I have an average orbital light curve for a source, that is, binned count rate vs orbital phase, where the count rate are averaged over a number of orbit.
I want to run MonteCarlo simulations to find the probability of obtaining a "very different" light curve profile (defined by certain criteria) by chance.
The criteria is that at a certain phase, the simulated profile must have a count rate that is less than $30\%$ than the real one.
My approach was to draw $10^5$ (or so) values for each phase bin, giving to the distributions a Poisson statistics.
However, it seems that, over $10^5$ simulations, none of the fake profiles, are significantly different from the average one, that is the condition established in the criteria is never met.
I have absolutely no experience with MonteCarlo simulations, therefore I am afraid I am doing something wrong. It seems to me reasonable that the condition is never met by chance, but I would like to know more on possible sources of error in my reasoning.
Is the mine a good approach? Is it enough to give a Poissonian distribution to the simulated values to ensure statistical variability? Should I increase the number of simulations?
EDIT: a Light curve is the behavior of the light (photon count rate) emitted by a source (e.g., a star) as a function of the time. An orbital light curve, is the same in the case of a binary system, that is the light curve is roughly periodical over the orbital period (in this case, the photon count rate is plotted versus the orbital phase, e.g., $\phi=t/P$, with $t$ time of the observed events and $P$ orbital period of the source). An averaged orbital light curve is an orbital light curve whose photon count rate has been averaged over a number of period. Here is a typical light curve: The profiles are shown two times for clarity, but they are exactly the same.