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BICEP2 I: Detection Of B-mode Polarization at Degree Angular Scales

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 نشر من قبل Clement Pryke
 تاريخ النشر 2014
  مجال البحث فيزياء
والبحث باللغة English
 تأليف P. A. R Ade




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(abridged for arXiv) We report results from the BICEP2 experiment, a cosmic microwave background (CMB) polarimeter specifically designed to search for the signal of inflationary gravitational waves in the B-mode power spectrum around $ellsim80$. The telescope comprised a 26 cm aperture all-cold refracting optical system equipped with a focal plane of 512 antenna coupled transition edge sensor 150 GHz bolometers each with temperature sensitivity of $approx300mumathrm{K}_mathrm{CMB}sqrt{s}$. BICEP2 observed from the South Pole for three seasons from 2010 to 2012. A low-foreground region of sky with an effective area of 380 square deg was observed to a depth of 87 nK deg in Stokes $Q$ and $U$. We find an excess of $B$-mode power over the base lensed-LCDM expectation in the range $30< ell< 150$, inconsistent with the null hypothesis at a significance of $> 5sigma$. Through jackknife tests and simulations we show that systematic contamination is much smaller than the observed excess. We also examine a number of available models of polarized dust emission and find that at their default parameter values they predict power $sim(5-10)times$ smaller than the observed excess signal. However, these models are not sufficiently constrained to exclude the possibility of dust emission bright enough to explain the entire excess signal. Cross correlating BICEP2 against 100 GHz maps from the BICEP1 experiment, the excess signal is confirmed and its spectral index is found to be consistent with that of the CMB, disfavoring dust at $1.7sigma$. The observed $B$-mode power spectrum is well fit by a lensed-LCDM + tensor theoretical model with tensor-to-scalar ratio $r=0.20^{+0.07}_{-0.05}$, with $r=0$ disfavored at $7.0sigma$. Accounting for the contribution of foreground dust will shift this value downward by an amount which will be better constrained with upcoming data sets.



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