$30 off During Our Annual Pro Sale. View Details »

My research talk for CCA promotion

My research talk for CCA promotion

A summary of what I've been up to for the past few years and where my research program is going.

Dan Foreman-Mackey

February 03, 2022
Tweet

More Decks by Dan Foreman-Mackey

Other Decks in Science

Transcript

  1. BUILDING


    THE


    SOFTWARE
    INFRASTRUCTURE


    FOR


    ASTROPHYSICS
    by Dan Foreman-Mackey

    View Slide

  2. who am I?
    / /
    what’ve I been up to?
    1

    View Slide

  3. 7
    [1] solving Hard™ data analysis problems


    [2] enabling and empowering astrophysicists

    View Slide

  4. implementation.

    View Slide

  5. data
    = >
    physics

    View Slide

  6. open source software for astrophysics
    2

    View Slide

  7. why?

    View Slide

  8. credit: Adrian Price-Whelan
    / /
    data: SAO/NASA ADS

    View Slide

  9. my open source contributions
    3

    View Slide

  10. View Slide

  11. gaussian processes
    4

    View Slide

  12. p(data|physics)

    View Slide

  13. data ~ N(model; noise)

    View Slide

  14. °0.6
    °0.3
    0.0
    0.3
    0.6
    raw [ppt]
    0 5 10 15 20 25
    time [days]
    °0.30
    °0.15
    0.00
    de-trended [ppt]
    N = 1000
    reference: DFM+ (2017)

    View Slide

  15. °0.6
    °0.3
    0.0
    0.3
    0.6
    raw [ppt]
    0 5 10 15 20 25
    time [days]
    °0.30
    °0.15
    0.00
    de-trended [ppt]
    N = 1000
    reference: DFM+ (2017)

    View Slide

  16. data ~ N(model; noise)

    View Slide

  17. data ~ N(model; noise)

    View Slide

  18. so. why not?

    View Slide

  19. data ~ N(model; noise)

    View Slide

  20. View Slide

  21. reference: Ambikasaran, DFM+ (2015)

    View Slide

  22. View Slide

  23. reference: Ambikasaran, DFM+ (2015)

    View Slide

  24. reference: DFM, Agol, Ambikasaran, Angus (2017); DFM (2018); DFM, Luger, et al. (2021)

    View Slide

  25. View Slide

  26. reference: Gordon, Agol, DFM (2020)

    View Slide

  27. what’s next?

    View Slide

  28. View Slide

  29. View Slide

  30. View Slide

  31. credit: Quang Tran

    View Slide

  32. reference: Luger, DFM, Hedges (2021)

    View Slide

  33. probabilistic inference
    5

    View Slide

  34. p(data|physics)

    View Slide

  35. have:


    physics
    = >
    data

    View Slide

  36. want:


    data
    = >
    physics

    View Slide

  37. integral of the form


    f(physics) p(physics|data) dphysics

    View Slide

  38. View Slide

  39. number of parameters
    patience required
    a few tenish not outrageously many
    reference: DFM (priv. comm.)

    View Slide

  40. number of parameters
    patience required
    emcee
    a few tenish not outrageously many
    reference: DFM (priv. comm.)

    View Slide

  41. number of parameters
    patience required
    emcee
    a few tenish not outrageously many
    how things should be
    reference: DFM (priv. comm.)

    View Slide

  42. View Slide

  43. View Slide

  44. View Slide

  45. View Slide

  46. gradients!

    View Slide

  47. dp(data|physics) / dphysics

    View Slide

  48. automatic differentiation
    aka “backpropagation”

    View Slide

  49. your model is just code

    View Slide

  50. apply the chain rule

    View Slide

  51. apply the chain rule


    over and over again
    . . .

    View Slide

  52. sounds silly?

    View Slide

  53. it's not! (mostly)

    View Slide

  54. View Slide

  55. View Slide

  56. what’s next?

    View Slide

  57. View Slide

  58. jax.readthedocs.io

    View Slide

  59. my approach to open source
    6

    View Slide

  60. View Slide

  61. [1] don’t underestimate users


    [2] build libraries, not (just) scripts


    [3] teach by example

    View Slide

  62. View Slide

  63. View Slide

  64. View Slide

  65. bringing open source practices


    to research more generally

    View Slide

  66. View Slide

  67. View Slide

  68. View Slide

  69. View Slide

  70. what’s next?
    7

    View Slide

  71. 7
    [1] inference with stochastic or


    intractable models


    [2] what can we do to better support


    open source in astrophysics

    View Slide

  72. 7

    View Slide

  73. 7
    credit: Adrian Price-Whelan

    View Slide

  74. many fundamental software packages


    have a shockingly small number of


    maintainers.

    View Slide

  75. a selection of some* CCA-supported software:
    * my apologies for neglecting your favorites!

    View Slide

  76. View Slide

  77. BUILDING


    THE


    SOFTWARE
    INFRASTRUCTURE


    FOR


    ASTROPHYSICS @ CCA

    View Slide