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LSST cadence and Superovae

federica
April 04, 2018
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LSST cadence and Superovae

talk given at EWASS 2018 on LSST cadence and its prosepects for SN studies

federica

April 04, 2018
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  1. LSST cadence for
    Supernovae
    federica b. bianco, NYU
    Science Collaborations Coordinator, LSST
    LSST Transient and Variable Stars Science Collaborations Co-Chair
    @fedhere fedhere
    and

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  2. Large Synoptic Survey Telescope
    LSST
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV

    View full-size slide

  3. federica bianco NYU
    LSST
    2022-2032
    Wide-Deep-Fast
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV
    75-95% total time

    View full-size slide

  4. federica bianco NYU
    LSST
    2022-2032
    Wide-Deep-Fast
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV
    cover large swaths of sky
    75-95% total time

    View full-size slide

  5. federica bianco NYU
    cover large swaths of sky to faint magnitudes
    LSST
    2022-2032
    Wide-Deep-Fast
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV
    75-95% total time

    View full-size slide

  6. federica bianco NYU
    cover large swaths of sky to faint magnitudes in a short amount of time
    LSST
    2022-2032
    Wide-Deep-Fast
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV
    75-95% total time

    View full-size slide

  7. federica bianco NYU
    cover large swaths of sky to faint magnitudes repeatedly at short intervals
    LSST
    2022-2032
    LSST
    2022-2032
    effective aperture of 6.7 m
    FoV 9.6 deg2
    large etendue :
    collecting area x FoV
    2022-2032
    Wide-Deep-Fast 75-95% total time

    View full-size slide

  8. 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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  9. 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 - supernovae

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

    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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  10. federica bianco NYU
    Color
    single-filter
    cadence density
    Regular/persistent
    WIDE
    DEEP
    Fast/Dense
    LSST constrained optimization problem and the SCs
    https://github.com/LSSTScienceCollaborations/ObservingStrategy
    https://arxiv.org/pdf/1708.04058.pdf

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  11. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    LSST Cadence
    questions a SN
    scientist should
    ask:

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  12. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Can we study SNe from LSST Data Products?
    Can we classify She from LSST Prompt Release data?
    Can we follow-up the SN? (faint and many!)
    LSST Cadence
    questions a SN
    scientist should
    ask:

    View full-size slide

  13. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Can we study SNe from LSST Data Products?
    Can we classify SNe from LSST Prompt Release data?
    Can we follow-up the SN? (faint and many!)
    LSST Cadence
    questions a SN
    scientist should
    ask:

    View full-size slide

  14. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Can we study SNe from LSST Data Products?
    Can we classify SNe from LSST Prompt Release data?
    Can we follow-up the SN? (faint and many!)
    LSST Cadence
    questions a SN
    scientist should
    ask:

    View full-size slide

  15. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Can we study SNe from LSST Data Products?
    Can we classify SNe from LSST Prompt Release data?
    Can we follow-up the SN? (faint and many!)

    View full-size slide

  16. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Wide-Deep-Fast (75-95% total time)
    LSST Cadence

    View full-size slide

  17. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Wide-Deep-Fast (75-95% total time)
    Minisurveys
    LSST Cadence

    View full-size slide

  18. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Wide-Deep-Fast (75-95% total time)
    Minisurveys
    Deep Drilling Fields
    LSST Cadence

    View full-size slide

  19. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Wide-Deep-Fast
    (85.1%)
    Baseline Cadence: Minion1016

    View full-size slide

  20. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    North Ecliptic
    Survey (6.5%)
    The NES is an
    extension to reach
    the Ecliptic at
    higher airmass
    than the WFD
    survey typically
    covers, no u
    Wide-Deep-Fast
    (85.1%)
    Baseline Cadence: Minion1016

    View full-size slide

  21. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    North Ecliptic
    Survey (6.5%)
    The NES is an
    extension to reach
    the Ecliptic at
    higher airmass
    than the WFD
    survey typically
    covers, no u
    South Celestial Pole (2.2%): higher airmass
    decl>−65 degrees. includes ugrizy, but takes
    fewer exposures/field than the WFD and does
    not collect in pairs.
    Wide-Deep-Fast
    (85.1%)
    Baseline Cadence: Minion1016

