In this next instalment, our characters discuss the norm you get by looking for the best possible correlation with a quadratic phase function. They end up discussing a heuristic argument that might, just conceivably, show that this norm is one of a wide class of norms that cannot possibly give rise to superlinear lower bounds. Along the way they have several thoughts, some of which are quite interesting, some not interesting at all, and some plain wrong. (The more interesting ones are mostly later on in the instalment.)

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๐ Last time we met, I came to the understanding that if you build a norm by means of a formula of the form then there are two properties that might have that will give the norm an outside chance of being a useful quasirandomness norm for proving nontrivial lower bounds. The first is that the cardinality of should be superpolynomial in (or else there is a trivial polynomial-time algorithm for working out the norm). The second, which implies the first, but which I prefer to think of as a separate property, is there should not be some clever polynomial-time way of working out the norm—which, when has superexponential size would require one to exploit special properties of the particular set of functions.

As I see it, if you take to be the set of all quadratic phase functions, then you get a set that definitely has the first property and could well have the second. So I want to go back to thinking about this quadratic-correlation norm. Earlier I convinced myself that a random low-complexity function should not correlate with any quadratic phase function. But if for any fixed quadratic phase function I can get only an exponentially small probability of a huge correlation, and if there are superexponentially many quadratic phase functions, then perhaps we need to revisit this statement. Is it conceivable that every function of linear circuit complexity correlates quite heavily with a quadratic phase function? (more…)