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What can the CMB sll tell us?• Praccally CV limited for determining the integrated reionizaon...

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What can the CMB s-ll tell us? Elena Pierpaoli University of Southern California
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Page 1: What can the CMB sll tell us?• Praccally CV limited for determining the integrated reionizaon signal • Not very good in determining the extent of reionizaon • Will help in relieving

WhatcantheCMBs-lltellus?

ElenaPierpaoliUniversityofSouthernCalifornia

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Summary

– AbroadlookatPlanckparameteres-ma-on

– Reioniza-on– DiffuseForegroundscharacteriza-on– Tensor‐to‐scalar(i.e.res-ma-on)forPlanckandfutureexperiments

From:Colombo&Pierpaoli(arXiv:0804.0278) Colombo,PierpaoliPritchard(arXiv:0811.2622) Betouleetal(arXiv:0901.1056)Macellarietal(tobesubmiZed)

+WhitePapersforCMBPol

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I:NearPerspec-ves:thePlancksatellite

•  Smallerbeam•  Lowernoise•  Polariza-on•  BeZerfrequencycoverage

COBE WMAP PlanckYear data received 1992 2003 2009Spatial resolution (deg) 7 0.23 0.08Frequencies (GHz) 30-90 22-94 30–857Polarization no yes yesSensitivity (muK/30' pix) 10.5 (8yrs) 1.4

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WherePlanckwilldobeZer

•  New information coming from: –  second and third peak in TT spectrum –  greater l range –  reionization “bump” in EE and second peak

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(L.ColomboE.PierpaoliJ.Pritchard2008)

Comparisonofparameteres-ma-onperformances(WMAPorPlanckonly)

(ColomboPierpaoliPritchard08)

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Wheredoestheinforma-oncomesfrom?

•  Temperature: 217 GHz and 143GHz playing similar roles at high resolution

•  Polarization: CV limited to l= 8-12, possibly sensitive to 3rd peak

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Impactonparameters

•  Major information coming from 70-143 GHz. Adding 217GHz iproves parameter determination by ~10%.

•  Giving up 143Ghz,pol results in a 73% (or factor 2) degradation for r estimate. •  LFI useful for improving r estimates.

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Frequencycoverageanddegeneracies

•  Frequencycoveragehelpssomedegeneracies,notall….

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Impactofbeammodeling

•  Assumingawrongbeambytheamountconsistentwithcurrentuncertain-esmaybiasimportantparametersby~sigma

Under‐es-ma-ngorover‐es-ma-ngthebeamby0.05%( )or0.2%()

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Tensortoscalarra-orfromPlanck

Forr>0.05,halfoftheinforma-oncomesfromtheBBspectrum

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Issueswiththetensorspectralindex

•  Forr~0.1,Planckwillnotbeabletoconstrainrandn_tsimultaneosly

•  EvenforanEPICtypeofexperiment,marginalizingonn_tincreasestheerrorsonrbyafactor3.

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Synergieswithothersurveys

Planckonly

BAO~JDEM(z=0.5‐2,10000sqdeg)

(CIP:z=2–6.5,1000sqdeg,2Mgal)

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Thelow‐lparameters:Thetensor‐to‐scalarra-orandreioniza-onτ

•  Reioniza-onimpactstheCMBtempertatureandpolariza-onspectra.•  TheOp-caldepthistheonlyparametercurrentlyconstrainedanditis

determinedbyEEspectra.

Constraints(WMAP3):Alldata:τ = 0.09 +/‐0.03EEonly:τ = 0.1 +/‐0.03(Pageetal2006)(WMAP5:0.087+/‐0.017)

II.REIONIZATION

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Lookingmorecarefully….

•  Differencesatl<30onEEandBBspectraare~10%‐20%

t=0.0845

(seee.g.HolderHaiman,Kaplinghat,Knox03,Hu&Holder03Colomboetal05)

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Ques-ons

•  Currentanalysismodelsassume“sharp”reioniza-on(possiblyincorrect).Howmuchthisassump-onaffectsPlanckparameteres-ma-on?