    View full-size slide

  22. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Galactic Plane (1.7%):
    covers the region where
    LSST is expected to be
    highly confused by the
    density of stellar sources;
    fewer total exposures/
    field and does not collect
    in pairs
    North Ecliptic
    Survey (6.5%)
    The NES is an
    extension to reach
    the Ecliptic at
    higher airmass
    than the WFD
    survey typically
    covers, no u
    South Celestial Pole (2.2%): higher airmass
    decl>−65 degrees. includes ugrizy, but takes
    fewer exposures/field than the WFD and does
    not collect in pairs.
    Wide-Deep-Fast
    (85.1%)
    Baseline Cadence: Minion1016

    View full-size slide

  23. federica bianco NYU
    LSST
    2022-2032
    LSST
    2022-2032
    2022-2032
    Deep Drilling Fields
    DDF (4.5%)
    North Ecliptic
    Survey
    The NES is an
    extension to reach
    the Ecliptic at
    higher airmass
    than the WFD
    survey typically
    covers, no u
    Galactic Plane (1.7%):
    covers the region where
    LSST is expected to be
    highly confused by the
    density of stellar sources;
    fewer total exposures/
    field and does not collect
    in pairs
    South Celestial Pole (2.2%): higher airmass
    decl>−65 degrees. includes ugrizy, but takes
    fewer exposures/field than the WFD and does
    not collect in pairs.
    Wide-Deep-Fast
    (85.1%)
    Baseline Cadence: Minion1016

    View full-size slide

  24. federica bianco NYU
    Baseline Cadence: Minion1016
    Fraction of SNe Ia detected pre-peak at z=0.5

    View full-size slide

  25. federica bianco NYU
    Baseline Cadence: Minion1016 inter- and intra-night gap

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  26. federica bianco NYU
    Median Inter-Night Gap (days)
    Median Intra-Night Gap (hours)
    any filter
    any filter
    Alternative Cadences: inter- and intra-night gap
    Chapter

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  27. federica bianco NYU
    Median Inter-Night Gap (days)
    Median Intra-Night Gap (hours)
    Chapter
    single filter: r
    single filter: r
    Alternative Cadences: inter- and intra-night gap

    View full-size slide

  28. federica bianco NYU
    Median Inter-Night Gap (days)
    Median Intra-Night Gap (hours)
    Chapter
    single filter: r
    single filter: r
    Alternative Cadences: inter- and intra-night gap

    View full-size slide

  29. federica bianco NYU
    Can we classify SNe from LSST Prompt Release data?

    View full-size slide

  30. time... in seconds

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  31. federica bianco NYU
    Transients’ similarity measured as the
    Euclidean distance between the magnitude
    change of each transient’s pair
    represented in log scale
    black -> |∆Mag1
    − ∆Mag2
    | ∼ 8
    white -> |∆Mag1
    − ∆Mag2
    | ∼ 0
    Chapter
    Can we classify SNe from LSST Prompt Release data?

    View full-size slide

  32. federica bianco NYU
    Transients’ similarity measured as the
    Euclidean distance between the magnitude
    change of each transient’s pair
    represented in log scale
    black -> |∆Mag1
    − ∆Mag2
    | ∼ 8
    white -> |∆Mag1
    − ∆Mag2
    | ∼ 0
    Chapter
    inter-night minutes
    days
    intra-night
    8
    25 25
    30
    Can we classify SNe from LSST Prompt Release data?

    View full-size slide

  33. federica bianco NYU
    Renee Hlozek, Rick Kessler
    Can we classify SNe from LSST Prompt Release data?

    View full-size slide

  34. federica bianco NYU
    Brokers : Antares (Matheson, Narayan ++)
    UK broker (Smartt ++)
    Can we classify SNe from LSST Prompt Release data?

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  35. federica bianco NYU
    Can we classify SNe from LSST Prompt Release data?
    goo.gl/orHKBn
    LSST TVSSC Task Force
    Characterize the functionality needed
    from a community-broker interface
    Brokers : Antares (Matheson, Narayan ++)
    UK broker (Smartt ++)

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  36. federica bianco NYU
    Can we study SNe from LSST Data Products?

    View full-size slide

  37. federica bianco NYU
    Wide Deep Fast
    Can we study SNe from LSST Data Products?

    View full-size slide

  38. federica bianco NYU
    Deep Drilling Fields
    Can we study SNe from LSST Data Products?

