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An open problem that is widely regarded as one of the most important in quantum query complexity is to resolve the quantum query complexity of the k-distinctness function on inputs of size N. While the case of k=2 (also called Element…

Quantum Physics · Physics 2023-03-15 Nikhil S. Mande , Justin Thaler , Shuchen Zhu

We present several results on the complexity of various forms of Sperner's Lemma in the black-box model of computing. We give a deterministic algorithm for Sperner problems over pseudo-manifolds of arbitrary dimension. The query complexity…

Quantum Physics · Physics 2007-05-23 Katalin Friedl , Gabor Ivanyos , Miklos Santha , Yves F. Verhoeven

Solving systems of m multivariate quadratic equations in n variables (MQ-problem) over finite fields is NP-hard. The security of many cryptographic systems is based on this problem. Up to now, the best algorithm for solving the underdefined…

Cryptography and Security · Computer Science 2015-07-15 Heliang Huang , Wansu Bao

In this paper, we introduce the hybrid query complexity, denoted as $\mathrm{Q}(f;q)$, which is the minimal query number needed to compute $f$, when a classical decision tree is allowed to call $q'$-query quantum subroutines for any $q'\leq…

Computational Complexity · Computer Science 2019-12-02 Xiaoming Sun , Yufan Zheng

We consider the number of quantum queries required to determine the coefficients of a degree-d polynomial over GF(q). A lower bound shown independently by Kane and Kutin and by Meyer and Pommersheim shows that d/2+1/2 quantum queries are…

Quantum Physics · Physics 2016-09-08 Andrew M. Childs , Wim van Dam , Shih-Han Hung , Igor E. Shparlinski

Local search is a powerful heuristic in optimization and computer science, the complexity of which was studied in the white box and black box models. In the black box model, we are given a graph $G = (V,E)$ and oracle access to a function…

Computational Complexity · Computer Science 2023-08-16 Simina Brânzei , Davin Choo , Nicholas Recker

We show that the `optimal' use of the parallel composition theorem corresponds to finding the size of the largest subset of queries that `overlap' on the data domain, a quantity we call the \emph{maximum overlap} of the queries. It has…

Cryptography and Security · Computer Science 2021-09-21 Josh Smith , Hassan Jameel Asghar , Gianpaolo Gioiosa , Sirine Mrabet , Serge Gaspers , Paul Tyler

In this article we give several new results on the complexity of algorithms that learn Boolean functions from quantum queries and quantum examples. Hunziker et al. conjectured that for any class C of Boolean functions, the number of quantum…

Quantum Physics · Physics 2007-05-23 Alp Atici , Rocco A. Servedio

The set equality problem is to decide whether two sets $A$ and $B$ are equal or disjoint, under the promise that one of these is the case. Some other problems, like the Graph Isomorphism problem, is solvable by reduction to the set quality…

Quantum Physics · Physics 2007-05-23 Gatis Midrijanis

We study the sample complexity of differentially private optimization of quasi-concave functions. For a fixed input domain $\mathcal{X}$, Cohen et al. (STOC 2023) proved that any generic private optimizer for low sensitive quasi-concave…

Cryptography and Security · Computer Science 2025-04-29 Kobbi Nissim , Eliad Tsfadia , Chao Yan

A fundamental problem in computer science is to find all the common zeroes of $m$ quadratic polynomials in $n$ unknowns over $\mathbb{F}_2$. The cryptanalysis of several modern ciphers reduces to this problem. Up to now, the best complexity…

Symbolic Computation · Computer Science 2015-03-19 Magali Bardet , Jean-Charles Faugère , Bruno Salvy , Pierre-Jean Spaenlehauer

We propose a new method for proving lower bounds on quantum query algorithms. Instead of a classical adversary that runs the algorithm with one input and then modifies the input, we use a quantum adversary that runs the algorithm with a…

Quantum Physics · Physics 2007-05-23 Andris Ambainis

Symmetry underlies many of the most effective classical and quantum learning algorithms, yet whether quantum learners can gain a fundamental advantage under symmetry-imposed structures remains an open question. Based on evidence that…

Quantum Physics · Physics 2026-02-04 Tuyen Nguyen , Mária Kieferová , Amira Abbas

Quantum error correction and symmetry arise in many areas of physics, including many-body systems, metrology in the presence of noise, fault-tolerant computation, and holographic quantum gravity. Here we study the compatibility of these two…

Quantum linear system (QLS) solvers are a fundamental class of quantum algorithms used in many potential quantum computing applications, including machine learning and solving differential equations. The performance of quantum algorithms is…

Quantum Physics · Physics 2026-01-26 Hitomi Mori , Yuta Kikuchi , Marcello Benedetti , Matthias Rosenkranz

The complex systems with edge computing require a huge amount of multi-feature data to extract appropriate insights for their decision making, so it is important to find a feasible feature selection method to improve the computational…

Machine Learning · Computer Science 2024-05-14 Wenjie Liu , Junxiu Chen , Yuxiang Wang , Peipei Gao , Zhibin Lei , Xu Ma

The textbook adversary bound for function evaluation states that to evaluate a function $f\colon D\to C$ with success probability $\frac{1}{2}+\delta$ in the quantum query model, one needs at least $\left( 2\delta -\sqrt{1-4\delta^2}…

Quantum Physics · Physics 2023-03-21 Duyal Yolcu

Low-rank approximation of kernels is a fundamental mathematical problem with widespread algorithmic applications. Often the kernel is restricted to an algebraic variety, e.g., in problems involving sparse or low-rank data. We show that…

Machine Learning · Computer Science 2023-10-02 Jason M. Altschuler , Pablo A. Parrilo

We show that any quantum algorithm deciding whether an input function $f$ from $[n]$ to $[n]$ is 2-to-1 or almost 2-to-1 requires $\Theta(n)$ queries to $f$. The same lower bound holds for determining whether or not a function $f$ from…

Computational Complexity · Computer Science 2012-02-01 Paul Beame , Widad Machmouchi

The problem of minimizing the maximum of $N$ convex, Lipschitz functions plays significant roles in optimization and machine learning. It has a series of results, with the most recent one requiring $O(N\epsilon^{-2/3} + \epsilon^{-8/3})$…

Quantum Physics · Physics 2024-02-21 Hao Wang , Chenyi Zhang , Tongyang Li