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New large-scale CIB maps from Planck

Daniel
June 06, 2018

New large-scale CIB maps from Planck

Lunch Colloquium at the University of Bonn/Max-Planck-Institute for Radio Astronomy on new large-scale CIB maps from Planck.

Daniel

June 06, 2018
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  1. New large-scale CIB
    maps from Planck data
    in collaboration with O. Doré,
    B. Hensley, G. Lagache
    Daniel Lenz
    Lunch Colloquium @MPIfR/AIfA
    June 6
    © 2018 California Institute of Technology. Government sponsorship acknowledged.

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  2. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Conclusions
    ❖ New CIB maps for 25%
    of the sky, 4 Planck
    bands
    ❖ Fewer systematics, larger
    sky fraction than
    previous studies
    ❖ Powerful for cross-
    correlations and de-
    lensing
    !2

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  3. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    What is the CIB?
    Cosmic infrared
    background (CIB):
    Made up from dust in
    galaxies at z=1-3
    Extragalactic background light
    !3

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  4. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    What is the CIB?
    Cosmic infrared
    background (CIB):
    Made up from dust in
    galaxies at z=1-3
    Extragalactic background light
    !3

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  5. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Schmidt+ (2015)
    ❖ Strong constraints on star
    formation history
    ❖ Probe dust temperature
    across cosmic times
    ❖ Understand star
    formation in DM halos
    !4
    Why study the CIB? Star-formation!

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  6. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Why study the CIB? Grav. lensing!
    ❖ Large-scale structure induces weak gravitational lensing
    !5

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  7. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Manzotti (2017)
    Why study the CIB? Grav. lensing!
    ❖ CIB kernel and the
    CMB lensing kernel
    are well matched
    !8

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  8. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Planck collaboration (2013, XVII)
    !9
    Why study the CIB? Grav. lensing!
    ❖ Cross-correlation of CIB and
    CMB lensing strongly detected
    in Planck data
    ❖ Lots of room for improvement:
    Sky fraction, CIB data, new
    CMB lensing map

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  9. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    How to obtain CIB maps?
    ❖ Galactic thermal dust and CIB dust dominate on large scales at
    ~200 to 1000 GHz
    ❖ How to disentangle them?
    !10

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  10. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    How to obtain CIB maps?
    A. Fit different frequency channels with modified blackbody spectra
    B. Utilize the different angular power spectra of these components
    C. Use template maps of Galactic dust (e.g. HI-based)
    ❖ Galactic thermal dust and CIB dust dominate on large scales at
    ~200 to 1000 GHz
    ❖ How to disentangle them?
    !10

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  11. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Correlation of dust and gas
    HI Dust
    Linear relation to first order, but better model required to get to CIB levels
    !11

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  12. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Planck data
    !12

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  13. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    HI4PI Survey
    ❖ Merges data from Effelsberg and Parkes
    ❖ Replaces LAB as state-of-the-art full-sky HI survey
    ❖ Higher sensitivity & resolution, fewer systematics, full sampling
    20
    21
    22
    log(NHI
    [cm 2])
    180
    135 90
    45
    0
    315
    270
    225 180
    60
    30
    0
    30
    60
    HI4PI collaboration

    (2017)
    !13

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  14. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Two challenges
    !15
    ❖ Spectrally
    ❖ O(1000) velocity channels in HI
    ❖ Need to control overfitting

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  15. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Two challenges
    ❖ Spatially
    ❖ Dust-to-gas ratios vary over the sky
    ❖ Need to preserve large-scale CIB power
    !15
    ❖ Spectrally
    ❖ O(1000) velocity channels in HI
    ❖ Need to control overfitting

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  16. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    HI-based dust models

    • Velocity separation difficult for
    complex structures and large scales
    Radial Velocity
    HVC
    IVC
    LVC
    I = ✏HVC NHVC + ✏IVC NIVC + ✏LVC NLVC
    !16

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  17. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    • Generalised linear model (GLM)

    Radial Velocity
    I =
    X
    i
    ✏iTi
    B
    !17
    HI-based dust models

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  18. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    • Generalised linear model (GLM)

    • Regularised:

    • Accounts for all features along
    line of sight
    I =
    X
    i
    ✏iTi
    B
    Radial Velocity
    |Datai Modeli
    |2 + ↵ · |✏i
    |
    !18
    HI-based dust models

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  19. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale bias
    !19
    Input CIB

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  20. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale bias
    !19
    Mean per field
    Input CIB

