Agenda/Notes from Systematics WG telecon July 19 2017
on the call: Brendan, Paolo, Colin, Julian, Shaul, Maurizio, Joy
S4 tools (Colin)
S4 doesn't yet have an instrument design, so at this point, they are considering generic “additive systematics” == something that adds additional B-mode power and could bias a measurment of “r”
A generic noise-like systematic (not rolled off by beam) is considered
Looked at an “uncorrelated” systematic (i.e. uncorrelated from band to band) such as residual beam mismatch: a white and a 1/ell version
Also looked at a correlated systematic which can bias cross-spectra, same amplitude (in CMB units) in all bands (i.e. looks like a CMB fluctuation)
Going back to Fischer forecast, including foreground separation in frequency space: can write down what level of systematic corresponds to as a bias in “r” of 1e-4 (target of sigma_r in 5e-4)
Colin is now applying this to the S4 data challenge.
Longer term this is meant to provide a benchmark to judge systematics against as a real instrument design takes shape.
What do we need in order to perform this type of analysis for the CMB probe Imager, given our set of bands and noise levels?
Can be done just with map noise and frequency bands: though of course it assumes an analysis method based on BICEP/Kick which may or may not be applicable to a full-sky analysis.
Also noise shape for a full-sky mission is likely to be quite different. Atmosphere enters in as an ell_knee
Simple parameterization for foreground estimation: probably fine for ~3% sky, but for Probe would use a full-sky template fit.
Julian points out that there will be a map-based analysis within S4 that will perhaps test this applicability. The more pixels that are available for a full-sky map, a maximum likelihood starts to become computationally expensive.
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Summary plots
Fig 17: estimates of HFI systematic errors in EE auto-spectra vs. projected noise
Fig 18: null tests of HFI detectors
Fig 23: LFI systematic errors
Specific plots
Fig 2: noise PSDs and CSDs: correlated cosmic ray hits; Fig A.1 shows this propagated to TT/EE/BB residuals.
Fig 4: HFI far sidelobe pickup: propagated physical optics models. (note: Physical optics models were not incredibly accurate)
Fig 9: residual ADC nonlinearity with gain correction leaves low ell polarization residuals: see Fig B.13 for what it looks like on the sky
Fig 10: “Empirical transfer function” unknown systematic
Fig 13: relative (detector to detector) gain measured from dipole to better than 1e-5 level
Fig 14: ground-based vs. sky-based bandpass leakage correction
Fig 30: estimated foreground residuals in HFI
Fig A.2: HFI warm readout drifts propagated to residual power spectra
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Any other business