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We study fine-grained uncertainty relations for several quantum measurements in a finite-dimensional Hilbert space. The proposed approach is based on exact calculation or estimation of the spectral norms of corresponding positive matrices.…

Quantum Physics · Physics 2015-05-07 Alexey E. Rastegin

We improve the entropic uncertainty relations for position and momentum coarse-grained measurements. We derive the continuous, coarse-grained counterparts of the discrete uncertainty relations based on the concept of majorization. The…

Quantum Physics · Physics 2015-06-30 Łukasz Rudnicki

Here, we investigate the uncertainty of dynamical observables in classical systems manipulated by repeated measurements and feedback control; the precision should be enhanced in the presence of an external controller but limited by the…

Statistical Mechanics · Physics 2020-01-23 Tan Van Vu , Yoshihiko Hasegawa

We discuss the relationship between entropic uncertainty relations and entanglement. We present two methods for deriving separability criteria in terms of entropic uncertainty relations. Especially we show how any entropic uncertainty…

Quantum Physics · Physics 2009-11-10 Otfried Guehne , Maciej Lewenstein

We consider a range of "theories" that violate the uncertainty relation for anti-commuting observables derived in [JMP, 49, 062105 (2008)]. We first show that Tsirelson's bound for the CHSH inequality can be derived from this uncertainty…

Quantum Physics · Physics 2011-05-02 Greg Ver Steeg , Stephanie Wehner

The uncertainty principle sets a bound on our ability to predict the measurement outcomes of two incompatible observables which are measured on a quantum particle simultaneously. In quantum information theory, the uncertainty principle can…

Quantum Physics · Physics 2019-12-03 H. Dolatkhah , S. Haseli , S. Salimi , A. s. Khorashad

We present a novel approach to uncertainty quantification in classification tasks based on label-wise decomposition of uncertainty measures. This label-wise perspective allows uncertainty to be quantified at the individual class level,…

Machine Learning · Computer Science 2024-06-05 Yusuf Sale , Paul Hofman , Timo Löhr , Lisa Wimmer , Thomas Nagler , Eyke Hüllermeier

Entropic uncertainty relations are interesting in their own rights as well as for a lot of applications. Keeping this in mind, we try to make the corresponding inequalities as tight as possible. The use of parametrized entropies also allows…

Quantum Physics · Physics 2023-05-30 Alexey E. Rastegin

Causal parameters may not be point identified in the presence of unobserved confounding. However, information about non-identified parameters, in the form of bounds, may still be recovered from the observed data in some cases. We develop a…

Methodology · Statistics 2020-07-02 Noam Finkelstein , Ilya Shpitser

We propose a new scheme to express the uncertainty principle in form of inequality of the bipartite correlation functions for a given multipartite state, which provides an experimentally feasible and model-independent way to verify various…

Quantum Physics · Physics 2014-03-05 Jun-Li Li , Kun Du , Cong-Feng Qiao

Entropic uncertainty relations provide an information-theoretic framework for quantifying the fundamental indeterminacy inherent in quantum mechanics. We propose more stringent quantum-memory-assisted entropic uncertainty relations for…

Quantum Physics · Physics 2026-04-07 Qing-Hua Zhang , Cong Xu , Jing-Feng Wu , Shao-Ming Fei

Estimating how uncertain an AI system is in its predictions is important to improve the safety of such systems. Uncertainty in predictive can result from uncertainty in model parameters, irreducible data uncertainty and uncertainty due to…

Machine Learning · Statistics 2018-12-03 Andrey Malinin , Mark Gales

We introduce a novel rule-based approach for handling regression problems. The new methodology carries elements from two frameworks: (i) it provides information about the uncertainty of the parameters of interest using Bayesian inference,…

Machine Learning · Statistics 2021-10-11 Themistoklis Botsas , Lachlan R. Mason , Indranil Pan

We analyze the Schwarz inequality and its generalizations, as well as inequalities resulting from the Jensen inequality. They are used in quantum theory to derive the Heisenberg-Robertson (HR) and Schroedinger-Robertson (SR) uncertainty…

Quantum Physics · Physics 2026-04-16 Krzysztof Urbanowski

Two special situations where the standard uncertainty product inequality appears to be useless are modified. One such case is noted to also trivialize the recently-introduced alternatives [Phys. Rev. Lett. 113, 260401 (2014); Sci. Rep. 6,…

Quantum Physics · Physics 2016-12-30 Kamal Bhattacharyya

We derive a family of necessary separability criteria for finite-dimensional systems based on inequalities for variances of observables. We show that every pure bipartite entangled state violates some of these inequalities. Furthermore, a…

Quantum Physics · Physics 2016-09-08 Otfried Guehne

We extend the concept of Wigner-Yanase-Dyson skew information to something we call ``metric adjusted skew information'' (of a state with respect to a conserved observable). This ``skew information'' is intended to be a non-negative quantity…

Mathematical Physics · Physics 2008-08-11 Frank Hansen

Indirect measurement can be used to read out the outcome of a quantum system without resorting to a straightforward approach, and it is the foundation of the measurement uncertainty relations that explain the incompatibility of conjugate…

Quantum Physics · Physics 2022-08-09 Ryo Mihashi , Yoshihiko Hasegawa

The entropic uncertainty relation proven by Maassen and Uffink for arbitrary pairs of two observables is known to be non-optimal. Here, we call an uncertainty relation optimal, if the lower bound can be attained for any value of either of…

Uncertainty relations involving complementary observables are one of the cornerstones of quantum mechanics. Aside from their fundamental significance, they play an important role in practical applications, such as detection of quantum…

Quantum Physics · Physics 2018-07-19 Fabricio Toscano , Daniel S. Tasca , Łukasz Rudnicki , Stephen P. Walborn