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bawolff • today at 12:50 AM • 1 reply • view on HN

O(n lg n) is a bit of a threshold value. For a lot of algorithms, this is the best you can do, even in theory (similar to how O(n^2) is also a threshold for many algorithms). So for many algorithms, people stop trying when they get close to O(n lg n) on the belief that you'll never do better than that.

The fact that you can in principle go faster than n lg n, even if just by an almost imperceptible amount, is kind of surprising. It raises the question of, if n lg n isn't the limit, what is? How far down can we get the speed? If we can get it a little past n lg n, maybe we can go a lot further.

[or at least that is my understanding. not a theoretical computer scientist]


Replies

ack_complete • today at 4:52 AM

It's potentially very interesting because there are a number of critical algorithms that are all related and share asymptotic lower bounds as a result. My first thought on seeing this was whether a proven result here would also open the door for FFTs to go below O(n log n).

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