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  21. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale bias
    !19
    Mean per field
    After mean subtraction
    Input CIB

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  22. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale bias
    !20
    Large scales Small scales

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  23. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale bias
    !20
    ❖ Separating one region at a time removes large-scale power
    ❖ Not properly recognized before
    ❖ Essential for CIB reconstruction at low l
    Large scales Small scales

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  24. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Spatial selection
    ❖ Build dust models that preserve large-scale power
    ❖ Use consistency checks and cross correlations
    ❖ Difficult trade-off!
    !21
    Offsets in the HI/
    dust correlation

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  25. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Spatial selection
    !22
    Offsets in the HI/
    dust correlation
    (smoothed)
    ❖ Build dust models that preserve large-scale power
    ❖ Use consistency checks and cross correlations
    ❖ Difficult trade-off!

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  26. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Results: Maps
    !23
    (preliminary)

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  27. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Smaller regions
    !24

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  28. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Large-scale CIB maps
    !25

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  29. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work
    !26

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  30. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Based on spatial information: GNILC
    ❖ Power-spectrum
    based
    ❖ Designed to
    remove CIB from
    Galactic dust
    maps
    ❖ Over-subtraction
    of CIB
    Planck (2016 XLVIII
    !27

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  31. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    HI-based: Planck (2014 XXX)
    ❖ ~10 individual fields, HI data
    from the GBT
    ❖ Two larger fields from EBHIS
    and GASS
    ❖ One field cleaned at a time
    ❖ Manual fine-tuning
    !28

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  32. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Small fields
    ❖ Very similar morphologies despite totally different spatial
    selections
    ❖ Yet differences remain!
    MJy/sr
    !29

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  33. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Small fields
    ❖ Very similar morphologies despite totally different spatial
    selections
    ❖ Yet differences remain!
    MJy/sr
    !29

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  34. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Small fields
    ❖ Differences can be partially attributed to the underlying HI data
    ❖ Radial velocity cuts have strong effect
    !30

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  35. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Small fields
    !31

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  36. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Small fields
    !31

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  37. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Large field
    Planck (2014 XXX) This work
    !32

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  38. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work: Large field
    Planck (2014 XXX) This work
    Planck 2014 - This work
    !32

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  39. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Comparison to earlier work
    !33
    Power spectra

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  40. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    CIB - CMB lensing cross power
    !34

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  41. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Conclusions
    ❖ Large-scale Planck CIB maps for 5 frequencies
    ❖ Significant improvement in component separation
    ❖ Much better understanding of systematics
    ❖ Large scales are challenging!
    !35

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  42. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Conclusions
    ❖ Large-scale Planck CIB maps for 5 frequencies
    ❖ Significant improvement in component separation
    ❖ Much better understanding of systematics
    ❖ Large scales are challenging!
    ❖ CIB is powerful probe of large-scale structure
    ❖ Study cosmic star-formation
    ❖ De-lensing for current and future CMB experiments
    !35

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  43. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    The next generation of space-based
    CMB probes
    PICO
    !36

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  44. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Probe of Inflation and Cosmic Origins
    !37
    ❖ NASA’s preparation for the 2020s
    ❖ Set up 8 Probe Missions studies;
    $400M - $1000M*
    *The cost information contained in this
    document is of a budgetary and planning
    nature and is intended for informational
    purposes only. It does not constitute a
    commitment on the part of JPL and/or
    Caltech.

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  45. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Probe of Inflation and Cosmic Origins
    ❖ PICO
    ❖ 21 bands, 21-800 GHz, full polarization
    ❖ 1.4m -> 38’ to 1’
    ❖ 5yr survey -> 0.6 uK arcmin RMS full
    sky
    ❖ Planck: 50 uK (full sky)
    ❖ CMB-S4: 0.8 uK (3% sky)
    !37
    ❖ NASA’s preparation for the 2020s
    ❖ Set up 8 Probe Missions studies;
    $400M - $1000M*
    *The cost information contained in this
    document is of a budgetary and planning
    nature and is intended for informational
    purposes only. It does not constitute a
    commitment on the part of JPL and/or
    Caltech.

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  46. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Probe of Inflation and Cosmic Origins
    !38
    ❖ Key science: CMB B-modes, tensor-to-scalar ratio r
    ❖ Dominated by foregrounds

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  47. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Thank you!
    !39

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  48. Daniel Lenz, JPL/Caltech Large-scale CIB maps from Planck data
    Based on spatial information: GNILC
    Planck (2016 XLVIII
    !40

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