Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Leibniz Institute for Astrophysics Potsdam wikipedia , lookup
Indian Institute of Astrophysics wikipedia , lookup
Astronomical spectroscopy wikipedia , lookup
Birefringence wikipedia , lookup
Polarization (waves) wikipedia , lookup
Cosmic microwave background wikipedia , lookup
Photon polarization wikipedia , lookup
CMB Polarization with the CBI Jonathan Sievers (CITA) The CBI Collaboration Caltech Team: Tony Readhead (Principal Investigator), John Cartwright, Clive Dickinson, Alison Farmer, Russ Keeney, Brian Mason, Steve Miller, Steve Padin (Project Scientist), Tim Pearson, Walter Schaal, Martin Shepherd, Jonathan Sievers, Pat Udomprasert, John Yamasaki. Operations in Chile: Pablo Altamirano, Ricardo Bustos, Cristobal Achermann, Tomislav Vucina, Juan Pablo Jacob, José Cortes, Wilson Araya. Collaborators: Dick Bond (CITA), Leonardo Bronfman (University of Chile), John Carlstrom (University of Chicago), Simon Casassus (University of Chile), Carlo Contaldi (CITA), Nils Halverson (University of California, Berkeley), Bill Holzapfel (University of California, Berkeley), Marshall Joy (NASA's Marshall Space Flight Center), John Kovac (University of Chicago), Erik Leitch (University of Chicago), Jorge May (University of Chile), Steven Myers (National Radio Astronomy Observatory), Angel Otarola (European Southern Observatory), Ue-Li Pen (CITA), Dmitry Pogosyan (University of Alberta), Simon Prunet (Institut d'Astrophysique de Paris), Clem Pryke (University of Chicago). The CBI Project is a collaboration between the California Institute of Technology, the Canadian Institute for Theoretical Astrophysics, the National Radio Astronomy Observatory, the University of Chicago, and the Universidad de Chile. The project has been supported by funds from the National Science Foundation, the California Institute of Technology, Maxine and Ronald Linde, Cecil and Sally Drinkward, Barbara and Stanley Rawn Jr., the Kavli Institute,and the Canadian Institute for Advanced Research. Whence Polarization? Polarization comes from Thomson scattering during recombination Quadrupole seen by electrons produces polarization. Dominant source from velocity modes – so out of phase with TT Pol’n lines up with modes, so no BB type Strongly predicted by TT – good check on model. No Dipole No net extra radiation from left/right or top/bottom, so no polarization Doppler shift makes dipole pattern, so moving electron in an isotropic field has no polarization. Quadrupole More radiation from left/right than top/bottom. Electron moves up/down, and so scattered radiation is polarized. E Mode Only If velocity converges, then electron moves normal to wave +E If diverges, electron moves along wave –E Never moves tilted, so no B radiation The Instrument 13 90-cm Cassegrain antennas • 78 baselines 6-meter platform • Baselines 1m – 5.51m 10 1 GHz channels 26-36 GHz • HEMT amplifiers (NRAO) • Cryogenic 6K, Tsys 20 K Single polarization (R or L) • Polarizers from U. Chicago Analog correlators • 780 complex correlators Field-of-view 44 arcmin • Image noise 4 mJy/bm 900s Resolution 4.5 – 10 arcmin The CBI Adventure… CBI located at 5080 meters in Atacama desert, Chile. Area is used by NASA as a proxy for Mars for testing/developing equipment. Land mines along border w/ Bolivia Steve Padin wearing the cannular oxygen system The CBI Adventure… Two winters a year! The roads fill with snow. The CBI Adventure… Volcan Lascar (~30 km away) erupts in 2001 CMB Interferometers Interferometers are a very clean way of measuring CMB. Robust with respect to instrumental systematics. Interferometers directly measure Fourier Plane • Resolution set by field of view Interferometers do not pick up large scale power • Gain fluctuations don’t see monopole/dipole Polarization: • Directly Measure E and B (modulo FOV) • Correlate circular electric fields to directly measure linear pol’n • Do not subtract two nearly equal signals uv coverage with mosaic beam Polarization – Stokes parameters CBI receivers can observe either RCP or LCP • cross-correlate RR, RL, LR, or LL from