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We consider the quantum query complexity of local search as a function of graph geometry. Given a graph $G = (V,E)$ with $n$ vertices and black box access to a function $f : V \to \mathbb{R}$, the goal is find a vertex $v$ that is a local…

Computational Complexity · Computer Science 2024-12-19 Simina Brânzei , Nicholas J. Recker

The approximate degree of a Boolean function $f(x_{1},x_{2},\ldots,x_{n})$ is the minimum degree of a real polynomial that approximates $f$ pointwise within $1/3$. Upper bounds on approximate degree have a variety of applications in…

Computational Complexity · Computer Science 2018-01-16 Alexander A. Sherstov

Given query access to an undirected graph $G$, we consider the problem of computing a $(1\pm\epsilon)$-approximation of the number of $k$-cliques in $G$. The standard query model for general graphs allows for degree queries, neighbor…

Data Structures and Algorithms · Computer Science 2018-11-13 Talya Eden , Dana Ron , C. Seshadhri

Lin and Lin have recently shown how starting with a classical query algorithm (decision tree) for a function, we may find upper bounds on its quantum query complexity. More precisely, they have shown that given a decision tree for a…

Quantum Physics · Physics 2020-03-04 Salman Beigi , Leila Taghavi

We present a quantum algorithm which identifies with certainty a hidden subgroup of an arbitrary finite group G in only a polynomial (in log |G|) number of calls to the oracle. This is exponentially better than the best classical algorithm.…

Quantum Physics · Physics 2016-12-30 Mark Ettinger , Peter Hoyer , Emanuel Knill

We prove a tight quantum query lower bound $\Omega(n^{k/(k+1)})$ for the problem of deciding whether there exist $k$ numbers among $n$ that sum up to a prescribed number, provided that the alphabet size is sufficiently large. This is an…

Quantum Physics · Physics 2012-08-13 Aleksandrs Belovs , Robert Spalek

The divide-and-conquer framework, used extensively in classical algorithm design, recursively breaks a problem of size $n$ into smaller subproblems (say, $a$ copies of size $n/b$ each), along with some auxiliary work of cost…

Quantum Physics · Physics 2025-07-15 Andrew M. Childs , Robin Kothari , Matt Kovacs-Deak , Aarthi Sundaram , Daochen Wang

We consider the quantum complexities of the following three problems: searching an ordered list, sorting an un-ordered list, and deciding whether the numbers in a list are all distinct. Letting N be the number of elements in the input list,…

Quantum Physics · Physics 2016-12-30 Peter Hoyer , Jan Neerbek , Yaoyun Shi

We initiate a systematic study of the time complexity of quantum divide and conquer algorithms for classical problems. We establish generic conditions under which search and minimization problems with classical divide and conquer algorithms…

Quantum Physics · Physics 2025-12-03 Jonathan Allcock , Jinge Bao , Aleksandrs Belovs , Troy Lee , Miklos Santha

Given an integer $k$, deciding whether a graph has a clique of size $k$ is an NP-complete problem. Wilf's inequality provides a spectral bound for the clique number of simple graphs. Wilf's inequality is stated as follows: $\frac{n}{n -…

Discrete Mathematics · Computer Science 2025-04-08 Hareshkumar Jadav , Sreekara Madyastha , Rahul Raut , Ranveer Singh

Let a Boolean function be available as a black-box (oracle) and one likes to devise an algorithm to test whether it has certain property or it is $\epsilon$-far from having that property. The efficiency of the algorithm is judged by the…

Quantum Physics · Physics 2013-06-27 Kaushik Chakraborty , Subhamoy Maitra

The Goldreich-Levin algorithm was originally proposed for a cryptographic purpose and then applied to learning. The algorithm is to find some larger Walsh coefficients of an $n$ variable Boolean function. Roughly speaking, it takes a…

Quantum Physics · Physics 2020-01-03 Hongwei Li

For each $r\ge 4$, we show that any graph $G$ with minimum degree at least $(1-1/100r)|G|$ has a fractional $K_r$-decomposition. This improves the best previous bounds on the minimum degree required to guarantee a fractional…

Combinatorics · Mathematics 2018-09-28 Richard Montgomery

We show that quantum search can be used to compute the hardness to round an elementary function, that is, to determine the minimum working precision required to compute the values of an elementary function correctly rounded to a target…

Quantum Physics · Physics 2026-01-21 Stefanos Kourtis

We study the query complexity of Weak Parity: the problem of computing the parity of an n-bit input string, where one only has to succeed on a 1/2+eps fraction of input strings, but must do so with high probability on those inputs where one…

Computational Complexity · Computer Science 2013-12-03 Scott Aaronson , Andris Ambainis , Kaspars Balodis , Mohammad Bavarian

Motivated by many applications, we study clustering with a faulty oracle. In this problem, there are $n$ items belonging to $k$ unknown clusters, and the algorithm is allowed to ask the oracle whether two items belong to the same cluster or…

Machine Learning · Computer Science 2022-07-13 Jinghui Xia , Zengfeng Huang

We prove that with high probability over the choice of a random graph $G$ from the Erd\H{o}s-R\'enyi distribution $G(n,1/2)$, the $n^{O(d)}$-time degree $d$ Sum-of-Squares semidefinite programming relaxation for the clique problem will give…

Computational Complexity · Computer Science 2016-04-13 Boaz Barak , Samuel B. Hopkins , Jonathan Kelner , Pravesh K. Kothari , Ankur Moitra , Aaron Potechin

In this paper, assuming the low-degree conjecture, we provide evidence of computational hardness for two problems: (1) the (partial) matching recovery problem in the sparse correlated Erd\H{o}s-R\'enyi graphs $\mathcal G(n,q;\rho)$ when the…

Machine Learning · Statistics 2025-12-30 Zhangsong Li

We introduce a framework for proving lower bounds on computational problems over distributions against algorithms that can be implemented using access to a statistical query oracle. For such algorithms, access to the input distribution is…

Computational Complexity · Computer Science 2016-08-16 Vitaly Feldman , Elena Grigorescu , Lev Reyzin , Santosh Vempala , Ying Xiao

We consider functions defined by deep neural networks as definable objects in an o-miminal expansion of the real field, and derive an almost linear (in the number of weights) bound on sample complexity of such networks.

Machine Learning · Computer Science 2019-10-25 Alexander Usvyatsov
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