def __init__(self,
z,
k,
mu,
k_par,
k_perp,
code = 'camb',
BAO_smearing = False,
cosmology = cc.cosmo()):
# Initialize galaxy parameters
gc.galaxy.__init__(self,
z = z,
k = k,
code = code,
BAO_smearing = BAO_smearing,
cosmology = cosmology)
# Initialize RSD parameters
self.mu = mu
self.k_par = k_par
self.k_perp = k_perp
self.nmu = len(np.atleast_1d(mu))
self.nk_par = len(np.atleast_1d(k_par))
self.nk_perp = len(np.atleast_1d(k_perp))
# Initialize RSD galaxy power spectrum
self.Pk['galaxies']['redshift space'] = {}
def __init__(self,
z,
k,
code='camb',
BAO_smearing=False,
cosmology=cc.cosmo()):
# Reading all cosmological parameters
self.cosmology = cosmology
# Code
self.code = code
# Smear BAO in non-linearities
self.BAO_smearing = BAO_smearing
# Overdensity spherical collapse
self.delta_sc = 3. / 20. * (12. * np.pi)**(2. / 3.)
# Redshift and scales at which all must be computed
self.z = np.atleast_1d(z)
self.k = np.atleast_1d(k)
self.nz = len(self.z)
self.nk = len(self.k)
# Growth factor
self.growth_factor = self.cosmology.growth_factor_scale_independent(
self.z)
# Power spectrum dictionary initialization
self.Pk = {}
self.Pk['matter'] = {}
# Load linear power spectrum
self.load_Pk()
# Initialize mass
self.nm = 512
self.mass = np.logspace(2., 18., self.nm)
# Peak height
self.peak_height = self.nu()
# virial_radii
self.rv = self.R_v(self.mass)
#========================
# Define cosmology instance
# We report as example all cosmological parameters
# but the syntax cc.cosmo() is sufficient to have all
# parameters set to default value.
C = cc.cosmo(
Omega_m=
0.3089, # total matter (CDM + baryons + neutrinos) density parameter today
Omega_b=0.0486, # baryon density parameter today
Omega_K=
0., # Curvature density parameter (Omega_lambda will be set as 1-Omega_K-Omega_m-Omega_b-Omega_gamma
ns=0.9667, # Scalar spectral index of primordial perturbation
As=2.14e-9, # Scalar amplitude of primordial perturbation
sigma_8=None, # Power spectrum normalization (set to None as As is defined)
h=0.6774, # Hubble parameter in units of 100 km/s/Mpc
w0=-1., # Dark energy parameter of state today
wa=0., # Evolution of dark energy parameter of state
tau=0.06, # Optical depth to reionization
T_cmb=2.7255, # CMB temperature today (fixes Omega_gamma)
M_nu=[0.05, 0.01
], # Neutrino masses in eV: in this case we have 2 massive neutrinos
N_nu=3, # Total number of neutrino species
N_eff=3.046
) # Effective number of neutrinos: since 2 are massive, only N_eff - massive_nu will be massless
print("Omega matter: %.4f" % (C.Omega_m))
print("Omega CDM: %.4f" % (C.Omega_cdm))
print("Omega baryons: %.4f" % (C.Omega_b))
print("Omega curvature: %.4f" % (C.Omega_K))
print("Omega Lambda: %.3e" % (C.Omega_lambda))
# Colors for different multipoles
colors = ['b', 'r', 'g', 'y', 'k', 'c']
# Choose RSD model among:
# - 'linear' (use linear power spectrum)
# - 'nonlinear' (use nonlinear power spectrum with Halofit)
# - 'HOD' (use HOD for the real space galaxy power spectrum)
# - 'halo model' (use halo model directly in redshift-space)
RSD_model = 'nonlinear'
#---------------------
#---------------------
# Cosmology instance
#---------------------
C = cc.cosmo()
#---------------------
#---------------------
# RSD instance
#---------------------
Z = rsd.RSD(
z=zz, # Redshift
k=np.geomspace(0.0005, 10., 201), # Scales in h/Mpc
mu=np.linspace(0., 1., 31), # Cosine of angles with LOS
k_par=np.linspace(0.01, 1., 51), # Scales parallel in h/Mpc
k_perp=np.linspace(0.01, 1., 31), # Scales perpendicular in h/Mpc
BAO_smearing=True, # Smooth BAO feature in non-linearities
cosmology=C) # Cosmology
print(">> RSD instance loaded")
#---------------------
# 'mead' (good for neutrinos)
# 'mead2020' (good for neutrinos)
# 'takahashi' (good for neutrinos)
# 'bird' (good for neutrinos)
# 'halomodel' (good for neutrinos)
# 'classichm' (not good for neutrinos)
set_halofit = 'mead2020'
#########################
#=================
# This code computes the non-linear matter power spectrum with different methods
# 1) the Halofit operator defined in CAMB
# 2) the Halofit operator defined in the `nonlinear.py` module
#=================
# Cosmology, redshifts and scales
C = cc.cosmo(Omega_m=0.3089, Omega_b=0.0486, As=2.14e-9, ns=0.9667,
h=0.6774) #,M_nu=0.3,w0=-1.1, wa=-0.3)
zz = np.linspace(0., 5., 6)
kk = np.logspace(-4., 2., 201)
zz = np.atleast_1d(zz)
#=================
# 1) Compute the non-linear power spectrum with CAMB
#=================
if set_halofit != 'classichm':
k_camb, pk_nl_camb = C.camb_Pk(k=kk,
z=zz,
nonlinear=True,
halofit=set_halofit)
else:
import colibri.halo as hc
H = hc.halo(z=zz, k=kk, code='camb', cosmology=C)
import colibri.fourier as FF
import colibri.useful_functions as UF
import matplotlib.pyplot as plt
plt.rc('text', usetex=True)
plt.rc('font', family='serif', size=30)
######################
# Test of FFTlog
######################
# This routine computes the linear power spectrum, inverse Fourier transforms it
# and then goes back to Fourier space to check both the correlation function and
# the goodness of the inversion
# Define cosmology
C = cc.cosmo(M_nu=0.0)
# Compute linear power spectrum with camb
k, pk = C.camb_Pk(z=0, k=np.logspace(-4., 2.5, 1001))
# The power spectrum is a matrix of shape (1,len(k)). Take the first element, i.e. an array of len(k)
pk = pk[0]
# Extrapolate a power law at low- and high-ends
k, pk = UF.extrapolate_log(k, pk, xmin=1e-10, xmax=1e6)
# Compute correlation function through inverse FFT in 3D
r, xi = FF.iFFT_iso_3D(k, pk)
# Go back to Fourier space through FFTlog
k_fft, pk_fft = FF.FFT_iso_3D(r, xi)
# Plot
import matplotlib.pyplot as plt
plt.rc('text', usetex=True)
plt.rc('font', size=25, family='serif')
#===========
# Fixed
#===========
RR = np.geomspace(0.1, 50., 101) # Radii of voids
DNL = -0.8 # Underdensity for voids
IMAX = 200 # Max index of sum (must be >= 200)
#===========
# Cosmology
#===========
C = cc.cosmo(Omega_m=0.26, Omega_b=0.044, ns=0.96, As=2.168e-9, h=0.715)
#===========
# Redshifts and scales
#===========
zz = np.linspace(0., 5., 11)
kk = np.logspace(-4., 2, 1001)
#===========
# Linear power spectra
#===========
_, pk = C.camb_Pk(z=zz, k=kk)
#===========
# VSFs
#===========