antenna pair Mapping of correlations (RR,LL,RL,LR) to Stokes parameters (I,Q,U,V) : Intensity I plus linear polarization Q,U important • CMB not circularly polarized, ignore V (RR = LL = I) • parallel hands RR, LL measure intensity I • cross-hands RL, LR measure polarization Q, U R-L phase gives Q, U electric vector position angle E and B modes A useful decomposition of the polarization signal is into “gradient” and “curl modes” – E and B: ~ ~ ~ ~ i 2 v Q ( v) i U ( v) E ( v) i B ( v) e v tan RL k V 1 v u E & B response smeared by phase variation over aperture A ~ ~ i 2 ( v k ) RL (u k ) d v Pk ( v) [ E ( v) i B ( v)] e ek 2 interferometer “directly” measures E & B! CBI 2000+2001 (TT), WMAP, ACBAR, BIMA Readhead et al. ApJ, 609, 498 (2004) astro-ph/0402359 CMB Primary SZE Secondary EE – A Separate View Excellent check on consistency of standard cosmological model. One example: pathological primordial spectra with very different params can mimic TT. However, EE changes dramatically. Sep ‘04: CBI, DASI, Capmap Spectrum Extraction Two step pipeline. First step – compress ~few 10^6 visibilities into 10^4 polarization estimators. Keep track of signal covariances, sources, ground signal etc. (Myers et al.) Second – do exact maximum likelihood on 10^4 estimators, get spectrum, window functions, likelihood surfaces etc. Analysis done on CITA McKenzie cluster. Stage 1 ~couple hours. Stage 2, ~10 minutes for spectrum, longer for other stuff. CBI Polarization Power Spectra Previously published pol’n detection – Science 306,836 NEW DATA ~ 50% increase presented here 7-band fits (Dl = 150 for 600<l<1200) 7-band spectra consistent with WMAPext model (TT from WMAP, ACBAR, 2000 + 2001 CBI) Consistent with old pol’n data, errors smaller New Spectra! Shaped Cl Fit Use WMAP’03+CBI TT+ Acbar best-fit Cl in signal covariance matrix • bandpower relative to fiducial PS • compute for single band encompassing all l Results for new CBI pol’n data • EE qB = 0.97 ± 0.14 (68%) • EE likelihood vs. zero : equivalent significance 10.1 σ • TE qB = 0.85 ± 0.25 • BB qB = 1.2 ± 1.8 μK2 No evidence for foregrounds Likelihood of EE Amplitude vs. TT Prediction Parameters w/CBI (old) Paramaters calculated using Antony Lewis’s MCMC code, COSMOMC Old CBI mosaics (Readhead et al. 2004) overlap with polarization mosaics. Not allowed to combine sample-limited part of spectra. Thermal limited (ℓ>1000) old spectrum included. New spectrum only for ℓ<1000. First time EE included for measuring parameters (though impact of EE quite small) Blue=WMAP Red=WMAP+Sep ’04 (Working on new data) Green=WMAP+Sep ‘04+CBI7 high-ℓ Params, contd… What Can We Get From EE? Sensitivity not so high that can get precision cosmology in many dimensional space. Ask question on restricted parameter range gives tighter results (3-15%, depending on questions asked) θ/θ0 Angular size of sound horizon at LSS should be same for TT and EE. CBI only has multiple solutions (shift spectrum by one peak). DASI removes degeneracy, but less sensitive. CBIold+DASI give scale vs. TT of 1.02 +/0.03. CBI θ/θ0 Peaks can slide to left for a degeneracy with CBI data only. DASI θ/θ0 DASI goes to lower ell removing degeneracy. DASI θ/θ0 Combination of CBI+DASI zeroes in on proper peak with few % accuracy. pattern shift parameter 0.998 +- 0.005 WMAP1+CBIpol TT/TE/EE Evolution: Jan00 11% Jan02 1.2% Jan03 0.9% Mar03 0.4% EE ONLY: 4% phase check of EE cf. TT pk/dip locales, amp too 1.00 +- 0.04 CBIpol+DASIpol EE only Isocurvature Isocurvature puts peaks in different places from adiabatic. We use seed isocurvature model (ask Antony for details) and find both EE and TE prefer adiabatic w/ iso consistent with zero. Isocurvature Cont. Normalize seed iso spectrum to total power expected from TT adiabatic prediction Fit shapes for both EE, TE EE adi =1.00±0.24, iso=0.03±0.20 TE adi = 0.86±0.26, iso=0.04±0.25 2D Iso/Adi Likelihood - EE EE only, isocurvature and adiabatic are rather strongly (anti)correlated. 