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Revision #1 to TR15-196 | 4th December 2015 20:04

Polynomials, Quantum Query Complexity, and Grothendieck's Inequality

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Revision #1
Authors: Scott Aaronson, Andris Ambainis, J?nis Iraids, Martins Kokainis, Juris Smotrovs
Accepted on: 4th December 2015 20:04
Downloads: 453
Keywords: 


Abstract:

We show an equivalence between 1-query quantum algorithms and representations by degree-2 polynomials.
Namely, a partial Boolean function $f$ is computable by a 1-query quantum algorithm with error bounded by $\epsilon<1/2$ iff $f$ can be approximated by a degree-2 polynomial with error bounded by $\epsilon'<1/2$.
This result holds for two different notions of approximation by a polynomial: the standard definition of Nisan and Szegedy and the approximation by block-multilinear polynomials recently introduced by Aaronson and Ambainis (STOC'2015).

We also show two results for polynomials of higher degree. First, there is a total Boolean function which requires $\tilde{\Omega}(n)$ quantum queries but can be represented by a block-multilinear polynomial of degree $\tilde{O}(\sqrt{n})$. Thus, in the general case (for an arbitrary number of queries), block-multilinear polynomials are not equivalent to quantum algorithms.

Second, for any constant degree $k$, the two notions of approximation by a polynomial (the standard and the block-multilinear) are equivalent. As a consequence, we solve an open problem of Aaronson and Ambainis (STOC'2015), showing that one can estimate the value of any bounded degree-$k$ polynomial $p:\{0, 1\}^n \rightarrow [-1, 1]$ with $O(n^{1-\frac{1}{2k}})$ queries.


Paper:

TR15-196 | 4th December 2015 16:31

Polynomials, Quantum Query Complexity, and Grothendieck's Inequality





TR15-196
Authors: Andris Ambainis
Publication: 4th December 2015 16:47
Downloads: 624
Keywords: 


Abstract:

We show an equivalence between 1-query quantum algorithms and representations by degree-2 polynomials.
Namely, a partial Boolean function $f$ is computable by a 1-query quantum algorithm with error bounded by $\epsilon<1/2$ iff $f$ can be approximated by a degree-2 polynomial with error bounded by $\epsilon'<1/2$.
This result holds for two different notions of approximation by a polynomial: the standard definition of Nisan and Szegedy and the approximation by block-multilinear polynomials recently introduced by Aaronson and Ambainis (STOC'2015).

We also show two results for polynomials of higher degree. First, there is a total Boolean function which requires $\tilde{\Omega}(n)$ quantum queries but can be represented by a block-multilinear polynomial of degree $\tilde{O}(\sqrt{n})$. Thus, in the general case (for an arbitrary number of queries), block-multilinear polynomials are not equivalent to quantum algorithms.

Second, for any constant degree $k$, the two notions of approximation by a polynomial (the standard and the block-multilinear) are equivalent. As a consequence, we solve an open problem of Aaronson and Ambainis (STOC'2015), showing that one can estimate the value of any bounded degree-$k$ polynomial $p:\{0, 1\}^n \rightarrow [-1, 1]$ with $O(n^{1-\frac{1}{2k}})$ queries.



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