  Collective synchronization in a large population of self-sustained units
appears both in natural and engineered systems. Sometimes this effect is in
demand, while in some cases, it is undesirable, which calls for control
techniques. In this paper, we concentrate on pulsatile control, with the goal
to either increase or decrease the level of synchrony. We quantify this level
by the entropy of the phase distribution. Motivated by possible applications in
neuroscience, we consider pulses of a realistic shape. Exploiting the noisy
Kuramoto-Winfree model, we search for the optimal pulse profile and the optimal
stimulation phase. For this purpose, we derive an expression for the change of
the phase distribution entropy due to the stimulus. We relate this change to
the properties of individual units characterized by generally different natural
frequencies and phase response curves and the population's state. We verify the
general result by analyzing a two-frequency population model and demonstrating
a good agreement of the theory and numerical simulations.
