Modifyng CAMB with Cobaya

[Helena Garcia]

I wanted to run cobaya with EDE modifying the .ini file that the CAMB that cobaya uses reads. How can I make cobaya read a modified .ini file for CAMB?
Thank you!

[Antony Lewis]

You need to pass the relevant parameters via the Cobaya input yaml file.

[Helena Garcia]

That is what I did! I followed the instructions if the documentation. I added the extra parameters of modified CAMB in the theory block and in the params block (I paste the modified part of the .yaml file at the end of this message). But when I run cobaya I get the following error:

cobaya.log.LoggedError: Could not find anything to use input parameter(s) {'extra_param_1', 'extra_param_2'}.

I want to modify the dark energy model, if I was running CAMB I would input a different .ini file (setting dark_energy_model = 'EarlyQuintessence' ), but I don't know how to do this with cobaya. Do you know how can I get cobaya to identify the extra input parameters?

Thank you in advance!

Code: Select all

theory:
  camb:
    extra_args:
     extra_param_1:
     extra_param_2:
params:
   extra_param_1:
    prior:
      min: 0
      max: 1
    ref:
      dist: norm
      loc: 0.5
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{extra_param_1}}'
   extra_param_2:
    prior:
      min: 0
      max: 1
    ref:
      dist: norm
      loc: 0.5
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{extra_param_2}}'

[Antony Lewis]

There's no parameter called "extra_param_1" in the supplied CAMB.

you need to set dark_energy_model in the extra_args input, and use the actual parameter names when sampling (not in extra_args).

[Helena Garcia]

Thank you so much! I got it running now, but I still have an issue when using the minimizer. I get this error

calc_zc_fde: NO PEAK
[0 : minimize] *ERROR* Cannot reproduce log minimum to within 0.01. Maybe your likelihood is stochastic or large numerical error? Recomputed min: -inf (was -1.79769e+308) at array([3.05057809e+00, 9.69716464e-01, 1.04123281e+00, 2.22220221e-02,..])

Do you know what can be wrong?

Here is my .yaml file

Code: Select all

theory:
  camb:
    extra_args:
      halofit_version: mead
      bbn_predictor: PArthENoPE_880.2_standard.dat
      lens_potential_accuracy: 1
      num_massive_neutrinos: 1
      nnu: 3.046
      theta_H0_range:
      - 20
      - 100
      dark_energy_model: EarlyQuintessence 
      n: 3
likelihood:
  planck_2018_lowl.TT: null
  planck_2018_lowl.EE: null
  planck_2018_highl_plik.TTTEEE: null
  bao.sdss_dr16_baoplus_lrg: null
  bao.sdss_dr16_baoplus_lyauto: null
  bao.sdss_dr16_baoplus_lyxqso: null
  bao.sdss_dr16_baoplus_qso: null
params:
  logA:
    prior:
      min: 1.61
      max: 3.91
    ref:
      dist: norm
      loc: 3.05
      scale: 0.001
    proposal: 0.001
    latex: \log(10^{10} A_\mathrm{s})
    drop: true
  As:
    value: 'lambda logA: 1e-10*np.exp(logA)'
    latex: A_\mathrm{s}
  ns:
    prior:
      min: 0.8
      max: 1.2
    ref:
      dist: norm
      loc: 0.965
      scale: 0.004
    proposal: 0.002
    latex: n_\mathrm{s}
  theta_MC_100:
    prior:
      min: 0.5
      max: 10
    ref:
      dist: norm
      loc: 1.04109
      scale: 0.0004
    proposal: 0.0002
    latex: 100\theta_\mathrm{MC}
    drop: true
    renames: theta
  cosmomc_theta:
    value: 'lambda theta_MC_100: 1.e-2*theta_MC_100'
    derived: false
  H0:
    latex: H_0
    min: 20
    max: 100
  ombh2:
    prior:
      min: 0.005
      max: 0.1
    ref:
      dist: norm
      loc: 0.0224
      scale: 0.0001
    proposal: 0.0001
    latex: \Omega_\mathrm{b} h^2
  omch2:
    prior:
      min: 0.001
      max: 0.99
    ref:
      dist: norm
      loc: 0.12
      scale: 0.001
    proposal: 0.0005
    latex: \Omega_\mathrm{c} h^2
  omegam:
    latex: \Omega_\mathrm{m}
  omegamh2:
    derived: 'lambda omegam, H0: omegam*(H0/100)**2'
    latex: \Omega_\mathrm{m} h^2
  mnu: 0.06
  YHe:
    latex: Y_\mathrm{P}
  Y_p:
    latex: Y_P^\mathrm{BBN}
  DHBBN:
    derived: 'lambda DH: 10**5*DH'
    latex: 10^5 \mathrm{D}/\mathrm{H}
  tau:
    prior:
      min: 0.01
      max: 0.8
    ref:
      dist: norm
      loc: 0.055
      scale: 0.006
    proposal: 0.003
    latex: \tau_\mathrm{reio}
  zre:
    latex: z_\mathrm{re}
  sigma8:
    latex: \sigma_8
  s8h5:
    derived: 'lambda sigma8, H0: sigma8*(H0*1e-2)**(-0.5)'
    latex: \sigma_8/h^{0.5}
  s8omegamp5:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.5'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.5}
  s8omegamp25:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.25'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.25}
  A:
    derived: 'lambda As: 1e9*As'
    latex: 10^9 A_\mathrm{s}
  clamp:
    derived: 'lambda As, tau: 1e9*As*np.exp(-2*tau)'
    latex: 10^9 A_\mathrm{s} e^{-2\tau}
  age:
    latex: '{\rm{Age}}/\mathrm{Gyr}'
  rdrag:
    latex: r_\mathrm{drag}
  fde_zc:
    prior:
      min: 0
      max: 0.5
    ref:
      dist: norm
      loc: 0.1
      scale: 0.01
    proposal: 0.005
    latex: '{\rm{fde_zc}}'
  zc:
    prior:
      min: 0
      max: 100000
    ref:
      dist: norm
      loc: 10000
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{criticalz}}'
sampler:
  minimize:
    method: bobyqa
    ignore_prior: False
    max_evals: 1e6d
    best_of: 2
    confidence_for_unbounded: 0.9999995 
output: /volumes/data2/cobaya/
debug: true