
    history(-ies)
    Hope to learn
    ● All the things
    DPAC (we) did
    wrong! [feedback]
    ● something new
    about the
    Milky-Way from
    Gaia.
    What I bring
    ● Some limited Gaia
    knowledge [DPAC]
    ● ADQL help
    tutorial mfouesneau/tap
    ● Dust attenuated
    SED simulations
    Tools & tutorial [specs. & phot.]
    mfouesneau/GaiaSprint2018
    Expect to do
    ● totally different
    projects triggered
    by discussions
    MPIA (Heidelberg) - Gaia DPAC [CU8]

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  27. Sven Buder
    MPIA, Heidelberg - The GALAH survey
    What I bring / expertise
    Stellar Spectroscopy
    GALAH DR2 (arXiv:1804.06041):
    340,000 stars, ≤ 23 abundances
    99.8 % overlap with Gaia DR2
    86 % with ϖ-unc. < 10%,
    ADQL X-matches 2MASS,WISE...
    Hope to do
    ● Low-[Fe/H] stars
    and their actions
    ● Counter-rotating
    halo?
    Hope to learn
    ● Analysing/dissecting
    action-abundance space
    ● How to get this in a short
    paper?

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  28. Ellianna Schwab Abrahams (AMNH, UC Berkeley)
    Hope to do: Use dust maps of the Kepler field as Bayesian priors to calculate
    better distances, absolute magnitudes etc. Make better crossmatches between
    faint stars in Gaia + other catalogs than the ones provided by ESA.
    Hope to learn: What is the best practices for calculating distance probabilities in a
    Bayesian way for a limited sample of stars (rather than modeling the entire
    galaxy)?
    What I bring: General low-mass star knowledge. Enthusiasm. Kepler + Gaia
    crossmatch.

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  29. TO DO & TO LEARN:
    - Look at all globular clusters; where are
    the tidal tails?
    - Action & angle-space disk substructure?
    - Wide binary separation as a fn of Jz?
    - Where are the spiral arms?
    TO BRING:
    - Gaia subsets for MW globular clusters
    - Python , stats , dynamics
    - Snarkyness & emotional support
    Adrian Price-Whelan (Princeton)

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  31. Boris Leistedt (NYU)
    Hope to do:
    Improved parallaxes with velocity marginalization
    CMD + 2D/3D dust maps without stellar models
    Hope to learn:
    Galaxy dynamics, white dwarf populations
    What I bring:
    Unconditional emotional support (impostor syndrome: sashay away!)
    File-by-file split of 2MASS-SDSS-PS1 cross-matches + filtering scripts
    Expertise in statistics and (very) large Bayesian inference problems

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  32. Nathan W. C. Leigh (AMNH, SBU)
    Hope to do: Constrain the origins of hypervelocity stars with a Galactic Center
    origin (i.e., “answer” the question: is there an IMBH in the Galactic Center?). I
    bring ARCHAIN models for the competing theoretical formation mechanisms.
    Hope to learn: The secrets of the Universe (all of them).
    What I do: I make (often abstract) models that describe simulated data.
    Dynamics (chaotic, secular, mostly in the collisional regime), gravity integrators,
    weird stellar populations (e.g., blue stragglers, sub-subgiant branch stars, etc.),
    multiple star systems (especially triples)

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  33. Hamish Silverwood Institute of Cosmos Sciences, University of Barcelona (ICCUB)
    Hope to do: Start new projects related to dark matter and galactic dynamics.
    Explore disequilibria features in DR2 and simulations. Push forward Local DM
    density project.
    Hope to learn: How to find the coldest White Dwarfs and derive temperatures and
    luminosities (which can be used to search for WIMP DM capture and annihilation).
    Anything and everything about disequilibria.
    What I bring:
    Knowledge and Expertise: Local DM density determinations, direct and indirect
    DM detection, Jeans modelling and galactic dynamics, Bayesian fits and
    MultiNest.
    Code and Data: 2D integrated Jeans code (GravImage2D). Code skeleton and
    Docker image for MultiNest. N-body mock data sets of MW type galaxy, with and
    without satellite mergers - old simulations but they have nice spirals, warps, flaring.
    ...and “Kiwi Goodness” according to the anonymous wit who came across my draft slide.
    z
    v
    Z

