Particle Swarm Optimization uses noisy historical information to select potentially optimal function samples. Though information-theoretic principles suggest that less noise indicates greater certainty, PSO's momentum term is usually both the least informed and the most deterministic. This dichotomy suggests that while momentum has a profound impact on swarm diversity, it would benefit from a more principled approach. We demonstrate that momentum can be made both more effective and better behaved with informed feedback, and that it may even be completely eliminated with proper application of more straightforward and well-behaved diversity injection strategies.