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Related papers: Uncertainty for convolutions of sets

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We show how a number of well-known uncertainty principles for the Fourier transform, such as the Heisenberg uncertainty principle, the Donoho--Stark uncertainty principle, and Meshulam's non-abelian uncertainty principle, have little to do…

Functional Analysis · Mathematics 2020-09-14 Avi Wigderson , Yuval Wigderson

We consider solving linear optimization (LO) problems with uncertain objective coefficients. For such problems, we often employ robust optimization (RO) approaches by introducing an uncertainty set for the unknown coefficients. Typical RO…

Optimization and Control · Mathematics 2023-12-04 Ayaka Ueta , Mirai Tanaka , Ken Kobayashi , Kazuhide Nakata

In this paper we provide a new set of uncertainty principles for unitary operators using a sequence of inequalities with the help of the geometric-arithmetic mean inequality. As these inequalities are "fine-grained" compared with the…

Quantum Physics · Physics 2019-08-15 Bing Yu , Naihuan Jing , Xianqing Li-Jost

The Union Closed Sets Conjecture states that in every finite, nontrivial set family closed under taking unions there is an element contained in at least half of all the sets of the family. We investigate two new directions with respect to…

Combinatorics · Mathematics 2023-04-05 Nicolas Nagel

In this technical communique we study the maximal robust positively invariant set for state-constrained continuous-time nonlinear systems subjected to a bounded disturbance. Extending results from the theory of barriers, we show that this…

Optimization and Control · Mathematics 2021-03-02 Willem Esterhuizen , Tim Aschenbruck , Stefan Streif

A new uncertainty relation (UR) is obtained for a system of N identical pure entangled particles if we use symmetrized observables when deriving the inequality. This new expression can be written in a form where we identify a term which…

Quantum Physics · Physics 2016-08-19 Gustavo Rigolin

We introduce the notion of evolution on sets and study several sets endowed with this structure and obtain some results about this new notion.

General Mathematics · Mathematics 2025-10-07 Eduardo Santana

We develop a new framework of uncertainty variables to model uncertainty. An uncertainty variable is characterized by an uncertainty set, in which its realization is bound to lie, while the conditional uncertainty is characterized by a set…

Machine Learning · Statistics 2019-12-10 Rajat Talak , Sertac Karaman , Eytan Modiano

Some properties of the $q$-Fourier-sine transform are studied and $q$-analogues of the Heisenberg uncertainty principle is derived for the $q$-Fourier-cosine transform studied in \cite{FB} and for the $q$-Fourier-sine transform.

Quantum Algebra · Mathematics 2016-09-07 Neji Bettaibi , Ahmed Fitouhi , Wafa Binous

We give a simple proof of the uncertainty principle with quantum side information, as in [Berta et al. Nature Physics 6, 659 (2010)], invoking the monotonicity of the relative entropy. Our proof shows that the entropic uncertainty principle…

Quantum Physics · Physics 2011-12-08 Patrick J. Coles , Li Yu , Michael Zwolak

Under Wigdersons' framework and by sorting out the technical points in the recent works of Tang (J. Fourier Anal. Appl. 31 (2025)) and Dias-Luef-Prata (J. Math. Pures Appl. (9) 198 (2025)), we prove an abstract uncertainty principle for…

Analysis of PDEs · Mathematics 2025-06-19 Tianxiao Huang , Ze Li , Jiani Liu

The concept of a visible point of a convex set relative to a given point is introduced. A number of basic properties of such visible point sets is developed. In particular, it is shown that this concept is useful in the study of best…

Functional Analysis · Mathematics 2012-11-07 Frank Deutsch , Hein Hundal , Ludmil Zikatanov

The correct use and interpretation of models depends on several steps, two of which being the calibration by parameter estimation and the analysis of uncertainty. In the biological literature, these steps are seldom discussed together, but…

Quantitative Methods · Quantitative Biology 2015-08-17 André Chalom , Paulo Inácio de Knegt López de Prado

We present a new strategic voting model where we use uncertainty representation to model preferences. Specifically, we use probability sets as uncertainty representations, together with lower and upper expected utility gains to take…

Computer Science and Game Theory · Computer Science 2026-05-18 Henri Surugue , Sébastien Destercke

A coordinate-free proof of the Maximum Principle is provided in the specific case of an optimal control problem with fixed time. Our treatment heavily relies on a special notion of variation of curves that consist of a concatenation of…

Differential Geometry · Mathematics 2007-05-23 B. Langerock

The uncertainty principle can be expressed in entropic terms, also taking into account the role of entanglement in reducing uncertainty. The information exclusion principle bounds instead the correlations that can exist between the outcomes…

Quantum Physics · Physics 2014-02-26 Patrick J. Coles , Marco Piani

In the article, the deformation of special relativity within the frame of conformable derivative is formulated. Within this context, the two postulates of the theory were re-stated. And, the addition of velocity laws were derived and used…

Classical Physics · Physics 2022-08-31 Ahmed Al-Jamel , Mohamed. Al-Masaeed , Eqab. M. Rabei , Dumitru Baleanu

Based on the doubly special relativity we find a new type of generalized uncertainty principle (GUP) where the coordinate remain unaltered at the high energy while the momentum is deformed at the high energy so that it may be bounded from…

General Relativity and Quantum Cosmology · Physics 2018-09-26 Won Sang Chung , Hassan Hassanabadi

Any permutation has a disjoint cycle decomposition and concept generates an equivalence class on the symmetry group called the cycle-type. The main focus of this work is on permutations of restricted cycle-types, with particular emphasis on…

Combinatorics · Mathematics 2014-06-11 Tewodros Amdeberhan , Victor H. Moll

Decision-making under uncertainty is hugely important for any decisions sensitive to perturbations in observed data. One method of incorporating uncertainty into making optimal decisions is through robust optimization, which minimizes the…

Methodology · Statistics 2021-09-06 Chancellor Johnstone , Bruce Cox