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Intro to Claire's research

05647a0ba3ab20f5f0a77792c5ca82fd?s=47 Claire Murray
February 22, 2021

Intro to Claire's research

Past and current research by Dr. Claire Murray

05647a0ba3ab20f5f0a77792c5ca82fd?s=128

Claire Murray

February 22, 2021
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  1. Claire Murray clairemurray56@gmail.com @radioclairity cmurray-astro@github https://cmurray-astro.github.io/ Karl G. Jansky Very

    Large Array (a.k.a. VLA, EVLA, JVLA….)
  2. A short history I grew up in Brooklyn, NY Carleton

    College (2007-2011) University of Wisconsin- Madison (2011-2017) Baltimore (2017-present) NRAO (Summer 2010)
  3. More things about me David French Poot

  4. Dissecting the interstellar medium [phase, structure, kinematics] in diverse conditions

    [Milky Way, nearby galaxies]
  5. “Galactic Science with the SKA” (Lorentz Center, 2014) ISM =

    complicated
  6. “Galactic Science with the SKA” (Lorentz Center, 2014) ISM =

    complicated Tumlinson et al. 2017
  7. “Galactic Science with the SKA” (Lorentz Center, 2014) ISM =

    complicated Tumlinson et al. 2017
  8. “Galactic Science with the SKA” (Lorentz Center, 2014) ISM =

    complicated Tumlinson et al. 2017 Cold Neutral Medium (CNM): 20 < T< 500 K Warm Neutral Medium (WNM): 2000 < T< 5000 K
  9. How is mass distributed between neutral gas phases? Measure HI

    properties with 21cm absorption and emission HI Cloud Flat spectrum background radio continuum source
  10. How is mass distributed between neutral gas phases? Measure HI

    properties with 21cm absorption and emission HI Cloud Sensitivity, calibration matters! Murray et al.: EVLA Memos 171, 176, 197 Heiles & Troland 2003 Flat spectrum background radio continuum source Murray et al. 2018b Optical depth
  11. How is mass distributed between neutral gas phases? Measure HI

    properties with 21cm absorption and emission HI Cloud Brightness Temperature Optical Depth Murray et al. 2018b 0 270 180 90 45 0 -45 0 21-SPONGE
  12. The WNM is unexpectedly “warm” Murray et al. 2014 How

    is mass distributed between neutral gas phases? 21-SPONGE
  13. The WNM is unexpectedly “warm” Murray et al. 2014 How

    is mass distributed between neutral gas phases? 21-SPONGE There is a significant amount of thermally unstable HI in the local ISM 52% 20% 28% WNM UNM CNM Murray et al. 2018b
  14. Planck Collaboration et al. (2011), 536, A19 ``Dark” gas? How

    is mass distributed between neutral gas phases? “Total gas” = HI + CO
  15. Planck Collaboration et al. (2011), 536, A19 ``Dark” gas? How

    is mass distributed between neutral gas phases? “Total gas” = HI + CO Optically-thick HI cannot solely account for ``dark” gas ``Dark” correction assuming excess dust = HI (Fukui et al. 2015) ``Dark” correction measured by 21cm absorption Murray, Peek et al. 2018
  16. GASKAP Dickey et al. 2013 Future surveys! ASKAP

  17. MACH 21SPONGE GASKAP ESPOIR (PI M.-Y. Lee) MACH (PI C.

    Murray) VLA Dickey et al. 2013 Future surveys! ASKAP VLA X-Large (PI A. Leroy) Koch et al. 2018 80 pc resolution M31, M33, NGC6822, IC10, IC1613, WLM
  18. New tools for analyzing spectral line observations Regularized derivative Autonomous

    Gaussian Decomposition Traditional derivative Example noisy data Lindner, Vera Ciro, Murray et al. 2015
  19. New tools for analyzing spectral line observations Autonomous Gaussian Decomposition

    Lindner, Vera Ciro, Murray et al. 2015 https://github.com/gausspy/gausspy
  20. New tools for analyzing spectral line observations Autonomous Gaussian Decomposition

    Lindner, Vera Ciro, Murray et al. 2015 https://github.com/gausspy/gausspy https://github.com/mriener/gausspyplus Riener et al. 2020 Riener et al. 2019
  21. N(HI) Testing deep learning methods on the high-latitude sky

