Difference between revisions of "RobustForecast"
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=== IIb. Curvature & Running ===
=== IIb. Curvature & Running ===
Revision as of 08:04, 20 May 2016
Robust forecasts on fundamental physics from the foreground-obscured, gravitationally-lensed CMB polarization
These forecasts are based on the framework developed in http://arxiv.org/abs/1509.06770. This formalism first performs a Fisher estimate of a given experimental configuration (sky fraction, frequencies, bandwidths, white noise levels and beams) to clean foregrounds (one- or two-component dust and synchrotron) from the CMB using a parametric maximum-likelihood method. Here, we take cleaning foregrounds to constitute estimating their spectral indices. The residual foregrounds and increased CMB noise level are propagated self-consistently to a delensing forecast (EBEB [iterative or otherwise], CMBxCIB or CMBxLSS); the resulting delensing residuals and lensing deflection noise are propagated to a standard CMB parameter Fisher code in which we marginalize over the amplitude and multipole dependence of any remaining foreground residuals. This formalism can combine pairs of experiments with different sky coverage, and can constrain numerous extensions to the standard model, namely , , , , , , , and . A schematic of the formalism is plotted below.
A web interface to the code is available on NERSC: http://portal.nersc.gov/project/mp107/index.html. The tool allows you to look at specific instrumental configurations (sensitivities, frequencies, bandpasses, FWHM), choose dust and synchrotron spectral indices, sky components, delensing options (CMBxCMB, CMBxCIB), marginalization for cosmological constraints, and many other options. A NERSC account tied to the mp107 user group is needed, but is simple to obtain.
I. Forecast on inflation:
These forecasts are based on the optimized experimental configurations provided by Victor Buza here. In summary, there are six configurations, assuming three values of (0.01, 0.05 and 0.1) and two values of (0 and 0.01). The experiment is broken down into a multi-frequency "degree-scale" effort aimed at cleaning foregrounds and a single-frequency (assumed 145 GHz, 1' FHWM) "arcmin-scale" effort aimed at delensing; both efforts are assumed to have access to a multipole range of . We combine all of these bands together and pass to our component-separation, delensing and Fisher formalism, assuming dust and synchrotron are present and using iterative CMB EBEB delensing (we can also provide constraints for no/CIB/LSS delensing). We perform the same procedure for Planck (we don't use the WMAP channels), and combine the two Fisher matrices together. We assume a simple CDM+ model, and constrain it using , , and information.
Clearly we have more optimistic results than Victor. This may be because we're using polarization noise levels rather than temperature [updated numbers now assume temperature noise values were quoted]; we also consider fewer foreground parameters than Victor does. There could also be differences in the way we're delensing. A further possibility is that we are using different foreground inputs: our foreground templates are extrapolated from Planck results, which specify the amplitude of the dust power in the cleanest 24, 33, 42, 53, 63 and 72% of the sky. As a result, the level of the foregrounds changes with . Essentially, we should discuss!
II. Forecast on other cosmological parameters , , &
We derive here results which aim at being compared to Erminia’s forecasts: https://cosmo.uchicago.edu/CMB-S4workshops/index.php/ForecastNu Some discrepancies might appear due to different assumptions, priors, polarized vs. total intensity sensitivity, etc.
We look at the variation of cosmological constraints (neutrino mass, Neff, running and curvature) as a function of polarized sensitivity or resolution. We combine the one-channel CMB-S4 with Planck and/or DESI BAO measurements. Results are summarized in this figures below, which can also be downloaded as the following presentation https://cosmo.uchicago.edu/CMB-S4workshops/images/Results_cosmo_params_vs_uKarcmin_FWHM.pdf.