•  Canyouavoidmakingthisassump-on?Atwhichcost?Areotherparametersaffectedbythechoice?

•  Canweconstrainsomethingmorethanjustτ?•  Ifyoudogiveupthatassump-on,whichisthebeststrategytoincorporateamoregeneralreioniza-onhistory?

Colombo&Pierpaoli08

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•  GetCl'sformodelswithdifferentxe(z)butsame t andothercosmologicalparameters•  BuildsimplePlancksimulateddatafor143GHzwithfsky=80%skycoverage

•  MCMCanalysisofsimulateddataassumingasharpreioniza-on

Howbigistheproblem?

fiducialmodels:sharp,extended,two‐step,doublewitht=.0845

t=.0845modelmean sbiasSR .0844.0045 ‐.02ER .0850.0044 .112R .0895.0046 1.09DR .0861.0046 .35log[1010As]=3.135modelmeansbiasSR 3.1349.0092 ‐.01ER 3.1356.0092 .072R 3.1452.0094 1.09DR 3.1382.0093 .34r=0.1modelmeansbiasSR .104.029 .14LR .096.029 ‐.142R .088.028 ‐.43DR .092 .030 ‐.26

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“Agnos-c”approachestoreioniza-on•  Binnedreioniza-on(Lewis,Weller,BaZye06)

•  PrincipalComponentofreioniza-onhistory(Mortonson&Hu07)

–  Assumeafiducialbinnedreioniza-onhistoryxe

fid(zi),i=1,2,...,Nzzmin≤zi≤zmax–  EvaluatetheFisherMatrixfortheEEmodes

–  TheprincipalcomponentsSn(zi)aretheeigenvectorsoftheFishermatrix

–  Agenericreioniza-onhistoriycanbespecifiedonthisbasisbyasetofcoefficientsµnas:

–  Evaluateasubsetofthesefromthedata

xe(z) = xfid + ∑ µnSn(z)

Xefid=1,z<60.15,6<z<30

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Reconstruc-ngreioniza-on•  Underlyingmodel:sharpreioniza-on(i.e.:wewanttobenasty)•  Analyzedwith6binsbetweenz=6andz=30(Δz=4)

Black:binnedreioniza-onRed:5Eigenmodes

•  Samebiasinrobservedinthetwomethods(otherparametersarerecoveredequallywell)

•  Binnedspectralesswellreconstructed(alotofcorrela-onbetweenbins)

•  Computa-onally:4-mesmoreexpensive

•  BinnedmodelingmaybebeZersuitedtointroduceexternalconstraintsonreioniza-on

Colombo&Pierpaoli08

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EPIC,PlanckandWMAPreioniza-on

WMAP5PlanckEPIC

Zaldarriagaetal2008

PlanckwillgreatlyimproveonWMAPonhighredshi{reioniza-on.

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“Experimental”Heliumcontribu-ontothemeasurementofreioniza-onhistory

BeingabletousemorecoolingheliumwouldresultinbeZerconstraintsonthereioniza-onhistoryathighredshi{s.

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Howwellwillafutureexperimentperform?

•  Prac-callyCVlimitedfordeterminingtheintegratedreioniza-onsignal•  Notverygoodindeterminingtheextentofreioniza-on•  WillhelpinrelievingsomemilddegeneraciesPlanckmayhave.

Zaldarriagaetal08

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III:Whatwewantandwhatweget:foregroundsissues

=+

CMB

Foregrounds

ObservaPons(realWMAPmaps!)

Galaxyclusters

GalacPcdust

Synchrotronemission

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Thesearchforr

•  B‐modepolariza-onwouldbeasmokinggunforinfla-onbutpolarizedforegroundsmaybealimi-ngfactor.

Pageetal07•  Howmuchdoweknowaboutpolarizedforegrounds

•  Howwellcanwehandlethem

•  Ul-mately,howlowofanrcanwemeasure,givenourcurrentknowledgeofforegrounds

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Characterizingdiffuseforegrounds:Cross‐correla-onmethod

•  Idea:assessforegroundcontribu-ontoWMAP5mapandtheirproper-esviacross‐correla-onswithdifferenttemplates(seeDaviesetal06)

•  Objec-ves:performananalysisatdifferentla-tudes,alsoincludingpolariza-on

•  Advantages:non‐parametric•  Disadvantages:notlocalized,dependentontherepresenta-onoftheforegroundbythetemplate.

