filtering effects. In a departure from the MASTER algorithm, however, we calculate cross-spectra [@polenta05; @tristram05] to eliminate noise bias in the spectrum. The SPT observation strategy is well-suited to cross-spectra as it produces approximately 100 complete, independent maps for each field. The analysis is performed in the flat-sky approximation and Fourier transforms are used instead of spherical harmonic transforms. We report the power spectrum in terms of $\mathcal{D}_\ell$, where $$\mathcal{D}_\ell=\frac{\ell\left(\ell+1\right)}{2\pi} C_\ell\;.$$

Details of the power spectrum estimator have been presented in previous SPT papers, most relevantly L10, @keisler11 (hereafter K11), and R12. In the following sections, we provide an overview on the method and note differences between the current analysis and the method used by R12.

### Cross spectra {#sec:xspec}

We apply a window to the map which smoothly goes to zero at the map edges and masks point sources detected above 5$\sigma$ at 150 GHz. The individual point source masks are a 2 arcmin radius disc for sources detected between 5$\sigma$ and 50$\sigma$, with the disc size increased to 5 arcmin for sources detected above 50$\sigma$. Outside of this radius, a Gaussian taper with $\sigma_{taper}=5$ arcmin is applied.

We Fourier transform the windowed maps, and then take a weighted 