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Candidacy I slides

Adina
September 26, 2019

Candidacy I slides

Adina

September 26, 2019
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  1. Exploiting TESS data to
    Understand Young Stars
    Adina Feinstein
    NSF Graduate Research Fellow
    Advisors: Jacob Bean & Benjamin Montet
    !1
    Candidacy I September 26, 2019

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  2. The Transiting Exoplanet Survey Satellite (TESS) is a
    four+ year, nearly all-sky survey monitoring millions
    of stars.
    !2

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  3. The Transiting Exoplanet Survey Satellite (TESS) is a
    four+ year, nearly all-sky survey monitoring millions
    of stars.
    !2
    27 days
    54 days
    81 days
    108 days
    189 days
    351 days

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  4. !3
    The entire 96° x 24° sector is observed
    in the TESS Full-Frame Images (FFIs).

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  5. Predictions indicate the detection of thousands of
    exoplanets which will not be covered in the 2-minute data.
    !4
    (Barclay et al. 2018)

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  6. !5
    Although TESS’s primary objective is to find
    exoplanets, it is a great data set for other fields.
    Exoplanet
    Solar System
    Extragalactic
    Stellar Astrophysics

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  7. !6
    Outline
    1. Developing eleanor, a tool for light curve extraction
    from TESS
    2. Robustly identifying and characterizing flares of young
    stars
    3. Connecting flares and spots to understand stellar
    activity

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  8. !7
    Outline
    1. Developing eleanor, a tool for light curve extraction
    from TESS
    2. Robustly identifying and characterizing flares of young
    stars
    3. Connecting flares and spots to understand stellar
    activity

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  9. Introducing eleanor, an open-source tool
    for light curve extraction from the FFIs.
    !8
    Feinstein, A. D., Montet, B. T., Foreman-Mackey, D., et al. 2019, PASP, 131, 094502
    https://GitHub.com/afeinstein20/eleanor

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  10. Introducing eleanor, an open-source tool
    for light curve extraction from the FFIs.
    !8
    Feinstein, A. D., Montet, B. T., Foreman-Mackey, D., et al. 2019, PASP, 131, 094502
    https://GitHub.com/afeinstein20/eleanor

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  11. !9
    All FFIs for a given sector are about 1TB
    of data, which is not user friendly.

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  12. !9
    All FFIs for a given sector are about 1TB
    of data, which is not user friendly.

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  13. !11
    From the “postcards” we create Target Pixel Files
    (TPFs) which we perform aperture photometry on.
    (Feinstein et al. 2019)

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  14. !12
    We provide four different types of
    light curves for the community to use.
    (Feinstein et al. 2019)

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  15. !13
    We completed a quick search of Sectors 1 and 2
    for new planet candidates.
    (Feinstein et al. 2019)
    Normalized Flux
    0.8
    1.0
    1.2
    0.99
    1.00
    1.01
    0.99
    1.00
    1.01
    0.98
    1.00
    0.98
    1.00
    1.02
    Time [BJD-2457000] Time from Mid-Transit [Days]
    1325 1330 1335 1340 1345 1350 -0.2 -0.1 0.0 0.1 0.2
    TIC 350844139
    TIC 394340349
    TIC 139771134
    TIC 159835004
    TIC 38907808

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  16. !14
    The eleanor package is a powerful tool for those
    not interested in stars and exoplanets as well.
    (Feinstein et al. 2019: See also Fausnaugh et al. 2019; Vallely et al. 2019)
    Time [BJD-2457000]
    Flux
    SN2018fhw
    SN2018eph
    SN2018exc
    MOA 2018-LMC-002
    MOA 2018-LMC-003
    60
    50
    40
    140
    130
    120
    140
    130
    120
    2900
    2800
    2700
    300
    200
    100
    1330 1340 1350 1360 1370 1380

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  17. !15
    Combining the FFIs and the two-minute data can
    allow for further confirmation of exciting systems.
    Planet Transit
    Stellar Eclipse
    (Kostov, Welsh, Feinstein et al. in prep)
    !15

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  18. !15
    Combining the FFIs and the two-minute data can
    allow for further confirmation of exciting systems.
    Planet Transit
    Stellar Eclipse
    (Kostov, Welsh, Feinstein et al. in prep)
    !15

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  19. !15
    Combining the FFIs and the two-minute data can
    allow for further confirmation of exciting systems.
    Planet Transit
    Stellar Eclipse
    (Kostov, Welsh, Feinstein et al. in prep)
    !15

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  20. !15
    Combining the FFIs and the two-minute data can
    allow for further confirmation of exciting systems.
    Planet Transit
    Stellar Eclipse
    (Kostov, Welsh, Feinstein et al. in prep)
    !15

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  21. !15
    Combining the FFIs and the two-minute data can
    allow for further confirmation of exciting systems.
    Planet Transit
    Stellar Eclipse
    (Kostov, Welsh, Feinstein et al. in prep)
    !15

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  22. !16
    The eleanor data products are being transferred
    to Mikulski Archive for Space Telescopes (MAST),
    but the software is available now.

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  23. !17
    The eleanor software has been
    widely used by the community.

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  24. !17
    The eleanor software has been
    widely used by the community.

