Back in the saddle: large deviation statistics of the cosmic log density field
We present a first principle approach to obtain analytical predictions for spherically averaged cosmic densities in the mildly non linear regime that go well beyond what is usually achieved by standard perturbation theory. A large deviation principle allows us to compute the leading order cumulants of average densities in concentric cells. In this symmetry, the spherical collapse model leads to cumulant generating functions that are robust for finite variances and free of critical points when logarithmic density transformations are implemented. They yield in turn accurate density probability distribution functions (PDFs) from a straightforward saddle point approximation valid for all density values. Based on this easy to implement modification, explicit analytic formulas for the evaluation of the one and two cell PDF are provided. The theoretical predictions obtained for the PDFs are accurate to a few percent compared to the numerical integration, regardless of the density under consideration and in excellent agreement with N body simulations for a wide range of densities. This formalism should prove valuable for accurately probing the quasi linear scales of low redshift surveys for arbitrary primordial power spectra.