  We use the first release of the VImos Public Extragalactic Redshift Survey of
galaxies (VIPERS) of ~50,000 objects to measure the biasing relation between
galaxies and mass in the redshift range z=[0.5,1.1]. We estimate the 1-point
distribution function [PDF] of VIPERS galaxies from counts in cells and,
assuming a model for the mass PDF, we infer their mean bias relation. The
reconstruction of the bias relation from PDFs is performed through a novel
method that accounts for Poisson noise, redshift distortions, inhomogeneous sky
coverage and other selection effects. With this procedure we constrain galaxy
bias and its deviations from linearity down to scales as small as 4 Mpc/h and
out to z=1.1. We detect small (~3%) but significant deviations from linear
bias. The mean biasing function is close to linear in regions above the mean
density. The mean slope of the biasing relation is a proxy to the linear bias
parameter. It increases both with luminosity, in agreement with results of
previous analyses, and with redshift. However, we detect a strong bias
evolution only for z>0.9 in agreement with some, but not all, previous studies.
We also detected a significant increase of the bias with the scale, from 4 to 8
Mpc/h, now seen for the first time out to z=1. The amplitude of nonlinearity
depends on redshift, luminosity and on scales but no clear trend is detected.
Thanks to the large cosmic volume probed by VIPERS we find that the mismatch
between the previous estimates of bias at z~1 from zCOSMOS and VVDS-Deep galaxy
samples is fully accounted for by cosmic variance. The results of our work
confirm the importance of going beyond the over-simplistic linear bias
hypothesis showing that non-linearities can be accurately measured through the
applications of the appropriate statistical tools to existing datasets like
VIPERS.
