High-High-ℓ CMBℓ CMB and the CBI and the CBI

Jonathan Sievers Jonathan Sievers (CITA/UToronto) (CITA/UToronto)

+CBI Collaboration+CBI Collaboration

CMB at High-CMB at High-ℓℓ Primary CMB fluctuations low past Primary CMB fluctuations low past ℓ~2000ℓ~2000 Signal expected to arise from secondary anisotropies – SZ galaxy Signal expected to arise from secondary anisotropies – SZ galaxy

clusters, point sources…clusters, point sources… High power level seen in CBI (30 GHz, High power level seen in CBI (30 GHz, ℓ~2000), BIMA (30 GHz, ℓ~2000), BIMA (30 GHz,

ℓ~6000). ACBAR (150 GHz, ℓ~2000) sees level consistent with ℓ~6000). ACBAR (150 GHz, ℓ~2000) sees level consistent with CBI if due to SZ (but also consistent with nothing?)CBI if due to SZ (but also consistent with nothing?)

Observed level much(?) larger than expected, especially in light Observed level much(?) larger than expected, especially in light of WMAP3 low of WMAP3 low σσ88..

SZ clusters expected to be dominant (non-point source) SZ clusters expected to be dominant (non-point source) component, but models suggest level is very sensitive to component, but models suggest level is very sensitive to σσ8 8

(seventh power), preferably ~0.9-1, unlike 0.75 in WMAP3.(seventh power), preferably ~0.9-1, unlike 0.75 in WMAP3.

What is the dominant source of signal at high-ℓ? We don’t know. Might even be interesting.ℓ? We don’t know. Might even be interesting.

Current Best CBI Spectrum (vs. Old)Current Best CBI Spectrum (vs. Old)

Bottom – old best TT spectrum.

Top – current best spectrum.

For most of ell range, errors down by ~40%. CBI in compact config. in polarization, so little high-ell data. Highest bin only ~10% smaller.

NB: two binningsshown. Red/bluepoints *not* independent.

Top panel – new spectrum! Will be published soon.Data on which current excess results based.

Current CBI+BIMA PSCurrent CBI+BIMA PSFit CMB+Excess modelto CBI data (using raw data, not a fit to the power spectrum). Red curve SPH simulation-based template (Bond et al.), blue curve analytic (Komatsu&Seljak, Spergel et al.). Red points latest CBI w/ finer binning. Black points latest BIMA. ACBAR green.

Models extrapolated to BIMA points – not a fit. Differences between analytic/simulation templates of factor of 2, implies σ8 model uncertainty of 0.08-0.09.

If CBI excess were due to unexpected source population, BIMA would see them. They don’t.

Actual Actual σσ88 From Chains From ChainsDo full parameter analysis with all CMB (including latest CBI, WMAP3).

Inferred σ8 for Bond et al. template is 1.00±0.1, for Komatsu & Seljak is 0.93±0.1.

Komatsu & Seljak consistent with latest Chandra M-T relation (Vikhlinin et al.). Latest XMM M-T (Arnaud et al.) 50% higher than Chandra – σ8~0.85? Subha Majumdar working on prediction.Errors assume Gaussian noise in PS only. Doesn’t

include errors from non-Gaussianity of clusters, uncertainty in faint source counts (~35% increase) M-T SCATTER??

Sources w/ GBTSources w/ GBT

Observing NVSS sources in CBI fields in 2-prong strategy.

First: veto survey to measure all sources to see which ones matter at 30 GHz (large majority don’t).

Second: deep obs. of faint NVSS sources to measure Ka counts. Are startbursts synchotron or Free-Free at 30? Requires GBT receiver to be stable for ~minute.White = NVSS sources in CBI fields.

Green = observed by GBT as part of veto survey. Increases by 50-100% CBI data.

Uncertain faint source flux at 30 GHz important source of uncertainty. When done with GBT observations, will nearly double significance of current CBI excess.

Very, Very Preliminary Optical-CMBVery, Very Preliminary Optical-CMB

If excess due to SZ, clusters in optical should correspond to holes in CBI maps. Have CFHT of CBI deep fields.

Don’t have masses yet from RCS guys – only significance. Very noisy. Want mass to ~50%.

