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 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
- correlated isocurvature amplitude
- uncorrelated isocurvature amplitude
- cosmic string tension
- neutrino mass sum
- neutrino sound speed
- dark matter annihilation
- light-axion fraction (Renee Hlozek)
With info on what data they can handle and who is available to run them
- Errard/Feeney code (Josquin Errard)
- Allison et al code - primary plus lensing plus cross-correlations plus BAO (Danielle Leonard, Jo Dunkley)
- Madhavacheril's code (similar to Allison et al) (Mat Madhavacheril)
- de Bernardis code - includes kSZ likelihood (Francesco de Bernardis)
- tSZ likelihood?
- Planck at l<30 over 80% of sky
- S4 TT/TE/EE/kk over 40% of sky, 30<l < lmax
- Planck TT/TE/EE from 30<l<2500 over additional 40% of sky
- Or neglect l<30 TE/EE and use tau prior 0.06+-0.01
- lmax(TT)=3000 unless explicit foreground cleaning is done in code
- lmax(TE,EE)=4000 unless explicit foreground cleaning done in code
- quadratic estimator with iterative delensing
- Gaussian likelihood neglecting T/E/k covariance is ok, but non-Gaussian better (what codes have that?)
- option to add DESI BAO
Nominal test case
- Single channel (e.g. 150 GHz) at 1 uK/amin, 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