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  34. Federica Spoto IMCCE (Paris Observatory) - Gaia DPAC [CU4, CU9]
    Hope to do
    New astrometric catalog
    correction for asteroid
    observations using Gaia DR2
    as reference
    Hope to learn
    Cross-match between Gaia
    and external catalogs
    Issues with DR2 dataset
    ADQL queries
    ….
    As much as possible from
    all of you!
    What I bring
    Asteroids in DR2
    and beyond: astrometry, orbits,
    possible impacts
    (the funny stuff!)
    14099
    asteroids in
    Gaia DR2
    Credit:
    ESA/Gaia/DPAC/
    P.Tanga, F.Spoto

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  36. Natalie Price-Jones (UToronto, Dunlap)
    Hope to do:
    - spectral space
    chemical tagging
    with DBSCAN on
    the DR2 x
    APOGEE overlap
    - validation on
    known DR2 OCs
    Hope to learn:
    - methods to
    handle high
    dimensional data
    - new clustering
    algorithms
    - more about
    machine learning!
    What I bring:
    - clustering algorithm expertise
    - help accessing APOGEE data
    - excitement!

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  37. Jason Hunt (Dunlap Institute, Toronto)
    Hope to do: Take a look at the kinematic substructure around the spiral arms, and
    the ridges in the velocity distribution.
    Hope to learn: How to get trustworthy distances, and understand uncertainties /
    biases in the bayesian distance estimates. Working with actions.
    What I bring: General dynamics knowledge, brief former member of Gaia DPAC
    radial velocity team. I can also make mock Gaia data from your galaxy models if
    anyone still want to do that!

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  38. Neige Frankel (MPIA)
    Hope to do:
    Quantify: how much churning VS blurring in the Galactic disk?
    Hope to learn:
    Selection function APOGEE-RC x Gaia DR2
    Do orbital actions have errors?
    What I bring:
    A radial migration model for the Milky Way disk
    (https://arxiv.org/abs/1805.09198)

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  39. Axel Widmark
    Hope to do: White dwarf population statistics, unresolved multiple stellar
    systems, dynamical matter density measurements
    Hope to learn: Everything and Gaia systematics (completeness, selection
    effects, etc.)
    What I bring: Experience with Bayesian hierarchical models and
    astrostatistics

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  40. Dan Foreman-Mackey
    Flatiron
    bring
    learn
    do
    data_analysis_tools. time
    series. tensorflow.
    gaia. stars. etc.
    special purpose isochrone
    fitting tool w/ tensorflow
    and hmc.

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  41. Eleonora Zari - Leiden Observatory
    Hope to do: 3D density map of young stars in the solar neighbourhood.
    Hope to learn:
    clustering algorithms.
    What I bring: general
    knowledge of star
    formation; photometry,
    ages (isochrone fitting),
    kinematic modelling of
    (young) moving groups.
    l [deg]
    b [deg]
    360 0
    -90
    90

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  43. Eileen Gonzales (CUNY, AMNH)
    Hope to do: Improve on the abs mags vs spectral type relations for subdwarfs.
    Potentially enlarge the sample of subdwarfs with fundamental parameters.
    What I bring: How to use the BDNYC Database and SEDkit to determine
    fundamental parameters of brown dwarfs, knowledge about subdwarfs and brown
    dwarfs
    What I want to learn: More about Gaia, what its lower limit is for faint sources,
    and other cool stuff about python.

