South Pole Telescope millimeter-wave observations of thermal emission by dust from 100 million high-z galaxies
Lloyd KnoxUC Davis
Photo credit: Keith VanderlindeSPT 2nd season winter-over
CIB Anisotrop
ies
Scientific Motivation I
Image: WMAP (slightly hacked by J. Vieira)
Anisotropies in the CIB are sensitive to the entire history of star
formation in the Universe
Where There’s Star Formation, There’s Dust
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Standard lore: Dust forms in cold envelopes of evolved stars and in ejecta of supernovae
• Dust also facilitates the cooling necessary for star formation
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Absorbs light at wavelengths
smaller than the grain size
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Radiates thermally at
longer wavelengths
Full-sky 94 GHz intensity map
Jessberger et al. (2001)
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Half of background light from stars is reprocessed by dust
Dole et al. 2006
CIB Brightness = 24 nW/m2/sr
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Simple Model of Dust Emission
34 K grey body spectrum
734 K grey body spectrum
Rest frequency from z = 1 to z = 5
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Dimming
redshifting
Object of same luminosity gets brighter when moved from z=1 to z=5
SPT BandsHall et al.
(2010)
Sub-mm magic
RS comment
n(z) for SMGs
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Dye et al 2009
850 um selected
250, 350, 500 um selected
z-independent brightness, but bulk of them are very faint
• To study in great numbers we need to study them in the confusion limit.
• Intensity = s S2 dN/dS d(lnS)
• Data points are from SPT (Vieira et al. 2010)
Figures by Nicholas
Hall
Number density = s S dN/dS (dlnS)
DSFG = ?
z-independent brightness, but bulk of them are very faint
• To study in great numbers we need to study them in the confusion limit.
• Intensity = s S2 dN/dS d(lnS)
• Data points are from SPT (Vieira et al. 2010)
Figures by Nicholas
Hall
Number density = sSdN/dS (dlnS)
DSFG = Dusty star-forming galaxy
Angular power spectra sensitive to relation between dark matter and star formation history
• To study in great numbers we need to study them in the confusion limit.
• Can measure angular power spectrum of diffuse background, with shape and amplitude dependent on relation of star formation history to dark matter density history.
• The latter we can calculate well from first principles.
Figures by Nicholas
Hall
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Outline• Measurement in the confusion limit with
SPT*.
• Modeling the signals inferred from SPT, BLAST and Spitzer data.
• Future observational prospects.
• Future modeling challenges.
*Many slides in this part from J. Vieira
The SPT
The South Pole Telescope (SPT)An experiment optimized for fine-scale
anisotropy measurements of the CMB• Dedicated 10-m telescope at the South Pole
• Background-limited 960-element mm camera
Science Goals:• Mass-limited SZ survey of galaxy clusters– study growth of structure, dark energy
equation of state
• Fine-scale CMB temperature anisotropies
– SZ power spectrum to measure σ8
• mm sources
– dusty star forming galaxies
– AGN
– Other rare objects
• NEXT: Polarization
Funded by NSF
Sub-millimeter Wavelength Telescope:• 10 meter telescope ⇒ 1’ FWHM beam at 1.4 mm• Clean and simple optical design to minimize
systematics• Off-axis Gregorian optics design for clear
aperture• Three levels of sidelobe mitigation:
– under-illuminated primary – Co-moving ground shield – cold (10K) secondary
• 20 micron RMS surface accuracy (good up to ~ 450 um window)
• 1 arc-second relative pointing ⇒ <3" RMS absolute pointing
• Fast scanning (up to 4 deg/sec in azimuth) ⇒ no chopping
1st Generation Camera:• 1 sq. deg FOV ⇒ good for surveys, bad for
pointed observations• 960 TES coupled spiderweb bolometers read out
with SQUIDS and fMUXed• Modular focal plane observes simultaneously in 3
bands at 1.4, 2.0, 3.2 mm with 1.0, 1.5, 2.0 fλ pixel spacing
• Closed cycle He cryogenics
The South Pole Telescope (SPT)
Collaboration
SPT Team February 2007SPT Team February 2007
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Survey Fields Completed• In 2008 mapped ~180
deg2 around 5hr and 23hrs to 18 uK/arcmin2 pixel. In 2009 we mapped ~ 550 deg2 to the same depth.
• BCS overlap and Magellan follow-up for optical confirmation and photo-z’s.
• Full survey will be ~2000 square degrees.
23hr 5hr30
Field used for recent results
T. Crawford, Recent Results from the South Pole Telescope, FNAL, March 30, 2009
Zoom in on 2 mm map~ 4 deg2 of actual data
T. Crawford, Recent Results from the South Pole Telescope, FNAL, March 30, 2009
Lots of bright emissive sources
~15-sigma SZ cluster detectionAll these “large-scale”
fluctuations are primary CMB.
Zoom in on 2 mm map~ 4 deg2 of actual data
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Radio galaxy model is from de Zotti et al. (2005)
ULIRG/DSFG model modified from Negrello et al. (2007)
Source Count Data points are from SPT(Vieira et al. 2010)
ClPoisson = s S3 dN/dS d(lnS)
Figure is from Hall et al. (2010)
DSFG = Dusty Star-Forming Galaxy
Data points from counting point sources
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Auto and Cross-Frequency Power Spectra: Data at l > 2000 (Hall et al. 2010)
Total observed signal
Need to develop model for CIB signal in these data
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Auto and Cross-Frequency Power Spectra: Data and Model at l > 2000 (Hall et al. 2010)
Total observed signal
poisson term due to sources at S/N
< 5
Best-fit tSZ from L10
Best-fit DSFG-clustering termAssumed kSZ
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Single-SED Model
Fiducial Model: Td = 34K, = 2, zc = 2, z = 2
Scale factor
= comoving distance
Dust emissivity index and temperature
*
*Planck function modified to power-law decline on Wien side with “mid-IR” index
Knox et al.
