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"So What Are You For, Exactly?" - ISM✻@ST Intro Talk

Chris Clark
April 06, 2020
29

"So What Are You For, Exactly?" - ISM✻@ST Intro Talk

Intro talk given to the ISM*@ST group meeting, introducing me and my science to the new (and old) members.

Chris Clark

April 06, 2020
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Transcript

  1. “So, what are
    you for, exactly?”
    ISM✻@ST Intro Talk
    Chris Clark

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  2. Chris Clark
    Clark & Redfern (1988)
    Helston

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  3. Chris Clark
    Cardiff

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  4. Chris Clark
    BBC (2009)

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  5. Chris Clark
    Dust in Type-Ia SNe?
    Gomez & Clark+ (2012a); Clark (PhD T., 2015)
    Kepler’s Supernova (SN1604) Tycho’s Supernova (SN1572)
    (optical & X-ray images)

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  6. Chris Clark
    Dust in Type-Ia SNe: Kepler’s SN
    Gomez & Clark+ (2012a); Clark (PhD T., 2015)
    Herschel-PACS (70, 100, 160 μm) Herschel-SPIRE (250, 350, 500 μm)

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  7. Chris Clark
    Dust in Type-Ia SNe: Tycho’s SN
    Gomez & Clark+ (2012a); Clark (PhD T., 2015)
    Herschel-PACS (70, 100, 160 μm) Herschel-SPIRE (250, 350, 500 μm)

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  8. Chris Clark
    Type-Ia SNe: Resolved Temps
    Gomez & Clark+ (2012a); Clark (PhD T., 2015)
    Kepler’s supernova; T
    hot
    (left) and T
    cold
    (right)
    Tycho’s supernova; T
    hot
    (left) and T
    cold
    (right)
    (Forgive the jet colour scale; I was young and didn’t know better!)
    Negligible dust manufactured by
    Type-Ia supernovæ
    Which means all the iron depleted
    into dust got there some other way

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  9. Chris Clark
    Dust in a Type-II SN: The Crab (SN1054)
    Gomez+ inc. Clark (2012b); Clark (PhD T., 2015)
    Herschel-PACS (70, 100, 160 μm) Herschel-SPIRE (250, 350, 500 μm)

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  10. Chris Clark
    Dust in a Type-II SN: The Crab (SN1054)
    Clark (PhD T., 2015)

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  11. Chris Clark
    The Crab: Synchrotron Power Law
    Gomez+ inc. Clark (2012b); Clark (PhD T., 2015)
    Spectral index map

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  12. Chris Clark
    The Crab: Component Separation
    Gomez+ inc. Clark (2012b); Clark (PhD T., 2015)
    Synchrotron @ 160 μm Hot dust @ 160 μm
    Cold dust @ 160
    μm
    We found 0.11 M

    supernova dust in the Crab Nebula
    Subsequent studies report values across 0.04–0.22 M

    range

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  13. Chris Clark
    Herschel-ATLAS
    (Herschel Astrophysical Terahertz Large Area Survey)
    Eales+ (2010)

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  14. Chris Clark
    Dust-Detected H-ATLAS Low-z Galaxies
    Clark+ (2015)
    H-ATLAS 250 µm
    15 < D < 45 Mpc
    SDSS gri-bands

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  15. Chris Clark
    BADGRS: Blue & Dusty Gas Rich Sources
    Clark+ (2015)
    Near-IR VIKING Ks
    Optical SDSS gri
    H-ATLAS 250 µm
    GALEX Far-UV
    Very blue (flux ratio FUV/K
    s
    > 25), flocculent, HI-dominated galaxies
    make up the majority of a blind low-z blind 250 µm selected survey.

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  16. Chris Clark
    BADGRS: Lots of Dust, Little Attenuation
    Clark+ (2015)
    More
    Attenuation
    Less
    Attenuation
    Dust Rich
    Dust Poor

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  17. Chris Clark
    BADGRS: Lots of Dust, Little Attenuation
    Clark+ (2015)
    M
    D
    /M
    S
    ~ 0.0005 M
    D
    /M
    S
    ~ 0.01

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  18. Chris Clark
    BADGRS: Lots of Dust, Little Attenuation
    Schofield (PhD, 2017)

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  19. Chris Clark
    BADGRS: The Peak of Dust-Richness
    Clark+ (2015)
    Older
    Younger
    Dust Rich
    Dust Poor

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  20. Chris Clark
    BADGRS: The Peak of Dust-Richness
    Clark+ (2015); De Vis (2017)
    Older
    Younger
    Dust Rich
    Dust Poor