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  44. Ting Li (Fermilab)
    Hope to do: Kinematics on stellar streams and stellar overdensities in the MW.
    Relations between VOD, HerAq, EriPhe overdensities?
    Hope to learn: Science that I’m not working on. Dynamical modeling/fitting with
    6D or 4-5D phase space info. Cool Science results/plots.
    What I bring: Anything about DES DR1. LOSV from spectroscopic observations
    on streams and dwarf galaxies. Cool science results. AAT observing TONIGHT!
    KICP workshop on Jun 27-29 if you are
    interested in DES DR1 and other DECam
    data, and synergy with Gaia. Registration is
    full but email or talk to me ([email protected]) at
    the sprint.
    Appear on arxiv this week

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  45. KATELIN SCHUTZ, GRADUATE STUDENT @ UC BERKELEY
    ● My aim is to continue in the
    spirit of looking for unique
    signatures of “non-vanilla” dark
    matter interactions by looking
    for distinct morphologies and
    substructure
    ● I have lots of ideas and my
    motto is “fail faster.” I think it
    could be fun to kill some of
    these ideas or see them
    develop if we manage not
    to kill them.
    ● My background is in particle
    theory and cosmology so I
    am eager to learn all I can
    about what can reasonably
    be done with this dataset--
    both in terms of limitations
    of the data and other
    complications from the
    baryonic side
    ● I have experience with Gaia data
    (DR1) doing a Holmberg & Flynn
    type analysis to search for a thin
    dark matter disk
    ← my face if you want to
    find me and chat! If you
    can’t find me my email is
    [email protected]

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  46. Borja Anguiano (University of Virginia)
    APOGEE Inter-Survey Science Chair
    Hope to do: Tilt angle of the velocity ellipsoid as a function of height
    |Z| away from the mid-plane using Gaia DR2.
    Hope to learn: How to get reliable individual space velocities **and
    their uncertainties** from Gaia measurements **-covariances-**
    What I bring: I can be helpful with the latest data releases from
    APOGEE, GALAH, RAVE and their data products.

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  48. Ted Mackereth
    (Liverpool John Moores University, UK)
    Hope To: Work out what’s going on with this stuff!
    Want to learn: How to use Gaia more carefully, more
    about dynamical modelling, and what is this dark matter
    thing, anyway? Also, MW Halo anyone??
    I bring:
    - a bit of knowledge about galpy (Fast orbit
    parameter/ action estimation, coordinate
    transforms)
    - A catalogue of actions/angles/orbits/freqs
    (+uncertainties!) for Gaia RV sample
    - APOGEE knowledge (selection function!)
    - Numerical simulations and analysis of them (in the
    interests of Gaia science!)
    Would love to collaborate on funky stuff i’ve never
    done before!

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  50. Daniella C. Bardalez Gagliuffi (AMNH)
    Hope to do: (1) Find planets orbiting brown dwarfs/low mass stars using the
    astrometric excess noise and other flags (2) Clean up the 25pc sample (3) Find
    triple systems as comovers to tight brown dwarf binary systems
    Hope to learn: The caveats of Gaia data and quality cuts, i.e. what is a real Gaia
    source and what’s not. Cool python/pandas tricks to make code more efficient.
    What I bring: lots of brown dwarf and binary systems chatter, non-pretty IDL/Python
    code to identify and characterize unresolved spectral binaries of brown dwarfs,
    SPLAT, SpeX spectra, moral support :)

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  51. Ruth Angus
    (Columbia)
    Do: IS THIS REAL? Investigate exoplanet occurrence rate as a function of vertical action. Compile
    metallicities from literature, etc. Convert Jz to age. Do young multis look different to old multis?
    Learn: what is The Best Way to calculate vertical actions with uncertainties for Gaia stars (and how well
    can you approximate this for Kepler stars without RVs?)?
    Bring: methods and code for measuring ages of main sequence stars.
    All planets Single planets Multiple planets

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  52. Lina Necib, Caltech
    I am interested in understanding the properties of dark matter from the stars.
    Hope to do: Interested in the completeness function of DR2, so I can make the local density
    distribution of the stars.
    Hope to learn: More about the measurements of the stars in dwarf galaxies.
    What I bring: I worked on the velocity distribution of metal poor stars, so always happy to discuss
    related topics: Mergers of the Milky Way, dynamics of the stellar halo, properties of the stars, etc...
    I am happy to have any particle physics/dark matter-related topics!

