Scott Aaronson

A long-standing open problem in quantum complexity theory is whether QMA has perfect completeness, i.e. whether any QMA verifier can be made to have completeness $c=1$. Previous constructions have yielded a completeness parameter exponentially close to 1. We improve this to doubly-exponentially close to 1. Additionally, we show that QMA has perfect completeness if one allows the verifier an infinite-dimensional (witness) space. We show that this can be achieved using a gate set which is such that the ability to use an infinite-dimensional space does not increase the computational power of QMA. We also show that when using a finite-dimensional space of polynomially many qubits, a completeness doubly-exponentially close to 1 is optimal among black-box constructions. We show that the soundness can at most be made exponentially small using black-box reductions.

Abstract Based on the recent breakthrough of Huang (2019), we show that for any total Boolean function f, deg(f) = O(~deg(f)^2): The degree of f is at most quadratic in the approximate degree of f. This is optimal as witnessed by the OR function. D(f) = O(Q(f)^4): The deterministic query complexity of f is at most quartic in the quantum query complexity of f. This matches the known separation (up to log factors) due to Ambainis, Balodis, Belovs, Lee, Santha, and Smotrovs (2017). We apply these results to resolve the quantum analogue of the Aanderaa--Karp--Rosenberg conjecture. We show that if f is a nontrivial monotone graph property of an n-vertex graph specified by its adjacency matrix, then Q(f)=Omega(n), which is also optimal. We also show that the approximate degree of any read-once formula on n variables is Theta(sqrt{n}).

The closest pair problem is a fundamental problem of computational geometry: given a set of $n$ points in a $d$-dimensional space, find a pair with the smallest distance. A classical algorithm taught in introductory courses solves this problem in $O(n\log n)$ time in constant dimensions (i.e., when $d=O(1)$). This paper asks and answers the question of the problem’s quantum {time} complexity. Specifically, we give an $\tilde{O}(n^{2/3})$ algorithm in constant dimensions, which is optimal up to a polylogarithmic factor by the lower bound on the quantum query complexity of element distinctness. The key to our algorithm is an efficient history-independent data structure that supports quantum interference. In $\text{polylog}(n)$ dimensions, no known quantum algorithms perform better than brute force search, with a quadratic speedup provided by Grover’s algorithm. To give evidence that the quadratic speedup is nearly optimal, we initiate the study of quantum fine-grained complexity and introduce the \emph{Quantum Strong Exponential Time Hypothesis (QSETH)}, which is based on the assumption that Grover’s algorithm is optimal for \textsf{CNF-SAT} when the clause width is large. We show that the na\”{i}ve Grover approach to closest pair in higher dimensions is optimal up to an $n^{o(1)}$ factor unless QSETH is false. We also study the bichromatic closest pair problem and the orthogonal vectors problem, with broadly similar results.

Several researchers, including Leonid Levin, Gerard 't Hooft, and Stephen Wolfram, have argued that quantum mechanics will break down before the factoring of large numbers becomes possible. If this is true, then there should be a natural "Sure/Shor separator" -- that is, a set of quantum states that can account for all experiments performed to date, but not for Shor's factoring algorithm. We propose as a candidate the set of states expressible by a polynomial number of additions and tensor products. Using a recent lower bound on multilinear formula size due to Raz, we then show that states arising in quantum error-correction require n^{Omega(log n)} additions and tensor products even to approximate, which incidentally yields the first superpolynomial gap between general and multilinear formula size of functions. More broadly, we introduce a complexity classification of pure quantum states, and prove many basic facts about this classification. Our goal is to refine vague ideas about a breakdown of quantum mechanics into specific hypotheses that might be experimentally testable in the near future. "Bonus features" will be included for those who have already heard this talk.

We present a complete classification of all possible sets of classical reversible gates acting on bits, in terms of which reversible transformations they generate, assuming swaps and ancilla bits are available for free. Our classification can be seen as the reversible-computing analogue of Post’s lattice, a central result in mathematical logic from the 1940s. It is a step toward the ambitious goal of classifying all possible quantum gate sets acting on qubits. In fact, in the quantum setting, the affine classical gates appear as stabilizer gates, and we extend our classification of affine classical gates to give a complete classification of the stabilizer gates. Our theorem implies a linear-time algorithm, that takes as input the truth tables of reversible gates G and H and decides whether G generates H. Previously, this problem was not even known to be decidable. The theorem also implies that any n-bit reversible circuit can be “compressed” to an equivalent circuit, over the same gates, that uses at most 2^n poly(n) gates and O(1) ancilla bits; these are the first upper bounds on these quantities known, and are close to optimal. Finally, the theorem implies that every non-degenerate reversible gate can implement either every reversible transformation, or every affine transformation, when restricted to an “encoded subspace.” Briefly, the theorem says that every set of reversible gates generates either all reversible transformations on n-bit strings; no transformations; all transformations that preserve Hamming weight; all transformations that preserve Hamming weight mod k for some k; all affine transformations; all affine transformations that preserve Hamming weight mod 2 or mod 4, inner products mod 2, or a combination thereof; or a previous class augmented by a NOT or NOTNOT gate. Prior to this work, it was not even known that every class was finitely generated.

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 $\epsilon\lt1/2$ iff $f$ can be approximated by a degree-2 polynomial with error bounded by $\epsilon'\lt1/2$. This result holds for two different notions of approximation by a polynomial: the standard definition of Nisan and Szegedy \cite{NS} and the approximation by block-multilinear polynomials recently introduced by Aaronson and Ambainis \cite{AA}.