lloyd knox uc davis

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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are needed to see this picture.Optical Properties of Dust

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)

5

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

8

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

10

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.