good_fede = []
good_zc = []
for i in range(N):
params['m_axion'] = maxion_table[i]
for j in range(N):
params['f_axion'] = faxion_table[j]
for k in range(N):
params['scf_parameters'] = '%.5f,0.0' % theta_initial_table[k]
print 'try:', maxion_table[i], faxion_table[
j], theta_initial_table[k]
# try to solve with a certain cosmology, no worries if it cannot
try:
cosmo.set(
params) # Set the parameters to the cosmological code
cosmo.compute() # solve physics
print 'fac:', cosmo.fEDE(), 'log10(zc):', cosmo.zc()
print 'good!', maxion_table[i], faxion_table[
j], theta_initial_table[k]
# good_maxion[i][j][k]=maxion_table[i]
# good_faxion[i][j][k]=faxion_table[j]
# good_theta[i][j][k]=theta_initial_table[k]
good_maxion.append(np.log10(maxion_table[i]))
good_faxion.append(np.log10(faxion_table[j]))
good_theta.append(theta_initial_table[k])
good_fede.append(np.log10(cosmo.fEDE()))
good_zc.append(cosmo.zc())
except CosmoComputationError: # this happens when CLASS fails
# print CosmoComputationError
print 'this one was bad...'
bad_maxion.append(np.log10(maxion_table[i]))
bad_faxion.append(np.log10(faxion_table[j]))
M = Class()
# Table I of 1908.06995, third column, best-fit values
# Note: f and m found by trial-and-error to give the best-fit fEDE=.12, zc=10^3.562=3647.
M.set({'f_scf': 3.98e+26, 'm_scf': 5.31e-28, 'thetai_scf': 2.83, 'A_s': 2.215e-09, 'n_s': 0.9889, '100*theta_s': 1.04152, 'omega_b': 0.02253, 'omega_cdm': 0.1306, 'm_ncdm': 0.06, 'tau_reio': 0.072})
#'non linear':can choose 'halofit' or 'HMCODE'
M.set({'non linear':'HMCODE','N_ncdm':1, 'N_ur':2.0328, 'Omega_Lambda':0.0, 'Omega_fld':0, 'Omega_scf':-1, 'n_scf':3, 'CC_scf':1, 'scf_parameters':'1, 1, 1, 1, 1, 0.0', 'scf_tuning_index':3, 'attractor_ic_scf':'no', 'output':'tCl pCl lCl mPk', 'lensing':'yes', 'l_max_scalars':2508, 'P_k_max_h/Mpc':20,'z_max_pk':4.})
M.compute()
print(M.Omega_m())
baM = M.get_background()
fEDE = M.fEDE()
z_c = M.z_c()
baH = baM['H [1/Mpc]']
baT = baM['conf. time [Mpc]']
baa = 1/(1 + baM['z'])
bV = baM['V_e_scf']
bpp = baM["phi'_scf"]
baCrit = baM['(.)rho_crit']
rho_scf = (bpp*bpp/(2*baa*baa) + bV)/3.
plt.figure(figsize=(10,10))
plt.rcParams.update({'font.size': 18})
plt.plot(baM['z'],rho_scf/baCrit,lw=2,c='k')
plt.axhline(fEDE,c='r',ls='--')
