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LSST Transients and Variable Stars Science Collaboration

federica
April 02, 2017

LSST Transients and Variable Stars Science Collaboration

an intro to the Transients and Variable Stars Science Collaboration of the Large Synoptic Survey Telescope (LSST)

federica

April 02, 2017
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  1. Transients and Variable LSST sky
    federica b. bianco, NYU
    The Transient and Variable Stars LSST Collaborations
    @fedhere fedhere

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  2. federica bianco NYU
    Atacama Desert, Cerro Pachon

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  3. federica bianco NYU
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue
    (collecting area x FoV)
    2022-2032

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  4. federica bianco NYU
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue
    (collecting area x FoV)
    Wide-Deep-Fast
    2022-2032

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  5. federica bianco NYU
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue
    (collecting area x FoV)
    2022-2032
    Wide-Deep-Fast
    cover large swaths of sky

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  6. federica bianco NYU
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue
    (collecting area x FoV)
    2022-2032
    Wide-Deep-Fast
    cover large swaths of sky
    to faint magnitudes

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  7. federica bianco NYU
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue
    (collecting area x FoV)
    2022-2032
    Wide-Deep-Fast
    cover large swaths of sky
    to faint magnitudes
    in a short amount of time

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  8. federica bianco NYU
    Innovative Optical Design

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  9. federica bianco NYU
    LSST
    8.4m diameter
    Gemini South
    8m diameter
    0.2 deg2
    MIRROR: FIELD OF VIEW:
    9.6 deg2

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  10. federica bianco NYU

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  11. federica bianco NYU
    3.2 Gigapixels

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  12. federica bianco NYU
    The LSST Data Stream

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  13. federica bianco NYU
    each night is 30TB data
    ■ 30 Terabytes: 1,500,000 trees made into paper and printed;
    The LSST Data Stream

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  14. federica bianco NYU
    each night is 30TB data
    ■ 30 Terabytes: 1,500,000 trees made into paper and printed;
    #OPENDATA #OPENSCIENCE
    The LSST Data Stream

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  15. federica bianco NYU
    each night is 30TB data
    At 1Gbps, 30TB would take 67 hours to download
    the LSST data

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  16. federica bianco NYU
    time... in seconds

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  18. federica bianco NYU
    The LSST Science

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  19. federica bianco NYU
    A stream of 1-10 million time-domain events per night,
    detected and transmitted within 60 seconds of
    observation.
    A catalog of orbits for 6 million bodies in the Solar System.
    A catalog of 37 billion objects: 20B galaxies, 17B stars
    characterized in shape, color, and variability.
    High resolution deep stacks that will allow measure weak
    lensing.

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  20. federica bianco NYU
    Dark energy and dark matter (via measurements of strong and weak lensing,
    large-scale structure, clusters of galaxies, and supernovae)

    Exploring the transient and variable universe

    Studying the structure of the Milky Way galaxy and its neighbors via resolved
    stellar populations

    An inventory of the Solar System, including Near Earth Asteroids and Potential
    Hazardous Objects, Main Belt Asteroids, and Kuiper Belt Objects
    Science Drivers

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  21. federica bianco NYU
    Dark energy and dark matter (via measurements of strong and weak lensing, large-
    scale structure, clusters of galaxies, and supernovae)

    Exploring the transient and variable universe

    Studying the structure of the Milky Way galaxy and its neighbors via resolved
    stellar populations

    An inventory of the Solar System, including Near Earth Asteroids and Potential
    Hazardous Objects, Main Belt Asteroids, and Kuiper Belt Objects moving objects
    Science Drivers
    all relevant to trasients + variable Universe!

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  22. federica bianco NYU
    WFD:
    a pair of images per field, repeated twice/night. ~85% of the observing time
    DeepDrilling fields:
    a pair of images per field, repeated >twice/night >1 band 5-10 DD fields
    Galactic plane survey
    South Celestial Cap
    Northern Ecliptic
    Survey Strategy

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  23. federica bianco NYU

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  24. federica bianco NYU
    https://tvs.science.lsst.org/home
    Ashish Mahabal Federica Bianco
    Transients & Variable Stars
    collaboration co-chairs

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  25. federica bianco NYU

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  26. federica bianco NYU
    Nearly 160 members!
    Each member declares a primary affiliation
    and up to 3 secondary affiliations

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  27. federica bianco NYU

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  28. federica bianco NYU

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  29. federica bianco NYU
    different variable and transient phenomena benefit from different observing strategies
    our group is working to reconcile the differences & understand the existing tensions & overlap
    AGNs
    supernovae
    LBVs
    Roadmapping LSST to success