(NB, only 2 clusters in highest bin, 5 in second-highest)

Field galaxies should show positive correlation (some are radio sources). Explains low-significance positive correlation?

Bin up clusters, measure CMB power vs. cluster “size”. SZ should be negative.

Note - sources in low-significance clusters already corrected for statistically in spectrum.

This month: CBI2!This month: CBI2! Upgrading CBI for better Upgrading CBI for better

spectrum.spectrum. 0.9m --> 1.4m dishes0.9m --> 1.4m dishes Ground Shield (eventually)Ground Shield (eventually) Measure the excessMeasure the excess Much better SZ sensitivity.Much better SZ sensitivity.

CBI2 Forecast – 1 Year on CMBCBI2 Forecast – 1 Year on CMB

Black = CMBRed= CMB+current excessMagenta=CBI nowBlue=CBI2Green=thermal noise in CBI2

Slightly more pessimistic forecast gives 8% error on current excess.

Should be able to get GBT follow-up observations.

SummarySummary Combined CBI dataset gives much better CMB power Combined CBI dataset gives much better CMB power

spectrum, modest improvement at highest ell.spectrum, modest improvement at highest ell. CBI detects excess power at ℓ>2000 at 3CBI detects excess power at ℓ>2000 at 3σσ. Will go to ~5. Will go to ~5σσ

(assuming level doesn’t change) with GBT data (most of (assuming level doesn’t change) with GBT data (most of which is in hand).which is in hand).

Working on CMB/Optical correlation, results should come Working on CMB/Optical correlation, results should come soon.soon.

CBI2 will do much better on high-ℓ excess. Important even CBI2 will do much better on high-ℓ excess. Important even with other expts. due to l-range, frequency. (new ACBAR with other expts. due to l-range, frequency. (new ACBAR will do same ℓ range at 150, SZA will do somewhat higher-will do same ℓ range at 150, SZA will do somewhat higher-ℓ.). ℓ.).

Observations w/ CBI2 start this month!Observations w/ CBI2 start this month!

CBI (+ACBAR?+BIMA) ExcessCBI (+ACBAR?+BIMA) Excess SZ clusters should contribute to the CMB power SZ clusters should contribute to the CMB power

spectrum in a frequency-dependent way.spectrum in a frequency-dependent way. Signal level very sensitive to Signal level very sensitive to σσ88 – roughly – roughly σσ88

77ΩΩMM22..

CBI currently detects excess at 4.1CBI currently detects excess at 4.1σσ (vs. primary (vs. primary CMB) in overall level, fold in uncertainty due to CMB) in overall level, fold in uncertainty due to faint point source contributions, goes to 2.9faint point source contributions, goes to 2.9σσ..

Currently observing radio point sources with GBT. Currently observing radio point sources with GBT. Gets us more data, plus better knowledge of Gets us more data, plus better knowledge of faint sources (currently 50% uncertainty). faint sources (currently 50% uncertainty).

CBI excess wants CBI excess wants σσ88~1.~1. BIMA also detects power at a level consistent with BIMA also detects power at a level consistent with

CBI if SZ. ACBAR has suggestion of detection, CBI if SZ. ACBAR has suggestion of detection, consistent with CBI+BIMA (150 GHz gets ¼ power consistent with CBI+BIMA (150 GHz gets ¼ power of 30 GHz) - but also pure CMB.of 30 GHz) - but also pure CMB.

How to Proceed?How to Proceed? If excess is from clusters, should be optical-radio correlation. If excess is from clusters, should be optical-radio correlation.

Signal clear since clusters are negative in radio, unlike Signal clear since clusters are negative in radio, unlike everything else in the sky. We have obtained CFHT images of everything else in the sky. We have obtained CFHT images of CBI deep fields, doing correlation now.CBI deep fields, doing correlation now.

Better source observations. 30 GHz faint source counts Better source observations. 30 GHz faint source counts uncertain at ~50%. Leads to 25% uncertainty in excess level. uncertain at ~50%. Leads to 25% uncertainty in excess level. GBT 30 GHz system working – we are observing faint sources in GBT 30 GHz system working – we are observing faint sources in NVSS to nail down 1.4-30 spectral index distribution.NVSS to nail down 1.4-30 spectral index distribution.