2D Iso/Adi Likelihood - TE TE only, isocurvature and adiabatic are somewhat weakly correlated. Noisier than EE. 2D Iso/Adi Likelihood – TT+EE Combined EE and TE does well as TE valley is tilted. Effectively lops of ends of EE valley. Summary Precision cosmology here in total power, coming along in polarization (CBI EE now > 10σ) Interferometers are a very clean, stable way of directly measuring power spectrum EE polarization consistent with TT prediction both in shape and amplitude Can measure distance to last scattering surface to 4% in pol’n only. Find most polarization power observed on sky comes from adiabatic, not (seed) isocurvature. Non-Gaussianity cont. Check nonGaussianity in each bin Might show ldependent effect (such as foreground) Individual bins consitent with Gaussian. Non-Gaussianity Decompose data into uncorrelated S/N eigenmodes for each bin. Pick out modes expected to have signal Check distribution for nonGaussianity Keep total of 5500 modes TT, 3800 EE – everything consistent with Gaussian First check of EE Gaussianity! More tests coming… New: CBI EE Polz’n Phase Parameterization 1: envelope plus shiftable sinusoid • fit to WMAP+ACBAR+CBI TT fiducial spectrum using rational functions = 0° : EE prediction = 180°: aligned with TT 1CEE a f g sin k CBI EE Polarization Phase Peaks in EE should be offset one-half cycle vs. TT • allow amplitude a and phase to vary best fit: a=0.94 = 24°±33° (Dc2=1) Dc2(1, 0°)=0.56 CBI Fine EE w/ Best Fit Phase CBI Projections Will BB (lensing) be foreground limited? The CBI Collaboration Caltech Team: Tony Readhead (Principal Investigator), John Cartwright, Clive Dickinson, Alison Farmer, Russ Keeney, Brian Mason, Steve Miller, Steve Padin (Project Scientist), Tim Pearson, Walter Schaal, Martin Shepherd, Jonathan Sievers, Pat Udomprasert, John Yamasaki. Operations in Chile: Pablo Altamirano, Ricardo Bustos, Cristobal Achermann, Tomislav Vucina, Juan Pablo Jacob, José Cortes, Wilson Araya. Collaborators: Dick Bond (CITA), Leonardo Bronfman (University of Chile), John Carlstrom (University of Chicago), Simon Casassus (University of Chile), Carlo Contaldi (CITA), Nils Halverson (University of California, Berkeley), Bill Holzapfel (University of California, Berkeley), Marshall Joy (NASA's Marshall Space Flight Center), John Kovac (University of Chicago), Erik Leitch (University of Chicago), Jorge May (University of Chile), Steven Myers (National Radio Astronomy Observatory), Angel Otarola (European Southern Observatory), Ue-Li Pen (CITA), Dmitry Pogosyan (University of Alberta), Simon Prunet (Institut d'Astrophysique de Paris), Clem Pryke (University of Chicago). The CBI Project is a collaboration between the California Institute of Technology, the Canadian Institute for Theoretical Astrophysics, the National Radio Astronomy Observatory, the University of Chicago, and the Universidad de Chile. The project has been supported by funds from the National Science Foundation, the California Institute of Technology, Maxine and Ronald Linde, Cecil and Sally Drinkward, Barbara and Stanley Rawn Jr., the Kavli Institute,and the Canadian Institute for Advanced Research. New: DASI EE θ/θ0 Leitch et al. 2004 5 bin EE bandpowers + covariance matrix plus approximate window functions New: CBI + DASI EE θ/θ0 Combined constraints on θ model: CBI a=0.67 overtone island: suppressed by DASI data CBI+DASI phase lock: θ/θ0= 1.02±0.03 a=0.78±0.15 (low DASI) CBI Projections 2 EE phase: July 2004 vs. 2006 July 2004 (Readhead et al.) 2006 Forecast Consistency w/ WMAP Spectra consistent with the cosmological model from WMAPext dataset χ2 = 7.98 TT, 3.77 EE, 4.33 BB (vs. 0), and 5.80 TE for 7 dof. CMB Interferometers CMB issues: • Extremely low surface brightness fluctuations < 50 mK Large monopole signal 3K, dipole 3 mK Polarization less than 10% signal < 5 mK • No compact features, approximately Gaussian random field • Foregrounds both galactic & extragalactic Traditional direct imaging • Differential horns or focal plane arrays Interferometry • Inherent differencing (fringe pattern), filtered images • Works in spatial Fourier domain • Element-based errors vs. baseline-based signals • Limited by need to correlate pairs of elements • Sensitivity requires compact arrays