We analyze seven year and nine year WMAP temperature maps for signatures of three finite flat topologies M_0=T^3, M_1=T^2 x R^1, and M_2=S^1 x R^2. We use Monte-Carlo simulations with the Feldman-Cousins method to obtain confidence intervals for the
size of the topologies considered. We analyze the V, W, and Q frequency bands along with the ILC map and find no significant difference in the results. The 95.5% confidence level lower bound on the size of the topology is 1.5L_0 for M_0, 1.4L_0 for M_1, and 1.1L_0 for M_2, where L_0 is the radius of the last scattering surface. Our results agree very well with the recently released results from the Planck temperature data. We show that the likelihood function is not Gaussian in the size, and therefore simulations are important for obtaining accurate bounds on the size. We then introduce the formalism for including polarization data in the analysis. The improvement that we find from WMAP polarization maps is small because of the high level of instrumental noise, but our forecast for Planck maps shows a much better improvement on the lower bound for L. For the M_0 topology we expect an improvement on the lower bound of L from 1.7L_0 to 1.9L_0 at 95.5% confidence level. Using both polarization and temperature data is important because it tests the hypothesis that deviations in the TT spectrum at small l originate in the primordial perturbation spectrum.
We place limits on semiclassical fluctuations that might be present in the primordial perturbation spectrum. These can arise if some signatures of pre-inflationary features survive the expansion, or could be created by whatever mechanism ends inflati
on. We study two possible models for such remnant fluctuations, both of which break the isotropy of CMB on large scales. We first consider a semiclassical fluctuation in one Fourier mode of primordial perturbations. The second scenario we analyze is a semiclassical Gaussian bump somewhere in space. These models are tested with the seven-year WMAP data using a Markov Chain Monte Carlo Bayesian analysis, and we place limits on these fluctuations. The upper bound for the amplitude of a fluctuation in a single Fourier mode is a<=10^(-4), while for the Gaussian bump a<=10^(-3).
