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We will show that if $\sM$ is a factor, then for any pair $\f, \p\in\sMdsup$ of normal positive linear functionals on $\sM$, the inequality: $$ \lrnorm{\f}\leq \lrnorm{\p} $$ is equivalent to the fact that there exist a countable family…

Operator Algebras · Mathematics 2012-08-28 Masamichi Takesaki

State and measurement tomography make assumptions about the experimental states or measurements. These assumptions are often not justified because state preparation and measurement errors are unavoidable in practice. Here we describe how…

Quantum Physics · Physics 2015-02-12 Cyril Stark

Let f be an arbitrary positive integer valued function. The goal of this note is to show that one can construct a finitely generated group in which the discrete log problem is polynomially equivalent to computing the function f. In…

Group Theory · Mathematics 2025-11-27 Christopher Battarbee , Arman Darbinyan , Delaram Kahrobaei

Dilative semistability extends the notion of semi-selfsimilarity for infinitely divisible stochastic processes by introducing an additional scaling in the convolution exponent. It is shown that this scaling relation is a natural extension…

Probability · Mathematics 2016-03-14 Peter Kern , Lina Wedrich

In this paper we consider the problem of uniformity testing with limited memory. We observe a sequence of independent identically distributed random variables drawn from a distribution $p$ over $[n]$, which is either uniform or is…

Information Theory · Computer Science 2022-06-22 Tomer Berg , Or Ordentlich , Ofer Shayevitz

Consider an algorithm computing in a differential field with several commuting derivations such that the only operations it performs with the elements of the field are arithmetic operations, differentiation, and zero testing. We show that,…

Commutative Algebra · Mathematics 2021-08-31 Wei Li , Alexey Ovchinnikov , Gleb Pogudin , Thomas Scanlon

Semidefinite programming (SDP) is a powerful framework from convex optimization that has striking potential for data science applications. This paper develops a provably correct randomized algorithm for solving large, weakly constrained SDP…

Optimization and Control · Mathematics 2021-03-26 Alp Yurtsever , Joel A. Tropp , Olivier Fercoq , Madeleine Udell , Volkan Cevher

Large Language Models (LLMs) achieve impressive accuracy on mathematical reasoning benchmarks, yet their performance drops when problems are modified with simple changes like different names or numbers. Code execution methods, which let…

Artificial Intelligence · Computer Science 2026-05-27 Matthew Kutakh

The low-rank matrix completion problem asks whether a given real matrix with missing values can be completed so that the resulting matrix has low rank or is close to a low-rank matrix. The completed matrix is often required to satisfy…

Computational Complexity · Computer Science 2025-06-24 Dror Chawin , Ishay Haviv

Large scale discrete uniform and homogeneous $P$-values often arise in applications with multiple testing. For example, this occurs in genome wide association studies whenever a nonparametric one-sample (or two-sample) test is applied…

Methodology · Statistics 2021-12-08 Marta Cousido-Rocha , Jacobo de Uña-Álvarez , Sebastian Döhler

Consider a quantum cat map $M$ associated to a matrix $A\in\mathop{\mathrm{Sp}}(2n,\mathbb Z)$, which is a common toy model in quantum chaos. We show that the mass of eigenfunctions of $M$ on any nonempty open set in the position-frequency…

Analysis of PDEs · Mathematics 2023-04-25 Semyon Dyatlov , Malo Jézéquel

This paper proposes an extension of Chaitin's halting probability \Omega to a measurement operator in an infinite dimensional quantum system. Chaitin's \Omega is defined as the probability that the universal self-delimiting Turing machine U…

Quantum Physics · Physics 2007-05-23 Kohtaro Tadaki

Positive semidefinite programs are an important subclass of semidefinite programs in which all matrices involved in the specification of the problem are positive semidefinite and all scalars involved are non-negative. We present a parallel…

Computational Complexity · Computer Science 2011-04-14 Rahul Jain , Penghui Yao

A nonparametric anomalous hypothesis testing problem is investigated, in which there are totally n sequences with s anomalous sequences to be detected. Each typical sequence contains m independent and identically distributed (i.i.d.)…

Machine Learning · Computer Science 2016-12-15 Shaofeng Zou , Yingbin Liang , H. Vincent Poor , Xinghua Shi

We study the parameterized complexity of algorithmic problems whose input is an integer set $A$ in terms of the doubling constant $C := |A + A|/|A|$, a fundamental measure of additive structure. We present evidence that this new…

Data Structures and Algorithms · Computer Science 2024-07-26 Tim Randolph , Karol Węgrzycki

In this paper we consider the problem of unambiguous discrimination between a set of linearly independent pure quantum states. We show that the design of the optimal measurement that minimizes the probability of an inconclusive result can…

Quantum Physics · Physics 2016-11-17 Yonina C. Eldar

Let $[q] = \{0,1,\ldots,q-1\}$, let $\Delta[q]$ denote the simplex of probability measures on $[q]$, and let $\gamma$ denote the Lebesgue measure normalized on $\Delta[q]$. We prove that for any symmetric monotone function $f \colon[q]^n…

Probability · Mathematics 2026-05-20 Saba Lepsveridze , Allen Lin

We investigate the problem of estimating the number of modes (i.e., local maxima) - a well known question in statistical inference - and we show how to do so without presmoothing the data. To this end, we modify the ideas of persistence…

Statistics Theory · Mathematics 2016-05-03 Ulrich Bauer , Axel Munk , Hannes Sieling , Max Wardetzky

Some problems of statistics can be reduced to extremal problems of minimizing functionals of smooth functions defined on the cube $[0,1]^m$, $m\geq 2$. In this paper, we study a class of extremal problems that is closely connected to the…

Probability · Mathematics 2010-12-06 Alexander Nazarov , Natalia Stepanova

We establish new upper and lower bounds on the number of queries required to test convexity of functions over various discrete domains. 1. We provide a simplified version of the non-adaptive convexity tester on the line. We re-prove the…

Computational Complexity · Computer Science 2019-08-08 Aleksandrs Belovs , Eric Blais , Abhinav Bommireddi