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The largest fluctuation in the CMB sky is the CMB dipole, which is believed to be caused by the motion of our observation frame with respect to the CMB rest frame. This motion accounts for the known motion of the Solar System barycentre with a best-fit amplitude of 369 km/s, in the direction ($ell= 264^circ$, $b=48^circ$) in galactic coordinates. Along with the CMB dipole signal, this motion also causes an inevitable signature of statistical anisotropy in the higher multipoles due to the modulation and aberration of the CMB temperature and polarization fields. This leads to a correlation between adjacent CMB multipoles causing a non-zero value of the off-diagonal terms in the covariance matrix which can be captured in terms of the dipolar spectra of the bipolar spherical harmonics (BipoSH). In our work, we jointly infer the CMB power spectrum and the BipoSH spectrum in a Bayesian framework using the $textit{Planck}$-2018 $texttt{SMICA}$ temperature map. We detect amplitude and direction of the local motion consistent with the canonical value $v=369$ km/s inferred from CMB dipole with a statistical significance of $4.54sigma$, $4.97sigma$ and $5.23sigma$ respectively from the masked temperature map with the available sky fraction $40.1%$, $59.1%$, and $72.2%$, confirming the common origin of both the signals. The Bayes factor in favor of the canonical value is between $7$ to $8$ depending on the choice of mask. But it strongly disagrees with the value inferred from quasar distribution from the Wide-field Infrared Survey Explorer data set with a value of the Bayes factor about $10^{-11}$.
Analysis of the Planck 2018 data set indicates that the statistical properties of the cosmic microwave background (CMB) temperature anisotropies are in excellent agreement with previous studies using the 2013 and 2015 data releases. In particular, th
We present a novel estimate of the cosmological microwave background (CMB) map by combining the two latest full-sky microwave surveys: WMAP nine-year and Planck PR1. The joint processing benefits from a recently introduced component separation method
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