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  21. Chris Clark
    BADGRS: Many Chemical Evolution Paths?
    De Vis+ (2017); Schofield (PhD T., 2017)
    Older
    Younger
    Dust Rich
    Dust Poor

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  22. Chris Clark
    BADGRS: Star Formation Still Ramping Up
    Schofield (PhD T., 2017)

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  23. Chris Clark
    BADGRS: Super Low M
    H2
    /M
    dust
    ?
    Dunne+ (2018)
    IRAM 30m CO(1–0)
    I
    CO
    = 0.2–2 K km s-1
    FWHM = 30–100 km s-1
    M
    H2
    /M
    dust
    = 2–27 (Z-based X
    CO
    – MW X
    CO
    )
    Z = 0.5–1 Z

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  24. Chris Clark
    BADGR Follow-Up: JINGLE (Preliminary)
    Saintonge+ (2018); Lamperti+ (2020); Clark+ (in prep.)
    More
    Attenuation
    Less
    Attenuation
    Dust Rich
    Dust Poor
    JINGLE
    JCMT dust & gas in Nearby
    Galaxies Legacy Exploration

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  25. Chris Clark
    Literature Values for κd (the Mass Opacity Coeff)
    Alton+ (2004); Demyk+ (2013); Köhler+ (2015); Clark+ (2016); Jones+ (2017); Clark+ (2019)
    Several dex total
    range in κ
    d
    values.
    Commonly-used
    standard values span
    a factor of ~3 range

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  26. Chris Clark
    Estimating κd
    with the HRS (the Herschel Reference Survey)
    Alton+ (2004); Demyk+ (2013); Köhler+ (2015); Clark+ (2016); Jones+ (2017); Clark+ (2019)
    κ
    500
    = 0.051 m2 kg-1
    (± 0.24 dex)

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  27. Chris Clark
    Biology‽

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  28. Chris Clark
    DustPedia Database
    Davies+ (2017); Clark+ (2018)
    • The DustPedia sample (Davies+,
    2017) covers all 875 nearby (D<40
    Mpc) extended (1’ < D25 < 1°)
    galaxies observed by Herschel.
    • Standardised imagery & photometry
    spanning 42 UV–microwave bands
    (Clark+, 2018).
    • Homogenised atomic & molecular gas
    values for 764 & 255 DustPedia
    galaxies respectively (; De Vis+, 2019;
    Casasola+, 2020).
    • 10000 consistently-determined gas-
    phase metallicity datapoints (from
    IFU, slit, and fibre spectra) for 492
    DustPedia galaxies (De Vis+, 2019).
    UV-NIR-FIR montage of some of the galaxies in the DustPedia database

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  29. Chris Clark
    DustPedia Photometry
    Clark+ (2018)
    Robust automated aperture photometry for extended sources.

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  30. Chris Clark
    DustPedia Photometry
    Clark+ (2018)
    Self-consistent
    photometry across
    many bands.

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  31. Chris Clark
    Literature Values for κd (the Mass Opacity Coeff)
    Alton+ (2004); Demyk+ (2013); Köhler+ (2015); Clark+ (2016); Jones+ (2017); Clark+ (2019)
    Several dex total
    range in κ
    d
    values.
    Commonly-used
    standard values span
    a factor of ~3 range

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  32. Chris Clark
    Data for Mapping κd
    Within Galaxies
    Clark+ (2018); Clark+ (2019)
    M83
    M74
    But also need
    metallicity maps to
    calculate κ
    d
    . These
    don’t normally exist
    for nearby galaxies…

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  33. Chris Clark
    Metallicity Mapping in Nearby Galaxies
    Clark+ (2019); De Vis+ (2019)
    Lots of individual metallicity points from individual
    metallicity spectra. But need to turn into metallicty map…
    M74
    M83

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  34. Chris Clark
    Gaussian Process Regression in M74
    Clark+ (2019); De Vis+ (2019)
    M74 Metallicity Map
    M74 Metallicity Uncertainty

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  35. Chris Clark
    Gaussian Process Regression in M83
    Clark+ (2019); De Vis+ (2019)
    M83 Metallicity Map
    M83 Metallicity Uncertainty

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  36. Chris Clark
    Maps of κd
    in Nearby Galaxies!
    Clark+ (2018); Clark+ (2019)
    M74 κ
    d
    map
    M83 κ
    d
    map
    UV-NIR-FIR image
    for reference
    UV-NIR-FIR image
    for reference

