Pseudorandom generators for polynomials

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In theoretical computer science, a pseudorandom generator for low-degree polynomials is an efficient procedure that maps a short truly random seed to a longer pseudorandom string in such a way that low-degree polynomials cannot distinguish the output distribution of the generator from the truly random distribution. That is, evaluating any low-degree polynomial at a point determined by the pseudorandom string is statistically close to evaluating the same polynomial at a point that is chosen uniformly at random.

Pseudorandom generators for low-degree polynomials are a particular instance of pseudorandom generators for statistical tests, where the statistical tests considered are evaluations of low-degree polynomials.


A pseudorandom generator for polynomials of degree over a finite field is an efficient procedure that maps a sequence of field elements to a sequence of field elements such that any -variate polynomial over of degree is fooled by the output distribution of . In other words, for every such polynomial , the statistical distance between the distributions and is at most a small , where is the uniform distribution over .


The case corresponds to pseudorandom generators for linear functions and is solved by small-bias generators. For example, the construction of Naor & Naor (1990) achieves a seed length of , which is optimal up to constant factors.

Bogdanov & Viola (2007) conjectured that the sum of small-bias generators fools low-degree polynomials and were able to prove this under the Gowers inverse conjecture. Lovett (2009) proved unconditionally that the sum of small-bias spaces fools polynomials of degree . Viola (2008) proves that, in fact, taking the sum of only small-bias generators is sufficient to fool polynomials of degree . The analysis of Viola (2008) gives a seed length of .