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  53. I would like to improve this ginormous hierarchical model of
    the Cepheid distance ladder using Gaia data. I would also like
    to help nice people do cool things. I know about model
    selection & assessment, Stan, MultiNest, PolyChord, likelihood-
    free inference and the crushing superiority of tea to coffee.
    Hello my
    name is
    Stephen
    Feeney
    and I
    work at
    the
    Flatiron
    Institute

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  54. Eddie Schlafly (LBL)
    Hope to do: Make new measurements of the extinction curve. Measure
    extinction rather than reddening, and add Gaia bands.
    Hope to learn: When to be skeptical of Gaia data. Comparison of Gaia distances
    and red clump distances show more scatter than I expected; help please!
    What I bring: Lots of dust. Its 3D structure and properties. Expertise in
    photometric data sets like PS1, the Legacy Survey, and the DECam Plane
    Survey. Modeling and analysis of data.

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  55. Rocio Kiman
    (The Graduate Center, CUNY; AMNH)
    Want to do: Find M-dwarfs in Gaia DR2. Map the galaxy in spt
    density and study the mass function. Estimate what
    percentage of M-dwarfs SDSS observes.
    Want to Learn: Cares when working with Gaia data (flags,
    parallaxes, etc.).
    Can help with: Gaia Data Queries and cross-matches.

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  56. Sanjib Sharma (University of Sydney, Australia)
    Hope to do:
    ● Checking the asteroseismic scaling relations using Gaia parallaxes.
    ● Anisotropy profile and dynamical modelling of the stellar halo using SEGUE
    data and GAIA DR2 proper motions.
    ● Fast methods to compute better distances from GAIA DR2, making use of prior
    information from isochrones and or proper motions.
    Want to learn: New ideas in Bayesian Nonparametric modelling, neural networks
    and proper treatment of uncertainties in GAIA DR2.
    What I bring:
    ● A new improved version of BMCMC, an MCMC code for Bayesian data
    analysis with ability to solve hierarchical models.
    ● Expertise with, GALAH , mock catalogs (Galaxia), selection function of
    GALAH, RAVE, Kepler, K2GAP, Bayesian estimation of stellar parameters.
    ● Efficient handling of large data sets with EBF file format.

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  57. Sarah Loebman (UC Davis)
    What I bring:
    ● Ananke: Gaia mock catalogs generated
    from the Latte simulations.
    ● Simulation insight in radial migration,
    thick disk formation, dark matter
    distribution, & stellar halo dynamics.
    Hope to learn (from you!):
    ● How to select, crossmatch, and understand errors for BHB stars.
    ● Ages of GALAH stars? Would love to hear about the Cannon applied to this sample.
    Hope to do:
    ● Poke at the stellar halo’s velocity anisotropy profile (β) for different metallicity stars
    ● Explore connections between chemistry & kinematics in disk via GALAH-Gaia &
    hunt for radially migrating stars.
    3 color image from Ananke (m12i)

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  58. Debris stars in M67, Pleiades and the Orion Complex
    with Gaia DR2 and APOGEE
    Elena D’Onghia & Boquan Chen
    University of Wisconsin-Madison
    Questions:
    ● How does star formation occur in open clusters? In dense regions or
    hierarchically?
    ● How do open clusters evolve and dissolve?
    ● Can we identify new open clusters in the Milky Way disk?
    What we Bring: Customized Shared Nearest Neighbors (SNN) clustering and other
    clustering algorithms in Python, Insight on simulations of dynamics
    What we hope to learn: whether we can learn about stellar ages and masses and how
    to better constrain star forming regions
    What we hope to do: find new open cluster candidates based on our algorithm.

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  59. Chemo-Dynamical Tagging with
    SNN Applied to APOGEE and Gaia
    DR2 Crossmatch Data
    SNN Applied to 5-D Data In The Orion Field In Gaia DR2
    Boquan Chen, University of Wisconsin-Madison

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  60. Melissa Ness
    Do: can I predict Lz from stellar spectra?
    Learn: different modeling approaches, error
    propagation in action space
    Bring: experience with spectra - APOGEE, GALAH,
    LAMOST and tools - The Cannon
    (Columbia/Flatiron)

