Difference between revisions of "Forecasting"
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Revision as of 13:42, 11 April 2016
Forecasting non-r parameters
The expectation is that these forecasts will be done mainly using Fisher forecasts for the Science Book, with prudent use of frequencies and ell-range to avoid being over-optimistic about the impact of Galactic and extragalactic foregrounds and noise from the ground.
Names of people responsible for generating forecasts in brackets. Sign yourself up and we can divide up tasks when we speak if there are multiple people.
- LCDM 6-parameters
- curvature (Danielle Leonard)
- birefringence (Vera)
- correlated isocurvature amplitude (Cora, Kimmy Wu)
- uncorrelated isocurvature amplitude (Cora, Kimmy Wu)
- axion isocurvature (Renee, Doddy, Dan)
- cosmic string tension (Renee)
- primordial magnetic field
- neutrino mass sum (Mat, Neelima)
- Neff (Dan G?, Mat, Neelima) -- with delensing of TT & EE (Joel, Alex, Dan)
- Yp (with delensing of TT & EE (Joel, Alex, Dan)
- neutrino sound speed
- dark matter annihilation (Cora)
- dark matter interactions (Cora)
- utralight-axion density (Renee, Doddy Marsh, Dan Grin)
- r with delensing (Neelima, Mat)
Here is place-holder for some suggested fiducial parameters and step-sizes, can be different though.File:Params steps.pdf
With info on what data they can handle and who is available to run them during next two months
- Errard/Feeney code (Josquin Errard)
- Allison et al code - lensed TT/TE/EE plus kk plus BAO, can take in non-white N_ell but no explicit FG handling (Danielle Leonard, Jo Dunkley)
- Extension of Allison et al code for axions (Renee Hlozek)
- Stony Brook code - TT/TE/EE/kk with iterative delensing plus BAO, can take in non-white N_ell but no explicit FG handling, being expanded to include LSST shear and cluster counts with halo lensing (Mat Madhavacheril, Neelima Sehgal, Nam Nguyen)
- de Bernardis code - includes kSZ likelihood (Francesco de Bernardis)
- Manzotti code- similar to Allison et al and already partially checked against that code; used for http://arxiv.org/abs/1512.02654 (Alessandro Manzotti)
- CITA code - includes delensing of spectra to all orders; forecasts of delensed covariances are in progress (Joel Meyers, Alex van Engelen, Dan Green)
- who has a tSZ likelihood?
- other codes and people?
- S4 TT/TE/EE/kk over 40% of sky, 30<ell < lmax
- Planck TT/TE/EE from 30<l<2500 over additional 20% of sky. Use these 'Planck-pol' specs for noise:File:Planck pol.pdf
- Planck TT at l<30 over 80% of sky
- Tau prior 0.06+-0.01
- lmax(TT)=3000 unless explicit foreground cleaning is done in code for kSZ etc
- lmax(TE,EE)=5000 unless explicit foreground cleaning done in code
- kk reconstructed from 30<l<lmax using MV estimate
- quadratic estimator for lensing, ideally with iterative delensing
- Gaussian likelihood neglecting T/E/k covariance is ok, but non-Gaussian better (do any codes have full lensed T/E/B/k covariance?)
- non-linear power spectrum for kk, e.g. ok to use halofit in CAMB
- option to add DESI BAO. These are placeholder for forecast rs/DVs.File:Bao desi.pdf
- cluster masses calibrated with LSST lensing or CMB halo lensing (need to refine what that means)
Nominal test case
- Single channel (e.g. 150 GHz) at 1 uK/amin in T and 1.4uK/amin in P, 3 arcmin resolution.
- White noise, no FG inflation
- Useful if your code can spit out errors as function of noise level in 1-10 uK/arcmin range and resolution in range 1-10 arcmin.
- Define multiple frequencies of the survey
- Decide if an N_ell that captures non-white-noise is necessary
- Define residual FG level if any