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We prove the following conjecture, raised by Aaronson and Ambainis in 2008: Let $f:\{-1,1\}^n \rightarrow [-1,1]$ be a multilinear polynomial of degree $d$. Then there exists a variable $x_i$ whose influence on $f$ is at least…

Computational Complexity · Computer Science 2019-12-03 Nathan Keller , Ohad Klein

How many quantum queries are required to determine the coefficients of a degree-$d$ polynomial in $n$ variables? We present and analyze quantum algorithms for this multivariate polynomial interpolation problem over the fields…

Quantum Physics · Physics 2018-01-22 Jianxin Chen , Andrew M. Childs , Shih-Han Hung

Simon's problem plays an important role in the history of quantum algorithms, as it inspired Shor to discover the celebrated quantum algorithm solving integer factorization in polynomial time. Besides, the quantum algorithm for Simon's…

Computational Complexity · Computer Science 2021-09-07 Zekun Ye , Yunqi Huang , Lvzhou Li , Yuyi Wang

We study quantum mechanics in the stochastic formulation, using the functional integral approach. The noise term enters the classical action as a local contribution of anticommuting fields. The partition function is not invariant under…

High Energy Physics - Lattice · Physics 2013-11-15 S. Nicolis

In the $k$-junta testing problem, a tester has to efficiently decide whether a given function $f:\{0,1\}^n\rightarrow \{0,1\}$ is a $k$-junta (i.e., depends on at most $k$ of its input bits) or is $\epsilon$-far from any $k$-junta. Our main…

Computational Complexity · Computer Science 2015-07-15 Andris Ambainis , Aleksandrs Belovs , Oded Regev , Ronald de Wolf

The main reason for query model's prominence in complexity theory and quantum computing is the presence of concrete lower bounding techniques: polynomial and adversary method. There have been considerable efforts to give lower bounds using…

Quantum Physics · Physics 2024-02-20 Rajat Mittal , Sanjay S Nair , Sunayana Patro

This paper considers the projection-free sparse convex optimization problem for the vector domain and the matrix domain, which covers a large number of important applications in machine learning and data science. For the vector domain…

Quantum Physics · Physics 2025-07-14 Jianhao He , John C. S. Lui

In this paper, we consider a quantum algorithm for solving the following problem: ``Suppose $f$ is a function given as a black box (that is also called an oracle) and $f$ is invariant under some AND-mask. Examine a property of $f$ by…

Quantum Physics · Physics 2007-05-23 Hiroo Azuma

We study the quantum query complexity of the Boolean hidden shift problem. Given oracle access to f(x+s) for a known Boolean function f, the task is to determine the n-bit string s. The quantum query complexity of this problem depends…

Quantum Physics · Physics 2013-11-28 Andrew M. Childs , Robin Kothari , Maris Ozols , Martin Roetteler

We study the query complexity of min-max optimization of a nonconvex-nonconcave function $f$ over $[0,1]^d \times [0,1]^d$. We show that, given oracle access to $f$ and to its gradient $\nabla f$, any algorithm that finds an…

Data Structures and Algorithms · Computer Science 2026-05-14 Martino Bernasconi , Matteo Castiglioni , Andrea Celli , Alexandros Hollender

This paper considers the query complexity of the functions in the family F_{N,M} of N-variable Boolean functions with onset size M, i.e., the number of inputs for which the function value is 1, where 1<= M <= 2^{N}/2 is assumed without loss…

The accuracies of modern quantum logic clocks have surpassed those of standard atomic fountain clocks. These clocks also provide a greater degree of control, because before and after clock queries, we are able to apply chosen unitary…

Quantum Physics · Physics 2011-07-28 Michael Mullan , Emanuel Knill

We discuss classical and quantum algorithms for solvability testing and finding integer solutions x,y of equations of the form af^x + bg^y = c over finite fields GF(q). A quantum algorithm with time complexity q^(3/8) (log q)^O(1) is…

Quantum Physics · Physics 2008-04-08 Wim van Dam , Igor E. Shparlinski

We study quantum algorithms that learn properties of a matrix using queries that return its action on an input vector. We show that for various problems, including computing the trace, determinant, or rank of a matrix or solving a linear…

Quantum Physics · Physics 2021-10-19 Andrew M. Childs , Shih-Han Hung , Tongyang Li

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

Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem,…

Quantum Physics · Physics 2023-08-09 Xiaosi Xu , Ying Li

Given a classical query algorithm as a decision tree, when does there exist a quantum query algorithm with a speed-up over the classical one? We provide a general construction based on the structure of the underlying decision tree, and…

Quantum Physics · Physics 2025-06-25 Arjan Cornelissen , Nikhil S. Mande , Subhasree Patro

Classically, determining the gradient of a black-box function f:R^p->R requires p+1 evaluations. Using the quantum Fourier transform, two evaluations suffice. This is based on the approximate local periodicity of exp(2*pi*i*f(x)). It is…

Quantum Physics · Physics 2007-05-23 David Bulger

Motivated by notions of quantum heuristics and by average-case rather than worst-case algorithmic analysis, we define quantum computational advantage in terms of individual problem instances. Inspired by the classical notions of Kolmogorov…

Quantum Physics · Physics 2025-10-03 Harry Buhrman , Niklas Galke , Konstantinos Meichanetzidis

Matrix scaling and matrix balancing are two basic linear-algebraic problems with a wide variety of applications, such as approximating the permanent, and pre-conditioning linear systems to make them more numerically stable. We study the…