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  30. federica bianco NYU
    The Time is Now!
    we need a science based evalution
    of the baseline LSST observing strategy and its variants
    Observing Strategy White Paper Secion 1.2

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  31. federica bianco NYU
    The success of TRANSIENTS & VARIABLES related science
    is tied to cadence choices

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  32. federica bianco NYU
    TVS
    ROADMAPPING
    MEETING

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  33. federica bianco NYU
    http://www.slac.stanford.edu/~digel/ObservingStrategy/whitepaper/LSST_Observing_Strategy_White_Paper.pdf
    https://github.com/LSSTScienceCollaborations/ObservingStrategy
    OBSERVING
    STRATEGY
    WHITE PAPER

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  34. federica bianco NYU
    how to contribute
    we need a science based evalution
    of the baseline LSST observing strategy and its variants
    Observing Strategy White Paper Secion 1.2

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  35. federica bianco NYU
    OpSim
    LSST developed operation simulations
    (A. Connoly)
    LSST simulates Observing Strategies

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  36. federica bianco NYU
    OpSim
    LSST developed operation simulations
    (A. Connoly)
    LSST simulates Observing Strategies
    MAF API
    Metric Analysis Framework
    (Peter Yoachim, Lynne Jones)
    https://github.com/LSST-nonproject/

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  37. federica bianco NYU
    OpSim
    LSST developed operation simulations
    (A. Connoly)
    MAF API
    Metric Analysis Framework
    (Peter Yoachim, Lynne Jones)
    SN Alert Fraction
    0.6
    0.0

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  38. federica bianco NYU
    Median Intra-Night Gap in hours
    Any Filter
    Median Intra-Night Gap in hours
    Any Filter
    r band
    r band
    Median Inter-Night Gap in days
    Median Inter-Night Gap in days

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  39. federica bianco NYU
    transients and variables
    from the Observing Strategy White Paper
    preliminary results

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  40. federica bianco NYU
    E. Bellm

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  41. federica bianco NYU
    Tensions:
    color or sampling? (SN/GW vs GRB)
    dense sampling or duration? (SN vs TDE)
    Rolling cadence?
    ToO?
    different variable and transient phenomena benefit from different observing strategies
    our group is working to reconcile the differences & understand the existing tensions & overlap

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  42. federica bianco NYU

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  43. federica bianco NYU

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  46. federica bianco NYU
    Non-Time-Critical

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  47. federica bianco NYU
    days to peak
    days to peak
    flux (units of peak flux)
    Olling+ 15 Marion+ 15
    flux (units of peak flux)
    constraint RG progenitor
    systems to <20%
    (Bianco+ 2012,
    3 year of SNLS data)
    LSST 3 month -> 1%

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  48. federica bianco NYU
    days to peak
    days to peak
    flux (units of peak flux)
    Olling+ 15 Marion+ 15
    constraint RG progenitor
    systems to <20%
    (Bianco+ 2012,
    3 year of SNLS data)
    LSST 3 month -> 1%
    also:
    shock breakout,
    IIB double peaks
    flux (units of peak flux)

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  49. federica bianco NYU

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  50. federica bianco NYU

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  51. federica bianco NYU
    Time-Critical:
    CLASSIFICATION: young/old
    FAST TRANSIENTS: GRB
    GW: counterpart discovery

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  52. federica bianco NYU

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  53. federica bianco NYU
    Days since explosion
    Gap between observations

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  54. federica bianco NYU

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  55. federica bianco NYU
    require 2 observations in 1 week after GW
    detection (Coperthwaite & Berger 2015)
    Median Intra-Night Gap in hours
    r band

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  56. federica bianco NYU

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  57. federica bianco NYU
    Deep Drilling Field

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  58. federica bianco NYU
    Deep Drilling Field
    Wide Deep Fast

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  59. federica bianco NYU
    Transients Classification challenge

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  60. federica bianco NYU
    Transients Classification challenge
    in 2009 Kessler+ issued s SN classification challenge.

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  61. federica bianco NYU
    things that happened since 2009
    Ipad April 2010
    04/21/2016
    instagram 2010

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  62. federica bianco NYU
    we have learned a lot
    since 2010!

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  63. federica bianco NYU
    Michelle Lochner+ 2016
    Anais Moller+ 2016
    Gautham Narayan, Tom Matheson working on ANTARES
    Kevian Stussen @Vanderbilt working on classifiers

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  64. federica bianco NYU
    Transients Classification challenge
    SNLS, SDSSII CSP
    Time for a NEW TRANSIENT CHALLENGE!
    with more data and
    incorporating recent advances in ML
    and this is one of the TVS projects

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  65. federica bianco NYU

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