- a repeated event when aggregated (like summed or averaged) tends to look more and more like a normal distribution the more samples you got - the standard dev

- a repeated event when aggregated (like summed or averaged) tends to look more and more like a normal distribution the more samples you got - the standard deviation of a normal distribution scales roughly by the square root of the number of samples - From microseconds to nanoseconds you need a 1000x in precision, 1000² = 1.000.000. So from an event that has a noise amplitude of microseconds, I think you may be able to measure a difference of nanoseconds with ~1 million samples. --- So yeah unlikely in normal scenarios. But if you could, for example, rent a server in 10km from your target, you can reduce by 10-100x the latency, which will reduce your number of samples by its square, so a 100x-10000x reduction And what if it's possible to rent a server in the same datacenter of your target? ... well K.O.