# Forecasting

From CMB-S4 wiki

### 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.

#### Parameters

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
- running
- birefringence
- correlated isocurvature amplitude
- uncorrelated isocurvature amplitude
- 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)
- w
- w0,wa
- f

- 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

#### Fisher codes

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?

#### Settings

- 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)

#### Specs

*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.

*Next steps*

- Define multiple frequencies of the survey
- Decide if an N_ell that captures non-white-noise is necessary
- Define residual FG level if any