The power spectra presented here are analyzed from the input HEALPix maps using the S2HAT and PS2HAT libraries (see also arXiv:0903.2350). Custom MATLAB mex bindings interface to the (P)S2HAT library and permit us to finishing processing using the MATLAB pipeline used for standard BICEP/Keck analysis (i.e. our FFT steps are replaced with (P)S2HAT, but debiasing, suppression factor correction, etc follow the same code path as used in BK analysis; see for example arXiv:1403.3985 and arXiv:1603.05976 for more details on the BK pipeline).

This is an update to BK-style processing of DC1 maps to spectra (J. Willmert & C. Bischoff) which expands from 70 to 1000 realizations for the Gaussian foreground simulation set (01.00) and adds the PySM foreground simulation sets (01.01 and 01.02).

Short summary of processing details:

- This posting makes use of and presents the 01.00, 01.01, and 01.02 maps as discussed in 01.00 sim input maps (C. Pryke). 1000 realizations of noise and (variable \(A_L\)) lensed-ΛCDM + noise + foregrounds (aka combined) input maps have been processed to power spectra.
- No E-to-B leakage debias has been applied. The use of the PS2HAT library minimizes leakage such that this should be unnecessary (and no unlensed-ΛCDM sims were processed from which the debias would normally be taken).
- Suppression factors (from the beam function and any algorithmic/processing losses) are computed from so-called “direct BPWFs” for each frequency band. (This is different than the previous posting where a no-beam BPWF was generated and post-processed to apply a beam function.) The cross-frequency BPWFs are assumed to be the geometric mean of the auto-frequency BPWFs. See BK-VII §7.3 for a complete description of the method.
- The “real” data points are just realization 0 of the combined maps data set.

Figure 1 | Final Pager |

- Thick red : lensed-ΛCDM scalars
- Thick black : Real data
- Colored : lensed-ΛCDM + noise + foreground realizations

- thick red : lensed-ΛCDM
- thin gray : s+n+f simulations with lensed-ΛCDM (sim type 5) and foregrounds (sim type 3) as signal, debiased with noise (sim type 6)
- thick gray : mean of sims (thin gray)
- red points with blue error bars : real data, debiased with the noise, uncertainties from the spread of the s+n+f sims (thin gray)

- thin gray : s+n+f sims
- thin red : 1 sigma contours
- thin green : 2 sigma contours
- thick black + markers : real data
- red markers : bins that go into chi2 analysis

Note: The contours mark the simulated bandpower in each bin closest to the respective percentile.

- red vertical : real data
- blue : distribution from s+n+f sims
- green : chi2 probability distribution fitted to blue

- red vertical : real data
- blue : distribution from s+n+f sims

- red : std of s+n+f sims
- blue : std of noise-only sims

Note: Remember that bandpower is a variance. Hence bandpower error bar is the std of a variance. This means noise and sample fluctuation components straight add, no quadrature — i.e. the difference between blue and red is the signal fluctatution component.

- [01.00_sim_input_maps]
- 01.00 sim input maps (C. Pryke)
- [20170224_cmbs4_dc1_final]
- BK-style processing of DC1 maps to spectra (J. Willmert, C. Bischoff)