  22. Convolutional neural networks extract the CNM without absorption information! Cold

    gas fraction Murray, Peek & Kim 2020 0.4 0.0
  23. E(B-V) data: Schlegel, Finkbeiner & Davis 1998 Murray, Peek &

    Kim 2020 Even for diffuse, high-latitude gas, the correlation between E(B-V) and N(HI) depends on amount of cold HI
  24. E(B-V) data: Schlegel, Finkbeiner & Davis 1998 Murray, Peek &

    Kim 2020 HI dominates 1<N(HI)<4e20 cm-2 Even for diffuse, high-latitude gas, the correlation between E(B-V) and N(HI) depends on amount of cold HI
  25. E(B-V) data: Schlegel, Finkbeiner & Davis 1998 Murray, Peek &

    Kim 2020 slope More cold, optically-thick HI Diffuse HI HI dominates 1<N(HI)<4e20 cm-2 Even for diffuse, high-latitude gas, the correlation between E(B-V) and N(HI) depends on amount of cold HI
  26. E(B-V) data: Schlegel, Finkbeiner & Davis 1998 Murray, Peek &

    Kim 2020 slope More cold, optically-thick HI Diffuse HI HI dominates 1<N(HI)<4e20 cm-2 Even for diffuse, high-latitude gas, the correlation between E(B-V) and N(HI) depends on amount of cold HI
  27. Murray et al. in prep CNM Fraction CNM Fraction Position

    Position Position Position Velocity Velocity 3D CNN We can already do better by leveraging morphology!
  28. HI (ASKAP): McClure-Griffiths et al. 2018 What is the structure

    of gas the Small Magellanic Cloud?
  29. RA Dec RA Dec Radial velocity HI (ASKAP): McClure-Griffiths et

    al. 2018 What is the structure of gas the Small Magellanic Cloud?
  30. Dec RA Radial velocity HI (ASKAP): McClure-Griffiths et al. 2018

    What is the structure of gas the Small Magellanic Cloud? Di Teodoro et al. 2019
  31. Observed Stars HI What is the structure of gas the

    Small Magellanic Cloud? Murray, Peek, Di Teodoro et al. 2019 Motions of young stars embedded in the ISM are more complicated than rotation alone
  32. Observed Rotation model Stars HI What is the structure of

    gas the Small Magellanic Cloud? Di Teodoro et al. 2019 Motions of young stars embedded in the ISM are more complicated than rotation alone Murray, Peek, Di Teodoro et al. 2019
  33. Dissecting the Magellanic Clouds with Scylla PI Murray, Gordon, McQuinn,

    Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 SMC LMC
  34. The Bayesian Extinction And Stellar Tool Gordon et al. 2016

    github.com/BEAST-Fitting/beast PI Murray, Gordon, McQuinn, Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 Dissecting the Magellanic Clouds with Scylla
  35. The Bayesian Extinction And Stellar Tool Gordon et al. 2016

    github.com/BEAST-Fitting/beast PI Murray, Gordon, McQuinn, Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 Dissecting the Magellanic Clouds with Scylla
  36. The Bayesian Extinction And Stellar Tool Gordon et al. 2016

    github.com/BEAST-Fitting/beast PI Murray, Gordon, McQuinn, Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 Dissecting the Magellanic Clouds with Scylla
  37. The Bayesian Extinction And Stellar Tool Gordon et al. 2016

    github.com/BEAST-Fitting/beast PI Murray, Gordon, McQuinn, Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 Dissecting the Magellanic Clouds with Scylla CO (1-0) contours
  38. The Bayesian Extinction And Stellar Tool Gordon et al. 2016

    github.com/BEAST-Fitting/beast PI Murray, Gordon, McQuinn, Yanchulova Merica-Jones, Lindberg, Williams +ISM@ST 500-orbit Hubble Space Telescope parallel UV-NIR imaging survey with WFC3 Dissecting the Magellanic Clouds with Scylla LMC SMC 58 60 62 64 66 AV
  39. Dissecting the interstellar medium [phase, structure, kinematics] in diverse conditions

    [Milky Way, nearby galaxies]