High-ℓ CMB and the CBI Jonathan Sievers (CITA/UToronto) +CBI Collaboration

CMB at High-ℓ  Primary CMB fluctuations low past ℓ~2000  Signal expected to arise from secondary anisotropies – SZ galaxy clusters, point sources…  High power level seen in CBI (30 GHz, ℓ~2000), BIMA (30 GHz, ℓ~6000). ACBAR (150 GHz, ℓ~2000) sees level consistent with CBI if due to SZ (but also consistent with nothing?)  Observed level much(?) larger than expected, especially in light of WMAP3 low σ 8.  SZ clusters expected to be dominant (non-point source) component, but models suggest level is very sensitive to σ 8 (seventh power), preferably ~0.9-1, unlike 0.75 in WMAP3. ℓ? We don’t know. Might even be interesting. What is the dominant source of signal at high- ℓ? We don’t know. Might even be interesting.

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 binnings shown. Red/blue points *not* independent. Top panel – new spectrum! Will be published soon. Data on which current excess results based.

Current CBI+BIMA PS Fit CMB+Excess model to 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 σ 8 model uncertainty of If CBI excess were due to unexpected source population, BIMA would see them. They don’t.

Actual σ 8 From Chains Do full parameter analysis with all CMB (including latest CBI, WMAP3). Inferred σ 8 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 – σ 8 ~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/ 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 % 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-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!  Upgrading CBI for better spectrum.  0.9m --> 1.4m dishes  Ground Shield (eventually)  Measure the excess  Much better SZ sensitivity.

CBI2 Forecast – 1 Year on CMB Black = CMB Red= CMB+current excess Magenta=CBI now Blue=CBI2 Green=thermal noise in CBI2 Slightly more pessimistic forecast gives 8% error on current excess. Should be able to get GBT follow-up observations.

Summary  Combined CBI dataset gives much better CMB power spectrum, modest improvement at highest ell.  CBI detects excess power at ℓ>2000 at 3σ. Will go to ~5σ (assuming level doesn’t change) with GBT data (most of which is in hand).  Working on CMB/Optical correlation, results should come soon.  CBI2 will do much better on high-ℓ excess. Important even with other expts. due to l-range, frequency. (new ACBAR will do same ℓ range at 150, SZA will do somewhat higher- ℓ.).  Observations w/ CBI2 start this month!

CBI (+ACBAR?+BIMA) Excess  SZ clusters should contribute to the CMB power spectrum in a frequency-dependent way.  Signal level very sensitive to σ 8 – roughly σ 8 7 Ω M 2.  CBI currently detects excess at 4.1σ (vs. primary CMB) in overall level, fold in uncertainty due to faint point source contributions, goes to 2.9σ.  Currently observing radio point sources with GBT. Gets us more data, plus better knowledge of faint sources (currently 50% uncertainty).  CBI excess wants σ 8 ~1.  BIMA also detects power at a level consistent with CBI if SZ. ACBAR has suggestion of detection, consistent with CBI+BIMA (150 GHz gets ¼ power of 30 GHz) - but also pure CMB.

How to Proceed?  If excess is from clusters, should be optical-radio correlation. Signal clear since clusters are negative in radio, unlike everything else in the sky. We have obtained CFHT images of CBI deep fields, doing correlation now.  Better source observations. 30 GHz faint source counts uncertain at ~50%. Leads to 25% uncertainty in excess level. GBT 30 GHz system working – we are observing faint sources in NVSS to nail down spectral index distribution.  Look at clusters in more detail. CCCP (PI Henk Hoekstra) a program to do weak lensing of ~50 X-Ray bright clusters. CBI will get SZ of ~20 – will help with prediction of SZ amplitude.  And, of course, BETTER DATA! CBI being upgraded – 1.4m dishes being installed as we speak. CBI2 will be 5-20 times as efficient at excess/cluster observations as original CBI. Should have much better spectrum in a year.

Weak 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 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 , WMAP, ACBAR, BIMA Readhead et al. ApJ, 609, 498 (2004) SZESecondary CMBPrimary +Boom03; Acbar05: very nice TT, Oct05. parameters & new excess analysis as SZ  = CMBall+LSS  8 Kuo et al. (2005, in prep)

What I Still Did Last Night Split vs. redshift. SZ stronger at higher z? Maybe just a selection effect. Need to get better estimates of cluster masses…

What I Did This Morning New spectrum with GBT non-detections subtracted (not projected), noise term added. Errors improve by ~15%. Should get another % 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 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 Imager  cm Cassegrain antennas 78 baselines78 baselines  6-meter platform Baselines 1m – 5.51mBaselines 1m – 5.51m  10 1 GHz channels GHz HEMT amplifiers (NRAO)HEMT amplifiers (NRAO) Cryogenic 6K, Tsys 25 KCryogenic 6K, Tsys 25 K  Single polarization (R or L) Polarizers from U. ChicagoPolarizers from U. Chicago  Analog correlators 780 complex correlators780 complex correlators  Field-of-view 44 arcmin Image noise 4 mJy/bm 900sImage noise 4 mJy/bm 900s  Resolution 4.5 – 10 arcmin ℓ) (Currently strongest detection of high-ℓ power)