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GUIbrush®: Characterizing the atmospheres of the new worlds with Python

Python Torino
September 27, 2023

GUIbrush®: Characterizing the atmospheres of the new worlds with Python

Video: https://video.linux.it/w/igKJp9HopEWjsA69zsQTkd?start=57m12s&stop=2h9m45s

Vediamo un progetto basato su Python per il recupero delle proprietà atmosferiche dei pianeti extrasolari, concentrandoci sulle sfide astrofisiche e computazionali.

Dott. Paolo Giacobbe — Ricercatore presso l'Osservatorio Astrofisico di Torino

Python Torino

September 27, 2023
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Transcript

  1. GUIbrush®
    i.e.
    Characterizing the atmospheres of new
    worlds
    with Python
    Paolo Giacobbe1 & Francesco Amadori1
    (1INAF-Osservatorio Astrofisico di Torino, Pino Torinese, Italy.)

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  2. When it all began (?)
    On 6 October 1995, Michel
    Mayor and Didier Queloz
    announced the discovery of a
    planetary mass object (0.5
    times Jupiter) orbiting the
    solar-type star 51 Peg.

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  3. Indirect detection methods:
    Radial Velocities

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  4. Indirect detection methods:
    transits
    Credits: NASA

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  5. Why study exoplanetary
    atmospheres?
    The Holy Grall of an exoplanetologist
    Biosignatures
    “..object, substance, and/or pattern whose origin specifically requires
    a biological agent”
    (Des Marais and Walter, 1999; Des Marais et al., 2008; Schwieterman
    et al. 2017)

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  6. Why study exoplanetary
    atmospheres?
    ▪We are in the era of comparative
    exoplanetology
    ▪Already now we reveal a rich diversity of
    chemical compositions and atmospheric
    processes hitherto unseen in the Solar
    System.
    ▪The spectrum of an exoplanet reveals the
    physical, chemical, and biological processes
    that have shaped its history and govern its
    future.

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  9. A graphical representation of the Trappist-1 system
    Credit: NASA/JPL-Caltech/Robert Hurt (IPAC)
    A C/O > 1 suggest that the planet formed
    beyond the water snowline
    and
    later migrated towards its star at the we
    observe it today

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  10. Variation of the C/O ratio of the gas in a disc due to
    freeze-out (Madhusudan 2019, Booth+2017).

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  11. Transmission Spectroscopy for Exoplanet Atmospheres

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  12. Credits: NASA

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  13. Transmission Spectroscopy for Exoplanet Atmospheres
    Sedaghati et al 2017
    Low resolution spectroscopy R < 1000

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  14. Low resolution spectroscopy and hot jupiters
    Figure from Sing+2016

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  19. Telescopio Nazionale Galileo @ La Palma

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  20. GIANO-B @ TNG - La Palma (Spain)
    NIR spectrograph mounted at the 3.6-metre
    Telescopio Nazionale Galileo (TNG).
    Simultaneous coverage in the 0.92-2.45 µm
    range (fifty orders )
    Spectral resolving power of R = 50,000.
    Oliva et al. 2006

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  22. At high spectral resolution, molecular features are resolved into a dense forest of of tens of thousands of
    individual lines in a pattern that it is unique for a given molecule -> a kind of fingerprint
    High Resolution ( R = 25,000 - 100,000)
    Transmission Spectroscopy

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  24. The high resolution spectroscopy helps to disentangle and isolate the exoplanet’s spectrum.
    Disentangle moving planet lines from stationary telluric & stellar lines
    High Resolution ( R = 25,000 - 100,000)
    Transmission Spectroscopy
    Snellen et al. (2010) C
    - HD209458b

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  27. GUIbrush®
    Graphic User Interface
    for Bayesian Retrieval
    Using Spectroscopy at
    High Resolution

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  28. VS

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  29. Guibrush® is coded in Python > 3.8
    THE DEMCMC is
    parallelized with the
    Multiprocessing
    Python library
    DEMCMC
    PetitRadTrans:
    Radiative Transfer Code
    ~10 sec for one model in
    the 0.9-2.5 micron range
    GPU?
    The goal is a 100x faster
    code for ANDES/JWST
    range, 3D models, etc
    etc

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  30. Bottleneck #1
    The Bayesian estimator

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  31. Bottleneck #1
    The Bayesian estimator

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  32. Bottleneck #2
    The radiative transfer code

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  33. Bottleneck #2
    The radiative transfer code

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  34. Radiative equilibrium calculations for HD209458b

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  35. C/O =1

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  36. Are there clouds?

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  37. The “final” matrix for Giano is 102’400 x 60 = 6’144’000
    Bottleneck #3
    The model reprocessing

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  40. When will the first 'good' news
    about biosignatures be
    released?

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