Syhchrotron:HaslamDust:FDS8Free‐free:Hα(Dickinsonetal03)

Macellarietal,inprep.

Templates:

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Intensityresults

•  Evidenceforanomalousdustemissionplusthermaldust,Free‐freeandsynchrotronspectralindexwithnosurprises.

CfrDaviesetal06

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Intensityresultsbyla-tude

•  Dustcorrelatedcomponentdominantonsynchrotronatlowandintermediatela-tudes

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Polariza-onemissivity

•  Synchrotrondominantatlowfrequencies,dustat94GHz.

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•  Totaldustfrac-onalpolariza-onbelow5%.•  Trendinla-tudeandfrequency.

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Synchrotronspectralindex

•  Consistentresultsintemperatureandpolariza-on,flaZeningathigherla-tudes

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•  Synchrotronfrac-onalpolariza-onsmallonthegalac-cplane,reaching40‐50%atintermediate/highgalac-cla-tudes

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IV:Impactofforegroundsonrdetermina-on

•  Methodforcomponentsepara-on:SMICA(Cardosoetal2008)

•  Maps:implemen-ngBforthethePlanckSkyModel•  Advantages:“bestpowerspectrumreconstruc-on”•  Disadvantages:noforegroundreconstruc-on.•  Foregroundconsidered:

–  Synchrotron(withrunning)–  Thermaldust(differentamplitedes/powerspectra)–  (extra‐galac-csources)–  (Lensing)

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X=vectorinfrequencyofobserva-ons:

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Thelikelihood

•  Insteadoftheusual:Thelikelihoodisgivenby:

WhereKisthesprectralmismatchbetweenthematrices:

Wemaximizethelikelihoodwithrespectto

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PreviousaZempts:

•  Verdeetal06:Fishermatrixapproachwithinstrumentalnoiseand~10%foregroundresiduals

•  Amblardetal07:Wienerfilteredmapsandes-mateoferrorsincludingforegroundresiduals(needtoknowcovariancesofyourforegrounds!)

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Foregroundlevelsandmodeling

ForegroundmodeledoutofthePSM

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Forecastsforfutureexperiments

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VariantstothemainmodelPointsources(EPIC‐CS)

Lensing(r=0.001)

Varia-onsinthesynchrotronspectralindex

Varia-onsinthedust

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Conclusions•  WMAPnaïveparameteres-matesabout30%lowerthanrealones.

Planckmayimprovebyseveralfactors,especiallyonr(with1/2oftheinforma-oncomingfromtheBBpowerspectrum).Es-matesconsideringforegroundsuggestthatatr~0.1foregroundsshouldnotdegradethesignificanceofthedetec-on.Planckwillcomplementfuturesurveysin…….

•  Allowingforageneralreioniza-onmodelwithinPlanckparameteres-ma-onisnecessarynottobiasrandpowerspectrumamplitude.Theimplementa-onisprac-callydoable.Bothprincipalcomponentorredshi{binsmaybeused.FutureCMBpolariza-onmissionsallperformwellNogoodreconstruc-onofreioniza-onhistoryistobeexpected,apartfromdiscrimina-ngbroadlybetweenearlyandlatecontribu-ontotheop-caldepth.

•  WMAP5Cross‐correla-onanalysis:dustpolariza-onbelow6%,dependentonfrequencyandla-tude.Synchrotronpolariza-onincreasingwithla-tudeupto40‐50%.Synchrotronspectralindexconsistentintemperatureandpolariza-on,flaZeningathigherla-tudes.

•  AsforfutureCMBpolariza-onmissions,foregroundshouldnotlimitdetec-onifr~0.001,withactualperformancesdependingonconfigura-on.Varia-onsinthediffusecomponentsisirrelevantfortheresults.Pointsources,ifneglected,biastheresults.


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