Very Massive Tracers and Higher Derivative Biases
  Most of the upcoming cosmological information will come from analyzing the
clustering of the Large Scale Structures (LSS) of the universe through LSS or
CMB observations. It is therefore essential to be able to understand their
behavior with exquisite precision. The Effective Field Theory of Large Scale
Structures (EFTofLSS) provides a consistent framework to make predictions for
LSS observables in the mildly non-linear regime. In this paper we focus on
biased tracers. We argue that in calculations at a given order in the dark
matter perturbations, highly biased tracers will underperform because of their
larger higher derivative biases. A natural prediction of the EFTofLSS is
therefore that by simply adding higher derivative biases, all tracers should
perform comparably well. We implement this prediction for the halo-halo and the
halo-matter power spectra at one loop, and the halo-halo-halo,
halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare
with simulations. We find good agreement with the prediction: for all tracers,
we are able to match the bispectra up to $k\simeq0.17\,h/$Mpc at $z=0$ and the
power spectra to a higher wavenumber.
