  We present a comparison of two methods of fitting solar-like variability to
increase the efficiency of detection of Earth-like planetary transits across
the disk of a Sun-like star. One of them is the harmonic fitting method that
coupled with the BLS detection algorithm demonstrated the best performance
during the first CoRoT blind test. We apply a Monte Carlo approach by
simulating a large number of light curves of duration 150 days for different
values of planetary radius, orbital period, epoch of the first transit, and
standard deviation of the photon shot noise. Stellar variability is assumed in
all the cases to be given by the Total Solar Irradiance variations as observed
close to the maximum of solar cycle 23. After fitting solar variability,
transits are searched for by means of the BLS algorithm. We find that a model
based on three point-like active regions is better suited than a best fit with
a linear combination of 200 harmonic functions to reduce the impact of stellar
microvariability provided that the standard deviation of the noise is 2-4 times
larger than the central depth of the transits. On the other hand, the
200-harmonic fit is better when the standard deviation of the noise is
comparable to the transit depth. Our results show the advantage of a model
including a simple but physically motivated treatment of stellar
microvariability for the detection of planetary transits when the standard
deviation of the photon shot noise is greater than the transit depth and
stellar variability is analogous to solar irradiance variations.
