A measurement of the polarization-temperature angular cross power spectrum of the Cosmic Microwave Background from the 2003 flight of BOOMERANG

TL;DR

The paper reports a measurement of the CMB temperature-polarization cross-correlation $\ abla \langle TE \rangle$ using eight polarization-sensitive bolometers on BOOMERANG during its 2003 flight. Employing two independent MASTER-based pipelines and Monte Carlo simulations, the authors extract TE band powers across $50 \lesssim \ell \lesssim 950$ and test TB as a foreground/systematics diagnostic, finding a significant TE signal while TB is consistent with zero. The results favor a fiducial ΛCDM model with adiabatic initial conditions, supporting the standard cosmology and the presence of coherent acoustic oscillations, while showing no large foreground contamination or instrumental bias. This work provides an independent bolometric confirmation of prior TE detections and reinforces the cosmological origin of the TE signal in the CMB.

Abstract

We present a measurement of the temperature-polarization angular cross power spectrum, <TE>, of the Cosmic Microwave Background. The result is based on $\sim 200$ hours of data from 8 polarization sensitive bolometers operating at 145 GHz during the 2003 flight of BOOMERANG. We detect a significant <TE> correlation in the $\ell$-range between 50 and 950 with a statistical significance > 3.5 sigma. Contamination by polarized foreground emission and systematic effects are negligible in comparison with statistical uncertainty. The spectrum is consistent with previous detections and with the "concordance model" that assumes adiabatic initial conditions. This is the first measurement of <TE> using bolometric detectors.

Figures (6)

• Figure 1: The $\langle TE \rangle$ power spectrum band powers for the NA (filled circles) and IT (open circles) pipelines. The upper part of the plot reports data with errorbars, the fiducial model ($\Lambda$CDM model fit to WMAP (year 1), Acbar, and CBI) as a black curve and the binned fiducial model as histogram. The middle and bottom plots are the results of two different consistency tests, obtained splitting the data in channels (WX-YZ) and in time (half 2 - half 1) respectively. In the low-$\ell$ part of the plot is evident the effect of a different weighting scheme between IT and NA, while at large multipoles the result is dominated by the same instrumental performances.
• Figure 2: The $\langle TB \rangle$ power spectrum band powers for the NA (filled circles) and IT (open circles) pipelines. The upper part of the plot reports the $\langle TB \rangle$ data with error-bars. The middle and bottom plots are the results of two different consistency tests, obtained splitting the data in channels (WX-YZ) and in time (half 2 - half 1) respectively.
• Figure 3: Likelihood of the parameters $a$ and $\Delta \ell$. Parameter $a$ is defined as the amplitude of the $\langle TE \rangle$ fiducial model, $\Delta \ell$ is the shift in multipole $\ell$ applied to the $\langle TE \rangle$ fiducial model. The continuum lines are for the Boom-erang $\langle TE \rangle$ data, the dashed lines are for $\langle TB \rangle$ data, compared to the same $\langle TE \rangle$ fiducial model. In the central plot is reported the two dimensional likelihood, $\mathcal{L}(\Delta \ell, a)$; the contours are 1, 2, and 3 $\sigma$, corresponding to 68.3, 95.4 and 99.7% of probability. The $\times$ symbol is the expected value for $\langle TE \rangle$ given the fiducial model, the + symbol is the expected value for $\langle TB \rangle$. In the right plot is reported the $\mathcal{L} (a)$ marginalizing over $\Delta \ell$, and in the top plot, the $\mathcal{L} (\Delta \ell)$ marginalizing over $a$. In the right and top plot, the gray lines are 1, 2, and 3 $\sigma$ boundaries for the $\langle TE \rangle$ data. The $\langle TB \rangle$ data likelihood is used to test the presence of foregrounds and systematic effects that would affect $\langle TE \rangle$ and $\langle TB \rangle$ in the same way. This plot is obtained using the IT dataset with a binning width of 50 multipole numbers. The NA dataset gives a similar result.
• Figure 4: Dust contamination. Filled circles are $\langle T_{dust} E_{B03} \rangle$, open circles $\langle T_{dust} B_{B03} \rangle$. The dust contamination to $\langle TE \rangle$ is two order of magnitude lower than the measured $\langle TE \rangle$. The B03 data are from the IT pipeline.
• Figure 5: Propagation of instrumental uncertainties in the $\langle TE \rangle$ error-bars. The dots are the square root of the diagonal part of the covariance matrix, relative calibration is varied by $\pm 0.8 \%$, polarization efficiency by $\pm 0.03$, time constants of the transfer function by $\pm 10 \%$, the angles of the polarizers respect to the telescope frame by $\pm 2^\circ$, and the beam (plotted as horizontal thicks) by $\pm 0.3'$. The error-bars ($\Delta C_\ell$) generated by uncertainties in instrumental characteristics are one order of magnitude lower than the errors due to noise and sampling variance (from NA pipeline here). Those error-base are not treated as an increased error, but rather as a systematic effect which is correlated bin-to-bin, and marginalized over in the parameter estimation as described in bridle2002.