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  61. Chao Liu
    (National Astronomical Observatories, CAS)
    Hope to do:
    Hope to learn:
    What I bring:
    - (Hierarchical) Bayesian models based on the Gaia measured quantities
    (e.g. parallaxes, proper motions and photometries)
    - kinematic and dynamical properties of the Galactic disk, local dark
    matter density
    - looking for N-body simulations with dwarf galaxy perturbations so that
    we can compare with our observed result in the outer disk
    LAMOST data and our latest view of the Galactic outer disk structure
    extending to 20 kpc (1804.10485), the anisotropy of the stellar halo
    (1805.04503) and the rotational stellar halo (1805.08326)
    Distributions of the mass-ratio (q) of binarities as a function of metallicity
    and mass of primary stars (m). As a first step, I will firstly focus on the
    unresolved solar-like binarities (with shorter periods) from LAMOST+Gaia
    within a few hundreds parsecs. Then I will extend to longer periods by
    searching wide binaries in the similar volume.
    q
    m1

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  62. Ken Van Tilburg (NYU & IAS)
    Hope to do: Look for astrometric, weak gravitational lensing by dark matter
    substructures in the Milky Way, using templates for the lensing-induced proper
    motion of background sources.
    Hope to learn: Real and fictitious proper motion correlations in DR2; covariance
    in astrometric parameters of nearby sources; how to deal with extreme outliers in
    the astrometric data.
    What I bring: Particle physics background, expertise in microphysics of dark
    matter models.

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  63. Sergey Koposov (CMU)
    Hope to do: Binary separation distribution,
    Binary mass ratio distribution, dependence of
    binary fraction on metallicity and stellar population.
    Wide binary disruption limit. Also: I’m interested in
    removing GDR2 parallax systematics.
    Hope to learn: Stuff
    What I bring: Access to a large SQL database
    with major surveys (ask me)
    Some expertise in SQL/Python/Stan/Gaia
    log10(Separation/1pc)

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  64. Vasily Belokurov (Cambridge, UK and CCA, New York)
    I would like to figure out sub-structure in the inner 3 kpc of the Galaxy. I bring
    ideas. I hope to learn how to mix stellar evolution and Galactic dynamics

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  65. Padawan looking
    for deep learning
    master

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  66. Robyn Sanderson (Caltech)
    ananke • girder.hub.yt

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  67. Visualizing Gaia Data
    Jackie Faherty, AMNH
    Thursday June 7 at 6pm, Hayden Planetarium Dome!
    If there is a dataset you have that you want visualized, talk to me ASAP

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  68. Sarah Pearson (Columbia University)
    Hope to do:
    Hope to learn:
    What I bring:
    Characterize the stellar stream of
    Palomar 5 in Gaia and search for the
    potential extension of its leading
    arm
    The science being done with Gaia
    data and to swap “stream-
    finding” strategies.
    Knowledge on galactic dynamics and stream
    modeling techniques
    Left: The Pal 5 stream as seen in Pan-STARRS.
    Right: Pal 5 evolved in potential with a rotating bar.
    Red circles: potential extension of the leading arm.

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  69. Keith Hawkins (Columbia Univ./UT Austin)
    Hope to do:
    Hope to learn:
    What I bring:
    ● Determine empirically how
    color and metallicity effect the
    abs. Mag of RC
    ● Do Chemical Cartography/tag
    in various elements (e.g. Ba
    seems to be enhanced in outer
    galaxy)
    GMM in STAN; Best
    distance/velocity practices
    Expertise in spectroscopic
    surveys / abundances/RC stars
    and standard candles
    2
    1

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  70. Kathryn V Johnston (Columbia University)
    Hope to do:
    Hope to learn:
    What I bring:
    ● M31 proper motion - writing (leads: David Hendel and Andy Tzanidakis)
    ● Contributions to
    ○ Pal 5 interpretation (lead: Sarah Pearson)
    ○ Outer disk projects (leads: Chervin Laporte, Adrian Price-Whelan)
    ○ abundances/dynamics (leads: Keith Hawkins, Moiya McTier, Melissa
    Ness)
    More about disk sub-structures - properties and intuition for
    interpretation
    Enthusiasm!
    Experience: dynamics of streams and outer disk; populations and
    abundances.

