CHAM: a fast algorithm of modelling non-linear matter power spectrum in
  the sCreened HAlo Model
  We present a fast numerical screened halo model algorithm (CHAM) for modeling
non-linear power spectrum for the alternative models to LCDM. This method has
three obvious advantages. First of all, it is not being restricted to a
specific dark energy/modified gravity model. In principle, all of the screened
scalar-tensor theories can be applied. Second, the least assumptions are made
in the calculation. Hence, the physical picture is very easily understandable.
Third, it is very predictable and does not rely on the calibration from N-body
simulation. As an example, we show the case of Hu-Sawicki f(R) gravity. In this
case, the typical CPU time with the current parallel Python script (8 threads)
is roughly within $10$ minutes. The resulting spectra are in a good agreement
with N-body data within a few percentage accuracy up to k~1 h/Mpc.
