Using primat with CLASS/CAMB tables, and in MCMC chains

Driving primat from a CLASS/CAMB background

primat does not call CLASS or CAMB directly; instead, feed their thermodynamics output through the Custom backgrounds and extra_rho’s custom_background= mechanism. Export (T_γ, t, a) from your CLASS/CAMB run as a tab- or comma-delimited file (columns named T [MeV], t [s], a — scale factor normalised to 1 today) and point custom_background at it:

from primat.backend import run_bbn

result = run_bbn({
    "custom_background": "class_output.tsv",
    "network": "small",
    "Omegabh2": 0.02242,
})

See Custom backgrounds and extra_rho for the exact table format, normalisation convention (a · T_γ → T_0CMB as T_γ → 0), and the caveats around neutrino temperatures (instantaneous-decoupling approximation in this mode).

Using primat in MCMC chains (Cobaya)

For embedding BBN directly in MCMC analyses of CMB or other cosmological data, use the Cobaya wrapper in the separate primat_tools repository (for use with Cobaya). It exposes Omegabh2, DeltaNeff, and the nuclear-rate uncertainty parameters (see Rate variation and Monte-Carlo uncertainty) as Cobaya theory/likelihood inputs, and returns the standard BBN observables (YPBBN, DoH, etc. — see Reading the result dict and time-evolution output) for use in a likelihood.

primat itself has no Cobaya dependency and none is implemented in this package — keep the run_bbn/PRIMAT.solve() result-dict keys stable across releases so the wrapper keeps working (see the primat_tools repo for its own docs and installation instructions).