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In this paper, we study the static cell probe complexity of non-adaptive data structures that maintain a subset of $n$ points from a universe consisting of $m=n^{1+\Omega(1)}$ points. A data structure is defined to be non-adaptive when the…

Data Structures and Algorithms · Computer Science 2024-04-19 Giuseppe Persiano , Kevin Yeo

We prove tight lower bounds for the following variant of the counting problem considered by Aaronson, Kothari, Kretschmer, and Thaler (2020). The task is to distinguish whether an input set $x\subseteq [n]$ has size either $k$ or…

Quantum Physics · Physics 2024-05-08 Aleksandrs Belovs , Ansis Rosmanis

In this work we present the first practical $\left(\frac{1}{e}-\epsilon\right)$-approximation algorithm to maximise a general non-negative submodular function subject to a matroid constraint. Our algorithm is based on combining the…

Data Structures and Algorithms · Computer Science 2017-03-22 Pau Segui-Gasco , Hyo-Sang Shin

We give a non-adaptive algorithm that makes $2^{\tilde{O}(\sqrt{k\log(1/\varepsilon_2 - \varepsilon_1)})}$ queries to a Boolean function $f:\{\pm 1\}^n \rightarrow \{\pm 1\}$ and distinguishes between $f$ being $\varepsilon_1$-close to some…

Data Structures and Algorithms · Computer Science 2024-04-23 Shivam Nadimpalli , Shyamal Patel

A Boolean function $f:\{0,1\}^n\to \{0,1\}$ is $k$-linear if it returns the sum (over the binary field $F_2$) of $k$ coordinates of the input. In this paper, we study property testing of the classes $k$-Linear, the class of all $k$-linear…

Computational Complexity · Computer Science 2020-06-09 Nader H. Bshouty

We study the minimum spanning tree (MST) problem in the massively parallel computation (MPC) model. Our focus is particularly on the *strictly sublinear* regime of MPC where the space per machine is $O(n^\delta)$. Here $n$ is the number of…

Data Structures and Algorithms · Computer Science 2025-10-10 Amir Azarmehr , Soheil Behnezhad , Rajesh Jayaram , Jakub Łącki , Vahab Mirrokni , Peilin Zhong

We give the first super-polynomial (in fact, mildly exponential) lower bounds for tolerant testing (equivalently, distance estimation) of monotonicity, unateness, and juntas with a constant separation between the "yes" and "no" cases.…

Computational Complexity · Computer Science 2023-09-25 Xi Chen , Anindya De , Yuhao Li , Shivam Nadimpalli , Rocco A. Servedio

An $(n,k,\ell)$-vector MDS code is a $\mathbb{F}$-linear subspace of $(\mathbb{F}^\ell)^n$ (for some field $\mathbb{F}$) of dimension $k\ell$, such that any $k$ (vector) symbols of the codeword suffice to determine the remaining $r=n-k$…

Information Theory · Computer Science 2021-09-29 Omar Alrabiah , Venkatesan Guruswami

The metric sketching problem is defined as follows. Given a metric on $n$ points, and $\epsilon>0$, we wish to produce a small size data structure (sketch) that, given any pair of point indices, recovers the distance between the points up…

Computational Geometry · Computer Science 2016-11-30 Piotr Indyk , Tal Wagner

We study approximation properties of sequences of centered random elements $X_d$, $d\in\mathbb N$, with values in separable Hilbert spaces. We focus on sequences of tensor product-type and, in particular, degree-type random elements, which…

Probability · Mathematics 2014-10-17 A. A. Khartov

Shannon entropy is the shortest average codeword length a lossless compressor can achieve by encoding i.i.d. symbols. However, there are cases in which the objective is to minimize the \textit{exponential} average codeword length, i.e. when…

Information Theory · Computer Science 2024-06-10 Andrea Somazzi , Paolo Ferragina , Diego Garlaschelli

Given an $n$-point metric space $(M,d)$, {\sc metric $1$-median} asks for a point $p\in M$ minimizing $\sum_{x\in M}\,d(p,x)$. We show that for each computable function $f\colon \mathbb{Z}^+\to\mathbb{Z}^+$ satisfying $f(n)=\omega(1)$, {\sc…

Data Structures and Algorithms · Computer Science 2022-01-06 Ching-Lueh Chang

We study the query complexity of the metric Steiner Tree problem, where we are given an $n \times n$ metric on a set $V$ of vertices along with a set $T \subseteq V$ of $k$ terminals, and the goal is to find a tree of minimum cost that…

Data Structures and Algorithms · Computer Science 2024-11-11 Yu Chen , Sanjeev Khanna , Zihan Tan

In view of the recent quest for well-behaved nonlinear extensions of the traditional Schroedinger-von Neumann unitary dynamics that could provide fundamental explanations of recent experimental evidence of loss of quantum coherence at the…

Quantum Physics · Physics 2010-11-13 Gian-Paolo Beretta

We estimate nonfactorizable 1/$N_c$ contributions in the $K\rightarrow 2\pi$ amplitudes using the approach proposed in our previous work. It is demonstrated that for the conventional (nonpenguin) operators these contributions are close in…

High Energy Physics - Phenomenology · Physics 2010-11-01 B. Blok , M. Shifman

We consider the task of implementing non-energy preserving gates (NEPG) on a finite-dimensional system S via an energy-preserving interaction with an external battery B. We prove that the entropic coherence of the battery (an instance of…

This paper introduces a numerical framework for establishing lower bounds on the conditional von-Neumann entropy in device-independent quantum cryptography and randomness extraction scenarios. Leveraging a hierarchy of semidefinite programs…

Quantum Physics · Physics 2025-08-22 Gereon Koßmann , René Schwonnek

Proving complexity lower bounds remains a challenging task: we only know how to prove conditional uniform lower bounds and nonuniform lower bounds in restricted circuit models. Williams (STOC 2010) showed how to derive nonuniform lower…

Computational Complexity · Computer Science 2026-03-10 Nikolai Chukhin , Alexander S. Kulikov , Ivan Mihajlin , Arina Smirnova

Entropies must correspond to mean values for them to be measurable. The Shannon entropy corresponds to the weighted arithmetic mean, whereas the Renyi entropy corresponds to the exponential mean. These means refer to code lengths, which are…

Statistical Mechanics · Physics 2011-10-25 B. H. Lavenda

Two-sample hypothesis testing-determining whether two sets of data are drawn from the same distribution-is a fundamental problem in statistics and machine learning with broad scientific applications. In the context of nonparametric testing,…

Machine Learning · Statistics 2026-04-21 Antoine Chatalic , Marco Letizia , Nicolas Schreuder , Lorenzo Rosasco