clxg for lcdm
-
- Posts: 10
- Joined: February 15 2014
- Affiliation: Cinvestav
clxg for lcdm
Hi everyone,
I have a question about clxg (photons) perturbations. I was comparing the CAMB outcome using w=-1 (labeled 'clxg_lcdm ') and w=-0.99999999999 (labeled 'clxg_lcdm_false'). Of course, I was expecting the spectra to be indistinguishable and they are. However, checking the clxg as function of the scale factor (a), I have found the difference shown in the figure.
clxg_a_lcdm.png
What may be the reason for this difference? And, Why it takes place at this particular value of a?
I have a question about clxg (photons) perturbations. I was comparing the CAMB outcome using w=-1 (labeled 'clxg_lcdm ') and w=-0.99999999999 (labeled 'clxg_lcdm_false'). Of course, I was expecting the spectra to be indistinguishable and they are. However, checking the clxg as function of the scale factor (a), I have found the difference shown in the figure.
clxg_a_lcdm.png
What may be the reason for this difference? And, Why it takes place at this particular value of a?
-
- Posts: 1945
- Joined: September 23 2004
- Affiliation: University of Sussex
- Contact:
Re: clxg for lcdm
Is this using equations.f90 or equations_ppf.f90?
-
- Posts: 10
- Joined: February 15 2014
- Affiliation: Cinvestav
clxg for lcdm
It's using 'equations.f90' and 'fixq = 1._dl'.
-
- Posts: 1945
- Joined: September 23 2004
- Affiliation: University of Sussex
- Contact:
Re: clxg for lcdm
I think you are probably plotting different things here. With do_late_rad_truncation = T, the photon perturbations are not calculated at late time, so the array element you are outputting will be something else (dark energy perturbation or something else, depending on whether w=-1 and hence whether there are any dark energy perturbations).
The best way to plot parameter evolution is to use the python wrapper
The best way to plot parameter evolution is to use the python wrapper
Code: Select all
from matplotlib import pyplot as plt
import camb
import numpy as np
pars = camb.set_params(H0=67.5, ombh2=0.022, omch2=0.122, As=2e-9, ns=0.95)
data= camb.get_background(pars)
a=10**(np.linspace(-8, 0, 500))
z = 1/a -1
eta = data.conformal_time(z)
ev = data.get_time_evolution(1., eta, ['delta_photon'])
plt.loglog(a, np.abs(ev))
-
- Posts: 10
- Joined: February 15 2014
- Affiliation: Cinvestav
clxg for lcdm
thank you, Antony. Now it calculates the photon perturbations at late time.