Look at clusters in more detail. CCCP (PI Henk Hoekstra) a Look at clusters in more detail. CCCP (PI Henk Hoekstra) a program to do weak lensing of ~50 X-Ray bright clusters. CBI program to do weak lensing of ~50 X-Ray bright clusters. CBI will get SZ of ~20 – will help with prediction of SZ amplitude.will get SZ of ~20 – will help with prediction of SZ amplitude.

And, of course, BETTER DATA! CBI being upgraded – 1.4m And, of course, BETTER DATA! CBI being upgraded – 1.4m dishes being installed as we speak. CBI2 will be 5-20 times as dishes being installed as we speak. CBI2 will be 5-20 times as efficient at excess/cluster observations as original CBI. Should efficient at excess/cluster observations as original CBI. Should have much better spectrum in a year.have much better spectrum in a year.

Weak Lensing vs. SZ/X-Ray MassesWeak Lensing vs. SZ/X-Ray Masses

Simple CBI2 forecast.Assume 130 uK error (differencing – worst case) or 80 uK (no differencing) errors. Fold in errors on X-Ray temp., see what errors on mass come out.

Does not include shape uncertainties, point sources… Assumes same shape for everybody.

(~10 total nights observing time on CBI2)

(noise added vertically, but not horizontally)

Some Clusters AlreadySome Clusters Already

Have observed ~15 z<0.1 clusters with CBI, of order 5 of CCCP sample. Image of 1 night on A2163.

Fit isothermal-β, fixing shape parameters from X-Ray. Get same model SZ decrement (10%) as OVRO, which is sensitive to ~10 times smaller scales. So for this case, isothermal-β a pretty good fit.

CBI 2000+2001, WMAP, ACBAR, BIMACBI 2000+2001, WMAP, ACBAR, BIMAReadhead et al. ApJ, 609, 498 (2004)Readhead et al. ApJ, 609, 498 (2004)

SZE SZE SecondarySecondaryCMB CMB

PrimaryPrimary

+Boom03; Acbar05: very nice TT, Oct05. parameters & new excess analysis as SZ

87

.82 +- .11

= .85 +- .05 CMBall+LSS8

Kuo et al. (2005, in prep)Kuo et al. (2005, in prep)

What I Still Did Last NightWhat I Still Did Last NightSplit vs. redshift. SZ stronger at higher z? Maybe just a selection effect.

Need to get better estimates of cluster masses…

What I Did This MorningWhat I Did This MorningNew spectrum with GBT non-detections subtracted (not projected), noise term added.

Errors improve by ~15%. Should get another 10-15% better when all of the sources are measured.

Absolutely critical: measurement of faint (~1 mJy) 1.4 GHz sources. They are a different population, may have different 30 GHz properties.

Uncertainty in excess evenly split between spectrum/source terms.

Can Tune Obs. Plan after 1 MonthCan Tune Obs. Plan after 1 Month Optimal observing strategy depends on signal level.

After 1-month, should have a much better idea of level

Will be able tune obs. plan during the run, which is nice.

The Cosmic Background ImagerThe Cosmic Background Imager

13 90-cm Cassegrain antennas13 90-cm Cassegrain antennas• 78 baselines78 baselines

6-meter platform6-meter platform• Baselines 1m – 5.51mBaselines 1m – 5.51m

10 1 GHz channels 26-36 GHz10 1 GHz channels 26-36 GHz• HEMT amplifiers (NRAO)HEMT amplifiers (NRAO)• Cryogenic 6K, Tsys 25 KCryogenic 6K, Tsys 25 K

Single polarization (R or L)Single polarization (R or L)• Polarizers from U. ChicagoPolarizers from U. Chicago

Analog correlatorsAnalog correlators• 780 complex correlators780 complex correlators

Field-of-view 44 arcminField-of-view 44 arcmin• Image noise 4 mJy/bm 900sImage noise 4 mJy/bm 900s

Resolution 4.5 – 10 arcminResolution 4.5 – 10 arcmin

(Currently strongest detection of high-ℓℓ power))