by D. Huterer and H.V. Peiris ( Phys. Rev. D

Below we provide Markov Chains with scalar field model parameters.

For each class of models and (current or future) cosmological data, there are are four chains (in four files) contained in a .tar.gz tarball. For each class, there are additional four files that contain the w(z) history for each model. The classes of models we have assumed are 2 and 3-parameter V(&phi) models with either current or future data.

** 2 parameter V(&phi), current data (75 Mb file):
**

Columns are, for the 2-V(&phi)-parameter case (these parameters,
for each model, are written in a single row)

weight, -ln(Likelihood)

&epsilon(3), &eta(3), &Omega_{DE}(3), w(3),
&theta_{A}, &Omega_{b}h^{2},

&epsilon(0), &eta(0), &Omega_{DE}(0), w(0),
&theta_{A}, &Omega_{b}h^{2},

&alpha_{1}, &alpha_{2}, &alpha_{3},

w_{0}, w_{a}

where the parentheses show whether the parameter was
evaluated at z=3 (our starting redshift) or z=0. Here &epsilon and
&eta are the two "slow-roll" parameters (note they are not necessarily
small for DE), and &Omega_{DE}, and w are energy density and
equation of state of DE. Further,
&theta_{A} and &Omega_{b}h^{2} are the CMB angle
subtended by the first peak (in degrees) and baryon fraction
respectively; note they are repeated twice in the files. Finally,
&alpha_{i} (i=1, 2, 3) are the first three principal
components of the equation of state, while w_{0} and
w_{a} are derived from the PCs as described in the paper.

For the 3-V(&phi)-parameter case there is one extra parameter, the
third "slow-roll" parameter &xi and the format is now

weight, -ln(Likelihood)

&epsilon(3), &eta(3), &Omega_{DE}(3), w(3),
&theta_{A}, &Omega_{b}h^{2} &xi(3),

&epsilon(0), &eta(0), &Omega_{DE}(0), w(0),
&theta_{A}, &Omega_{b}h^{2} &xi(0),

&alpha_{1}, &alpha_{2}, &alpha_{3},

w_{0}, w_{a}

Finally, for the "_wz" files the format is

weight, -ln(Likelihood), w(0.0), w(0.2),... w(3.0)

where w(z) refers to value of the equation of state at redshift z in
each model.

While we give the likelihood of individual models for reference, the posterior must be calculated using the weights of the models which are proportional to the PDF (Bayes Theorem). Our chains are fully compatible with the GetDist parameter estimation package, supplied as part of cosmomc, with minor modifications to the parameter file to change the variable names to those that we use.

Dragan Huterer