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Equiangular tight frames are examples of Grassmannian line packings for a Hilbert space. More specifically, according to a bound by Welch, they are minimizers for the maximal magnitude occurring among the inner products of all pairs of…

Functional Analysis · Mathematics 2015-09-18 Bernhard G. Bodmann , John Haas

We characterize the extreme points of the set of incentive-compatible mechanisms for screening problems with linear utility. Our framework subsumes problems with and without transfers, such as monopoly pricing, principal-optimal bilateral…

Theoretical Economics · Economics 2025-10-24 Patrick Lahr , Axel Niemeyer

The space of positive operator-valued measures on the Borel sets of a compact (or even locally compact) Hausdorff space with values in the algebra of linear operators acting on a d-dimensional Hilbert space is studied from the perspectives…

Quantum Physics · Physics 2015-05-30 Douglas Farenick , Sarah Plosker , Jerrod Smith

Partially observable Markov decision processes (POMDPs) model specific environments in sequential decision-making under uncertainty. Critically, optimal policies for POMDPs may not be robust against perturbations in the environment.…

Artificial Intelligence · Computer Science 2025-08-21 Maris F. L. Galesloot , Roman Andriushchenko , Milan Češka , Sebastian Junges , Nils Jansen

We show how an upper bound for the ability to discriminate any number N of candidates for the Hamiltonian governing the evolution of an open quantum system may be calculated by numerically efficient means. Our method applies an effective…

Quantum Physics · Physics 2018-05-23 Alexander Holm Kiilerich , Klaus Mølmer

We define a complete measurement of a quantum observable (POVM) as a measurement of the maximally refined version of the POVM. Complete measurements give information from the multiplicities of the measurement outcomes and can be viewed as…

Quantum Physics · Physics 2015-06-05 Juha-Pekka Pellonpää

The task of reconstructing a matrix given a sample of observedentries is known as the matrix completion problem. It arises ina wide range of problems, including recommender systems, collaborativefiltering, dimensionality reduction, image…

Statistics Theory · Mathematics 2014-12-20 Jean Lafond , Olga Klopp , Eric Moulines , Jospeh Salmon

In a recent paper, Buscemi and al. defined a notion of clean positive operator valued measures (POVMs). We here characterize which POVMs are clean in some class that we call quasi-qubit POVMs, namely POVMs whose elements are all rank-one or…

Quantum Physics · Physics 2015-06-26 Jonas Kahn

To develop a unitary quantum theory with probabilistic description for pseudo- Hermitian systems one needs to consider the theories in a different Hilbert space endowed with a positive definite metric operator. There are different…

Quantum Physics · Physics 2013-05-10 Ananya Ghatak , Bhabani Prasad Mandal

We discuss the problem of implementing generalized measurements (POVMs) with linear optics, either based upon a static linear array or including conditional dynamics. In our approach, a given POVM shall be identified as a solution to an…

Quantum Physics · Physics 2016-08-16 Peter van Loock , Kae Nemoto , William J. Munro , Philippe Raynal , Norbert Lütkenhaus

Many prominent quantum computing algorithms with applications in fields such as chemistry and materials science require a large number of measurements, which represents an important roadblock for future real-world use cases. We introduce a…

We use tools of additive combinatorics for the study of subvarieties defined by {\it high rank} families of polynomials in high dimensional $\mathbb{F} _q$-vector spaces. In the first, analytic part of the paper we prove a number properties…

Algebraic Geometry · Mathematics 2020-07-20 David Kazhdan , Tamar Ziegler

Any decision making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This paper proposes new methods for empirically assessing forecast calibration in a multivariate setting where…

Methodology · Statistics 2014-07-02 Thordis L. Thorarinsdottir , Michael Scheuerer , Christopher Heinz

Many processes, such as discrete event systems in engineering or population dynamics in biology, evolve in discrete space and continuous time. We consider the problem of optimal decision making in such discrete state and action space…

Machine Learning · Computer Science 2020-10-27 Bastian Alt , Matthias Schultheis , Heinz Koeppl

Quantum parameter estimation holds significant promise for achieving high precision through the utilization of the most informative measurements. While various lower bounds have been developed to assess the best accuracy for estimates, they…

Quantum Physics · Physics 2024-07-19 Jianchao Zhang , Jun Suzuki

We study an extremal projection principle for families of operators ordered by domination, induced by fixed bounded linear mappings acting on a source with an additive baseline. Stability is defined through domination of second--order…

Functional Analysis · Mathematics 2026-02-04 Philip Kennerberg

A convex envelope for the problem of finding the best approximation to a given matrix with a prescribed rank is constructed. This convex envelope allows the usage of traditional optimization techniques when additional constraints are added…

Functional Analysis · Mathematics 2016-08-30 Fredrik Andersson , Marcus Carlsson , Carl Olsson

The objective of this work is to develop a recursive, discrete time quantum filtering equation for a system that interacts with a probe, on which measurements are performed according to the Positive Operator Valued Measures (POVMs)…

Quantum Physics · Physics 2013-09-10 Ram A. Somaraju , Alain Sarlette , Hugo Thienpont

Efficiently enumerating all the extreme points of a polytope identified by a system of linear inequalities is a well-known challenge issue.We consider a special case and present an algorithm that enumerates all the extreme points of a…

Discrete Mathematics · Computer Science 2024-07-04 Yasuko Matsui , Takeshi Naitoh , Ping Zhan

Classifying points in high dimensional spaces is a fundamental geometric problem in machine learning. In this paper, we address classifying points in the $d$-dimensional Hilbert polygonal metric. The Hilbert metric is a generalization of…

Computational Geometry · Computer Science 2026-01-21 Aditya Acharya , Auguste H. Gezalyan , David M. Mount
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