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  25. !17
    The eleanor software has been
    widely used by the community.

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  26. !18
    Future plans including using eleanor to find
    young planets for Rossiter-McLaughlin studies
    with MAROON-X.

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  27. !19
    Outline
    1. Developing eleanor, a tool for light curve extraction
    from TESS
    2. Robustly identifying and characterizing flares of young
    stars
    3. Connecting flares and spots to understand stellar
    activity

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  28. !20
    What is the relationship between stellar
    flare energy and age? Spectral type?

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  29. !21
    What is the relationship between stellar
    flare energy and age? Spectral type?

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  30. !22
    Similar studies with Kepler demonstrated a relationship
    between spectral type, rotation period, and flare energy.
    (Davenport, 2016)
    1.66 1.13 0.86 0.73 0.62 0.47 0.28
    Mass [MSun
    ]
    Maximum Log(Flare Energy [ergs])
    32
    33
    34
    35
    36
    37
    38
    39
    40

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  31. !22
    Similar studies with Kepler demonstrated a relationship
    between spectral type, rotation period, and flare energy.
    (Davenport, 2016)
    1.66 1.13 0.86 0.73 0.62 0.47 0.28
    Mass [MSun
    ]
    Maximum Log(Flare Energy [ergs])
    32
    33
    34
    35
    36
    37
    38
    39
    40

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  32. !22
    Similar studies with Kepler demonstrated a relationship
    between spectral type, rotation period, and flare energy.
    (Yang & Liu, 2019)
    (Davenport, 2016)
    1.66 1.13 0.86 0.73 0.62 0.47 0.28
    Mass [MSun
    ]
    Maximum Log(Flare Energy [ergs])
    32
    33
    34
    35
    36
    37
    38
    39
    40

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  33. !22
    Similar studies with Kepler demonstrated a relationship
    between spectral type, rotation period, and flare energy.
    (Yang & Liu, 2019)
    (Davenport, 2016)
    1.66 1.13 0.86 0.73 0.62 0.47 0.28
    Mass [MSun
    ]
    Maximum Log(Flare Energy [ergs])
    32
    33
    34
    35
    36
    37
    38
    39
    40

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  34. !23
    What is the relationship between stellar
    flare energy and age? Spectral type?

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  35. !24
    We have completed a literature search for young
    moving group members with ages 1-750 Myr.

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  36. !25
    What is the relationship between stellar
    flare energy and age? Spectral type?

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  37. !26
    Previous flare studies have relied on sigma
    clipping methods to identify flares.

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  38. !26
    Previous flare studies have relied on sigma
    clipping methods to identify flares.
    (Chang, Byun, & Hartman, 2015)

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  39. !26
    Previous flare studies have relied on sigma
    clipping methods to identify flares.
    (Chang, Byun, & Hartman, 2015)
    :(

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  40. !27
    What is the most complete method for
    detecting flares of all energies?

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  41. !28
    Machine learning can be used when searching
    for signals with a characteristic shape.

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  42. !28
    Machine learning can be used when searching
    for signals with a characteristic shape.
    (Pearson et al. 2017)

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  43. !28
    Machine learning can be used when searching
    for signals with a characteristic shape.
    (Pearson et al. 2017)

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  44. We can use machine learning techniques
    to automate finding flares in TESS data.
    !29

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  45. !30
    We simulate spot modulation and flares of
    different amplitudes to pass in as the training set.

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  46. !31
    Every light curve receives a label that the neural
    network learns over several epochs.

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  47. !32
    Feeding in a test training set assigns a
    probability that the object is or is not a flare.

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  48. !33
    We determine the probability that each
    data point is a part of a potential flare.

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  49. !33
    We determine the probability that each
    data point is a part of a potential flare.

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  50. !34
    The first results of applying the neural network to
    a TESS two-minute target are promising.

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  51. !35
    https://GitHub.com/afeinstein20/stella
    Zooming in, we can see the confidence of the
    neural network with identifying large flares.

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  52. !36
    Outline
    1. Developing eleanor, a tool for light curve extraction
    from TESS
    2. Robustly identifying and characterizing flares of young
    stars
    3. Connecting flares and spots to understand stellar
    activity

    View full-size slide

  53. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.

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  54. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.
    (Doyle et al. 2018)

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  55. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.
    (Doyle et al. 2018)

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  56. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.
    (Doyle et al. 2018) (Roettenbacher et al. 2018)
    1-5% increase
    > 5% increase

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  57. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.
    (Doyle et al. 2018) (Roettenbacher et al. 2018)
    1-5% increase
    > 5% increase

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  58. !37
    In the same year, two papers presented conflicting
    results on where flares occur with relation to spots.
    (Doyle et al. 2018) (Roettenbacher et al. 2018)
    1-5% increase
    > 5% increase
    Sample size: 32 Sample size: 119

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  59. !38
    The take-away figure will show the location of flares
    with respect to the phase of spot modulation.

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  60. !39
    Summary
    • We have created an open-source software package for
    extracting light curves from the TESS FFIs.
    • Light curve data products will be hosted on MAST for
    community use.
    • Currently, I am exploring flare properties of young (1-750
    Myr) stars observed by TESS using a neural network, with
    the hopes of answering how flares are related to starspots.

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