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  71. Chervin Laporte (University of Victoria)
    Hope to do:
    Hope to learn:
    What I bring:
    Finish paper on Anticenter d~10 kpc and start modeling ACS:
    1. Improve current Density/PM maps of Galaxy d~10 kpc using MSTOs,
    RC, RGB (see also Adrian leading work on extending maps as a
    function of distance)
    2. Use GOG/Galaxia remove contaminants in current maps -> better
    interpret/dissect signal on global breathing signal of disc + signs of
    spiral arms towards Galactic center & kinematics of substructure in
    Monoceros.
    3. Fitting a model to the ACS “stream” (tidal tail)
    Bayesian methods to fit orbit to streams
    Many results on density + pml, pmb maps in MSTOs, RCs,
    RGBs for disc at 10 kpc + selections of individual tracers
    (RC+RGB) along ACS over 160 degrees
    Numerical simulations to interpret results/signals (useful maybe
    for other people working on disc perturbations)
    MSTOs DR2
    RCs median mub
    Simulations MW+Sgr

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  72. View Slide

  73. Alcione Mora (ESA-ESAC)
    ● Hope to do:
    ○ Science, especially if far from comfort zone (star formation, exoplanets)
    ○ Acquaintances, met very interesting people in 2016 NYC sprint
    ● Want to learn:
    ○ How astronomers work with Gaia data (Archive, local DB, Spark?)
    ○ How to improve the Archive to better serve community
    ○ Hot topics after DR2
    ○ Prepare for Gaia ESAC exploration lab
    ● Plan to bring:
    ○ Gaia Archive and hardware expertise
    ○ Enthusiasm, amazement

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  74. Rachael Beaton (Princeton,Carnegie Observatories)
    ● I hope to do:
    ○ Time Resolved Stellar Parameters & Chemical Abundances for high
    precision Variable Stars with APOGEE data (it works! see right) -- try
    to estimate Extinction from DIBs.
    ○ Think about Baade-Wesselink method in the light of Gaia.
    ○ Convince folks here to make their awesome codes run on APOGEE
    DR14 into official Value-Added-Catalogs for APOGEE DR16!
    (ahem, Kareem, Ted, Adrian, Yuan-Sen, among others ... )
    ● I need to learn:
    ○ Proper way to think about Gaia systematics for luminosity
    calibration.
    ○ How you use APOGEE so that we can make it better, stronger,
    friendlier, better documented, better calibrated,
    ● I bring:
    ○ Scary amount of knowledge about APOGEE (esp. known problems in DR14)
    ○ Lots of thinking/doing/observing to prepare for the (Extra)Galactic
    Distance Scale as anchored by Gaia.
    Co-Chair, APOGEE-2 Science Working Group
    Surface Gravity
    log(g)
    Metallicity
    [M/H]
    Effective
    Temperature

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  75. View Slide

  76. Andy Casey
    Monash University (Melbourne, Australia)
    do Infer properties of binary systems from Gaia data (RV
    error, lack of RVs, photometry, astrometric noise).
    There are millions of binaries from any of these data!
    Binarity in the field/clusters; w.r.t. stellar [Fe/H];
    stellar-mass black hole companions.
    No fear in asking dumb questions.
    Expertise in data analysis, stars, etc.
    How should I responsibly interpret Gaia
    housekeeping data?
    learn
    bring

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  77. Matthew Wilde University of Washington
    Hope to do: galactic structure in the halo, star formation history of the galaxy,
    work with awesome people.
    Hope to learn: everything cool being done with Gaia! Best practices and pitfalls.
    All of this “Bayes” stuff people keep talking about.
    What I bring: lots of (probably dumb) questions, mediocre coding, ML, and data
    viz (d3) skills.