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  37. Chris Clark
    κd
    vs ISM Surface Density
    Clark+ (2018); Clark+ (2019)
    Appears that κ
    d
    is
    anticorrelated with ISM
    density. Opposite of
    what is predicted by
    models…

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  38. Chris Clark
    M74 & M83 κd
    Compared to Literature
    Alton+ (2004); Demyk+ (2013); Köhler+ (2015); Clark+ (2016); Jones+ (2017); Clark+ (2019)

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  39. Chris Clark
    Issues Observing Extended Galaxies in FIR
    Meixner+ (2014); Roman-Duval+ (2017); Williams+ (2018); Clark+ (in prep.)
    Herschel only; little diffuse emission

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  40. Chris Clark
    So, You Want to Study Dust in the Magellanic Clouds?
    Roman-Duval+ (2017); Clark+ (in prep.)
    • Herschel!
    • …Except faint structure at the edges got removed as ‘background’,
    as the map was too small; large-scale features get filtered out.
    • Okay, Planck then!
    • …And Planck is great! But its shortest band is 350μm, so you can’t
    constrain dust temperature. And beam is 10x worse than Herschel.
    • How about Spitzer?
    • …Only covers the shorter wavelengths, and iffy resolution. Plus,
    severe non-linearity issues at high surface brightness for 160μm.
    • But there’s always IRAS, right?
    • …Unless you want to observe something that is extended and has
    very high surface brightness. Like the Magellanic Clouds.
    • Urm, I suppose I could try using Akari?
    • …
    • Good point. How about JCMT? Or ISO?
    • …Never observed more than tiny parts of the Clouds.
    • I suppose that leaves…

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  41. Chris Clark
    Only Trustworthy Data is COBE!
    Meixner+ (2014); Roman-Duval+ (2017); Williams+ (2018); Clark+ (in prep.)
    Herschel-SPIRE 250 µm COBE-DIRBE 240 µm

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  42. Chris Clark
    Feathering in Fourier Space
    Williams+ (2018); Clark+ (in prep.)
    COBE 100 µm IRAS 100 µm
    COBE feathered with IRAS COBE feathered with IRAS

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  43. Chris Clark
    Combine Alllll the Data in Fourier Space…
    Clark+ (in prep.)
    COBE
    Far-infrared data,
    large angular scales
    IRAS
    Far-infrared data,
    medium angular scales
    Planck
    Submm data, large &
    medium angular scales
    COBE + IRAS
    FIR data, large and
    medium angular scales
    COBE + IRAS
    + Planck
    FIR-submm data, large &
    medium angular scales
    Herschel
    FIR-submm data,
    small angular scales
    COBE + IRAS
    + Planck + Herschel
    FIR-submm data, large &
    medium & small angular scales

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  44. Chris Clark
    Issues Observing Extended Galaxies in FIR
    Meixner+ (2014); Roman-Duval+ (2017); Williams+ (2018); Clark+ (in prep.)
    Herschel only; little diffuse emission Herschel et al; Fourier-combined (WIP)

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  45. Questions
    welcome!

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  46. Chris Clark
    Gaussian Process Regression – Reliable!
    Clark+ (2019); De Vis+ (2019)

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  47. Chris Clark
    Alternate Models
    Clark+ (2019)
    M74
    DTM ∝ radius DTM ∝ ISM density “Toy” model
    M83
    CHAOS Z

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  48. Chris Clark
    Alternate Models
    Clark+ (2019)
    DTM ∝ radius DTM ∝ ISM density “Toy” model

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  49. Chris Clark
    CO r
    2:1
    Regression
    Leroy+ (2012); Clark+ (2019)

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  50. Chris Clark
    SED-Fitting Example
    Clark+ (2019)

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  51. Chris Clark
    Dust-to-Metals in THEMIS
    Jones+ (2017); Jones+ (2018)
    Dust-to-metals expected to vary
    by factor of ~3.6 in THEMIS dust
    model (Jones+ 2017;2018).
    Table 3 from
    Jones+ (2018)

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  52. Chris Clark
    Dust-to-Metals from Depletions
    Jenkins (2009); De Cia+ (2016); Wiseman+ (2016)
    Wiseman+ (2016) and De Cia+ (2016) find DTM varies with metallicity, from
    DLA depletions; but for metallicities of >0.1 Z

    this variation is less than factor
    of ≤2.
    Jenkins+ (2009) find Milky Way variation of factor ≤2.7.
    Figure 7 from Wiseman+ (2016) Figure 15 from De Cia+ (2016)

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