    View full-size slide

  39. federica bianco NYU
    days to peak
    days to peak
    flux (units of peak flux)
    flux (units of peak flux)
    Bianco+ 11
    SNLS 3 years:
    ~100 SNe
    5 days color sampling
    we set a 20% upper limit to WD-RG progenitors
    Can we study SNe from LSST Data Products?
    Progenitor studies from light curves - SN Ia example

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  40. federica bianco NYU
    LSST can do constrain a
    5% SD progenitors contribution
    in <=3 months!
    • Create synthetic progenitor populations with a fraction of single
    degenerate progenitor systems 0.05 ≤ fSD ≤ 0.6 in 0.05 intervals and
    random lines of sight with respect to the binary’s geometry.
    • We need 1000 detections within 1 day in 2 filters at a SNR ≥ 7
    Science-Driven Optimization
    of the LSST Observing Strategy
    The LSST Science Collaborations (Marshall+ 2017)

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  41. federica bianco NYU
    LSST compared to other SN-relevant surveys
    5-sigma depth per visit (mag) Single filter gap (days)
    area
    (sq deg)
    u g r i z Y
    104
    102
    103
    10
    26
    20
    23
    0
    20
    10
    Dan Scolnic with Kessler, Biswas, Jha, Hložek, DESC SNWG
    Scolnic+ 2017 ApJ 852,1
    Minion1016

    View full-size slide

  42. federica bianco NYU
    5-sigma depth per visit (mag) Single filter gap (days)
    area
    (sq deg)
    u g r i z Y
    104
    102
    103
    10
    26
    20
    23
    0
    20
    10
    Dan Scolnic with Kessler, Biswas, Jha, Hložek, DESC SNWG
    Scolnic+ 2017 ApJ 852,1
    Minion1016
    LSST compared to other SN-relevant surveys

    View full-size slide

  43. federica bianco NYU
    Rolling Cadences: inter- and intra-night gap
    5-sigma depth per visit (mag) Single filter gap (days)
    area
    (sq deg)
    u g r i z Y
    104
    102
    103
    10
    26
    20
    23
    0
    20
    10
    Dan Scolnic with Kessler, Biswas, Jha, Hložek, DESC SNWG
    Scolnic+ 2017 ApJ 852,1
    Rolling
    cadence

    View full-size slide

  44. federica bianco NYU
    Deep Drilling Fields
    How many?
    What is the cadence?
    What coordinates (galactic vs extragalactic)?
    Current cadence current plan:
    1 DDF/night, 5 filters, total~1hr
    few DDFs/night ~10-15min each
    nightly or every other night
    Sarah Jha, LSST-DESC

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  45. federica bianco NYU
    Call for DDF and MiniSurvey White Paper proposals
    expected in Summer 2018 with a deadline in Fall 2018.
    Good News! You can still change all this!

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  46. federica bianco NYU
    Good News! You can still change all this!
    especially if you are an LSST data rights holder…

    join an LSST Science Collaboration!
    Galaxies
    Michael Cooper (UC Irvine)
    Brant Robertson (University of California, Santa Cruz)
    Stars, Milky Way, and Local Volume
    John Bochanski (Rider University)
    John Gizis (University of Delaware)
    Nitya Jacob Kallivayalil(University of Virginia)
    Solar System
    Megan Schwamb (Gemini Observatory, Northern Operations Center)
    David Trilling (Northern Arizona University) 

    Dark Energy
    Eric Gawiser (Rutgers The State University of New Jersey)
    Phil Marshall (KIPAC)
    Active Galactic Nuclei
    Niel Brandt (Pennsylvania State University)
    Transients and variable stars
    Federica Bianco (New York University)
    Rachel Street (LCO)
    Strong Lensing
    Charles Keeton (Rutgers-The State University of New Jersey)
    Aprajita Verma (Oxford University)
    Informatics and Statistics
    Tom Loredo (Cornell University)
    Chad Schafer (Carnegie Mellon University)
    Currently there are 8 SCs
    ranging in size from ~1000 to ~50 members.

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  47. federica bianco NYU
    Chile 69
    UK: 60
    Italy: 60
    France:45

    California: 174
    Washington: 88
    Pennsylvania: 63
    SC over 100 members, membership across the world
    Good News! You can still change all this!
    especially if you are an LSST data rights holder…

    join an LSST Science Collaboration!

    View full-size slide

  48. federica bianco NYU
    Good News! You can still change all this!
    especially if you are an LSST data rights holder…

    join an LSST Science Collaboration!

    View full-size slide

  49. Somewhere, something incredible is waiting to be known.
    Carl Segan
    [email protected] - LSST SC coordinator, LSST TVSSC co-chair

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