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- #------Experiments to test (separated with commas)-----
- data.experiments=['act_s1316_sim','Planck_lensing','Planck_lowl','Planck_highl_TTTEEE_lite']
- #------ Parameter list -------
- # data.parameters[class name] = [mean, min, max, 1-sigma, scale, role]
- # - if min max irrelevant, put to None
- # - if fixed, put 1-sigma to 0
- # - if scale irrelevant, put to 1, otherwise to the appropriate factor
- # - role is either 'cosmo', 'nuisance' or 'derived'. You should put the derived
- # parameters at the end, and in case you are using the `-j fast` Cholesky
- # decomposition, you should order your nuisance parameters from slowest to
- # fastest.
- # Cosmological parameters list
- data.parameters['omega_b'] = [ 2.2253, 1.0, 3.0, 0.028, 0.01, 'cosmo']
- data.parameters['omega_dmeff'] = [0.11919, 0.05, 0.2, 0.0027, 1, 'cosmo']
- data.parameters['100*theta_s'] = [ 1.0418, 1.0, 1.1, 3e-4, 1, 'cosmo']
- data.parameters['ln10^{10}A_s'] = [ 3.0753, 2.5, 3.5, 0.0029, 1, 'cosmo']
- data.parameters['n_s'] = [0.96229, 0.8, 1.2, 0.0074, 1, 'cosmo']
- data.parameters['tau_reio'] = [0.09463, 0.04, 0.13, 0.013, 1, 'cosmo']
- data.parameters['log10sigma_dmeff'] = [-28, -35, -18, 2, 1, 'cosmo']
- # Nuisance parameter list, same call, except the name does not have to be a class name
- data.parameters['yp'] = [0.97, 0.9, 1.0, 0.015, 1, 'nuisance']
- data.parameters['A_planck'] = [100.028, 90, 110, 0.25, 0.01,'nuisance']
- # Derived parameters
- data.parameters['h'] = [0, None, None, 0, 1, 'derived']
- data.parameters['A_s'] = [0, None, None, 0, 1e-9, 'derived']
- data.parameters['sigma8'] = [0, None, None, 0, 1, 'derived']
- # data.parameters['z_reio'] = [1, None, None, 0, 1, 'derived']
- # data.parameters['Omega_Lambda'] = [1, None, None, 0, 1, 'derived']
- # data.parameters['YHe'] = [1, None, None, 0, 1, 'derived']
- # data.parameters['H0'] = [0, None, None, 0, 1, 'derived']
- # Other cosmo parameters (fixed parameters, precision parameters, etc.)
- data.cosmo_arguments['sBBN file'] = data.path['cosmo']+'/bbn/sBBN.dat'
- data.cosmo_arguments['k_pivot'] = 0.05
- # The base model features two massless
- # and one massive neutrino with m=0.06eV.
- # The settings below ensures that Neff=3.046
- # and m/omega = 93.14 eV
- data.cosmo_arguments['N_ur'] = 2.0328
- data.cosmo_arguments['N_ncdm'] = 1
- data.cosmo_arguments['m_ncdm'] = 0.06
- data.cosmo_arguments['T_ncdm'] = 0.71611
- # These two are required to get sigma8 as a derived parameter
- # (class must compute the P(k) until sufficient k)
- data.cosmo_arguments['output'] = 'mPk'
- data.cosmo_arguments['P_k_max_h/Mpc'] = 5.
- data.cosmo_arguments['k_per_decade_for_pk'] = 100
- data.cosmo_arguments['omega_cdm'] = 1e-22
- data.cosmo_arguments['gauge']='synchronous'
- data.cosmo_arguments['tight_coupling_trigger_tau_c_over_tau_h']=0
- data.cosmo_arguments['tight_coupling_trigger_tau_c_over_tau_k']=0
- data.cosmo_arguments['background_verbose'] = 0
- data.cosmo_arguments['m_dmeff'] = 1e-3
- data.cosmo_arguments['npow_dmeff'] = 0.
- #------ Mcmc parameters ----
- data.N=100000
- data.write_step=5
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