(2001)
Hall et al. (2010)
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Redshift distribution of mean for Lagache, Dole
and Puget (2005) model and Hall et al. (2010) single-SED model
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Auto and Cross-Frequency Power Spectra: Data and Model at l > 2000 (Hall et al. 2010)
Total observed signal
poisson term due to sources at S/N
< 5
Best-fit tSZ from L10
Best-fit DSFG-clustering term Assumed kSZ
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With CMB and tSZ subtracted
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Spectrum of Poisson Power
• Weak dependence on threshold
• LDP model too shallow -- spectrum is steeper than expected at low frequencies
• single-SED model is NOT fit to these data
BLAST: Viero et al. (2009), Spitzer: Lagache et al. (2007)
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Large 150 to 220 spectral indexFor S proportional to about = 220 GHz we find = 3.86 § 0.26
from SPT dataIn RJ limit, = + 2
For Td = 34K and sources at z = 1 (or 2) we get
= + 1.7 (or 1.5)
Roughly expect for our single-SED model, =
1.38 + = 3.38
Theoretical models calibrated with astronomical and
laboratory data suggest ~ 2 (Gordon 1995).
Meny et al. (2007) claim effects of long-range
disorder in dust can lead to > 2
Silva et al. (1998) models
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Spectrum of Poisson Power
Can get away with lower if assume higher Td or lower z, but then over-predict BLAST and Spitzer power.
BLAST: Viero et al. (2009), Spitzer: Lagache et al. (2007)
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Auto and Cross-Frequency Power Spectra: Data and Model at l > 2000 (Hall et al. 2010)
Total observed signal
poisson term due to sources at S/N
< 5
Best-fit tSZ from L10
Best-fit DSFG-clustering term much stronger at 220x220 than
150x220 Assumed kSZ
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Spectrum of Clustering Power
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Clustering amplitudes at theoretically expected levels
Haiman & Knox (2000)
(RJ)
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Clustering amplitudes at expected levels• Mean CIB inferred from FIRAS data
• a few arc minutes corresponds to several comoving Mpc
•variance in density fluctuations is order unity on Mpc scales
• line of sight probes a few hundred independent cells
• I/I = b/3000.5 = 0.1
Fixsen et al. (1998)
Puget et al. (1996)
Reproduces observed clustering power
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Outline• Measurement in the confusion limit with
SPT*.
• Modeling the signals inferred from SPT, BLAST and Spitzer data.
• Future observational prospects.
• Future modeling challenges.
*Many slides in this part from J. Vieira
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Clustering power will be measured with high precision by Planck very soon
Relevant Planck channels: 143, 217, 353, 545, 850 GHz
CIB is the dominant source of fluctuation power over large parts of sky, and a large range of
angular scales in the highest frequency channels of Planck
Knox et al. (2001)
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Precision Measurement Expected from Planck
• F for FIRB = CIB
• Forecast for Planck 545 GHz shown
• In addition will have auto and cross-frequency power from 217, 353, 545, 850
Milky Way Dust
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Cross-correlation opportunities• CIB anisotropies arise from a broad range in redshifts and therefore have cross correlations with other tracers of large-scale structure
• Can reconstruct the lensing potential from the lensed CMB and cross-correlate with CIB
Lensing-FIRB cross-power forecast for
Planck
Song et al. (2003)
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Cross-correlate with CMB2!
Square of kSZ signal correlates with cosmic shear (Dore et al.
2003)
Should also correlate with CIB -- might be first way effect of
kSZ is detected
gas-rich merger
dusty star forming galaxy
AGN dominated phase
massive ellipticaldust from
SN + debris disks
Narayanan+2009
Slide from J. Vieira
Another model
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Righi, Hernandez-
Monteagudo & Sunyaev (2008)Righi et al.
work out CIB power
spectrum predictions associating DSFGs with mergers
Righi model has lots of light from very high redshift
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Righi et al. predictions
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SPT detected
clustering power at 220 GHz
Phenomenology ripe for development
• Merger model of Righi et al. can accommodate data as well as the `light traces (halo) mass’ models.
• How do we discriminate?
• How do we parameterize the connection between star formation and dark matter evolution to help us interpret the forthcoming high-precision data?
• I am working on these questions with Z. Haiman (Columbia) and A. Benson (Caltech)
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CIB as a Nuisance
4646
Best-fit tSZ
Assumed kSZPossible Patchy reionization signal (not included in
modeling)
Best-fit residual DSFG Poisson Power
Lueker et al. 2010 bandpowers from subtraction
Ts = 1/(1-0.325) (T150 - 0.325 T220)For
subtracting DSFGs(Dusty Star-Forming
Galaxies)
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Summary• CIB offers us a probe of entire history of star formation• From SPT data, we have a first detection of the clustering
of CIB at millimeter wavelengths, at expected amplitudes.• A simple model can accommodate frequency dependence
of CIB anisotropy from 150 to 1900 GHz (with steep emissivity index)
• Observational progress in the confusion limit will be rapid and is driving the development of theoretical modeling to facilitate interpretation
• Phenomenology of the CIB is very ripe for further development, so that we can turn the observational signatures into interesting conclusions about the history of star formation in the Universe.