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  78. Colin Slater
    University of Washington
    What’s the deal with the outer Galactic disk? Monoceros,
    Tri-And, warps, flares, etc.; what are all these things, and why
    are they there?
    Use proper motion + every other useful parameter to dissect
    the disk.
    A mild obsession with making all-sky maps of the MW, and
    the infrastructure to do so.
    Hope to learn:
    Hope to do:
    What I bring:

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  79. Oren Slone
    Princeton University
    Hope to answer the question
    “Is there a Vertical Acceleration Relation?”
    by
    Comparing local solutions of the Jeans and
    Poisson Equations
    I bring to the Sprint
    a background in Dark Matter pheno
    McGaugh et. al.
    The Radial Acceleration Relation

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  80. Lauren Anderson - Flatiron Institute
    Bring - knowledge about gaia DR2 data, bayesian inference, hierarchical models, data viz
    Learn - dynamics, dust
    CMD as f(phase space) halo substructure via RR lyrae
    Do

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  81. View Slide

  82. Luke Zoltan Kelley
    Do
    - Calculate a Gaia Gravitational Wave Limit
    Learn
    - Systematics characterization & modeling
    (i.e. the BAM wiggle)
    Bring
    - Bandwagon ripe
    for jumping on
    - Keen misunderstanding
    of basic statistics
    - General knowledge of
    high-energy & transient
    phenom irrelevant to Gaia
    [email protected]
    Harvard CfA ⇒ Northwestern CIERA
    Gravitational Waves, Gaia & You!

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  83. David Hendel
    Columbia University University of Toronto
    Hope to do: measure the proper motion of
    Andromeda using PS1/2MASS-selected stars
    (w/ Kathryn Johnston, Andy Tzanidakis, you???)
    Hope to learn: how to build a mixture model for
    M31+contaminants, best practices for selection
    from CMDs
    What I bring: galactic and stream dynamics
    knowledge, lots of minor merger N-body
    simulations
    Also interested in: streams, substructure, the stellar halo, RR Lyrae
    Andy Tzanidakis

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  84. Sihao Cheng (Johns Hopkins University)
    Hope to do: Measure the amount of dust outside disk with RR Lyrae.
    Hope to learn: I am very interested in the bifurcation of Sagittarius Stream,
    structures and dynamics in Milky-way etc. Gaia parallax systematics. Purity and
    completeness of the RR Lyrae sample.
    What I bring: some knowledge of RR Lyrae, enthusiasm to topics of dynamics

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  85. View Slide

  86. Denis Erkal (University of Surrey)
    DO: Extensions of Pal 5 stream (other streams?)
    Search for streams around GCs
    Search for extended debris (dwarfs) around GC streams
    LEARN: Gaia systematics
    Improved isochrone selection
    Things I don’t know
    BRING: Orbits in the presence of the LMC
    Orbits marginalized over MW potential uncertainties
    Orbit/stream modelling of streams
    Knowledge of effect of substructure on tidal streams
    N-body simulation library/expertise
    Pal 5 in GDR2
    Ophiuchus stream

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  87. Richard Galvez (NYU)
    Do / Learn:
    1. Find signs of lensing / velocity anomalies
    2. Join in your cool project idea!
    3. Find applications of machine learning
    4. Hang out and have fun learning new things.
    Bring:
    1. ADQL / SQL magic tricks in accessing gaia data
    2. One weird trick with the machine learnings
    3. Know the ways of the python.
    4. Can make pretty plots.
    5. Inspiring karaoke game.

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  88. Mark Fardal (STScI, UMass)
    Hope to do:
    ➢ Sagittarius stream: how is it moving? What does
    that mean? How far can we trace it?
    ➢ Other streamy stuff: detect tails from known
    globulars? Good proper motions and clean
    evolved-star CMDs for existing streams?
    Measure solar motion?
    Hope to learn: Our current map of the halo. Efficient
    methods for large-area studies. How to use variable
    stars from DR2 (LPV/Miras, RRL). And so, ad infinitum...
    What I bring: some dynamics and statistics. An
    attempt at suppressing proper motion systematics.

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  89. Do:
    ● Look at pair statistics in the Solar neighborhood
    as a function of color
    ● Compare nearby open cluster morphology
    (... or possibly something else)
    Semyeong Oh (Princeton)
    /se-mjʌŋ/
    Learn:
    ● stellar multiple (binaries – star clusters) formation and disruption
    ● Gaia DR2 limitations
    Bring:
    ● experience with data analysis / visualization tools

    View Slide