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The Heisenberg uncertainty principle sets a lower bound on the sensitivity of continuous optical measurements of force. This bound, the standard quantum limit, can only be reached when a mechanical oscillator subjected to the force is…

Heisenberg's uncertainty principle states that the position and momentum of a particle cannot be sharply determined simultaneously. Standard-deviation and entropic formulations capture the spread of the probability distribution but say…

Quantum Physics · Physics 2026-05-07 Jia-Yi Lin , Xin-Yu Li , Wei Wang , Shengjun Wu

This paper deduces universal uncertainty principle in different quantum theories after about one century of proposing uncertainty principle by Heisenberg, i.e., new universal uncertainty principle of any orders of physical quantities in…

Quantum Physics · Physics 2018-07-31 C. Huang , Yong-Chang Huang

Within the Heisenberg's uncertainty principle it is explicitly discussed the impact of these inequalities on the theory of integrated photonics at sub-wavelength regime. More especially, the uncertainty of the effective index values in…

Quantum Physics · Physics 2016-04-04 Bruno Bêche , E Gaviot

The classical uncertainty principles deal with functions on abelian groups. In this paper, we discuss the uncertainty principles for finite index subfactors which include the cases for finite groups and finite dimensional Kac algebras. We…

Operator Algebras · Mathematics 2015-11-12 Chunlan Jiang , Zhengwei Liu , Jinsong Wu

We approach uncertainty principles of Cowling-Price-Heis-\\enberg-type as a variational principle on modulation spaces. In our discussion we are naturally led to compact localization operators with symbols in modulation spaces. The optimal…

Functional Analysis · Mathematics 2023-03-21 Nuno Costa Dias , Franz Luef , João Nuno Prata

The aim of the paper is two-fold. First, we provide an explicit form of the functions for which equality holds for the uncertainty inequalities studied in \cite{Fei}. Second, we establish an $L^p$-type Heisenberg-Pauli-Weyl uncertainty…

Functional Analysis · Mathematics 2025-03-10 Sunit Ghosh , Younis Ahmad Bhat , Jitendriya Swain

Optical-model potentials (OMPs) continue to play a key role in nuclear reaction calculations. However, the uncertainty of phenomenological OMPs in widespread use -- inherent to any parametric model trained on data -- has not been fully…

Nuclear Theory · Physics 2023-01-06 C. D. Pruitt , J. E. Escher , R. Rahman

This paper presents a proof of an uncertainty principle of Donoho-Stark type involving $\varepsilon$-concentration of localization operators. More general operators associated with time-frequency representations in the Cohen class are then…

Functional Analysis · Mathematics 2018-01-12 Paolo Boggiatto , Evanthia Carypis , Alessandro Oliaro

Toy models for quantum evolution in the presence of closed timelike curves (CTCs) have gained attention in the recent literature due to the strange effects they predict. The circuits that give rise to these effects appear quite abstract and…

Quantum Physics · Physics 2013-05-30 J. L. Pienaar , C. R. Myers , T. C. Ralph

The linear canonical transform (LCT) serves as a powerful generalization of the Fourier transform (FT), encapsulating various integral transforms within a unified framework. This versatility has made it a cornerstone in fields such as…

Functional Analysis · Mathematics 2024-10-28 Muhammad Adnan Samad , Yuanqing Xia , Saima Siddiqui , Muhammad Younus Bhat

We shed new light on Heisenberg's uncertainty principle in the sense of Beurling, by offering an essentially different proof which permits us to weaken the assumptions substantially, and examples show that the result is sharp. The proof…

Functional Analysis · Mathematics 2013-11-11 Haakan Hedenmalm

The uncertainty principle, originally formulated by Heisenberg, dramatically illustrates the difference between classical and quantum mechanics. The principle bounds the uncertainties about the outcomes of two incompatible measurements,…

Quantum Physics · Physics 2011-03-02 Mario Berta , Matthias Christandl , Roger Colbeck , Joseph M. Renes , Renato Renner

In this paper, we introduce a family of integral transforms, denoted by \(\mathcal{O}_{\alpha}\), and constructed via kernel fusion of the fractional Fourier transform (FRFT) with angle \(\alpha \notin \pi \mathbb{Z}\). We demonstrate that…

Classical Analysis and ODEs · Mathematics 2026-03-09 Lai Tien Minh , Trinh Tuan

In this paper we review the Heisenberg uncertainty principle in a discrete setting and, as in the classical uncertainty principle, we give it a dynamical sense related to the discrete Schr\"odinger equation. We study the convergence of the…

Analysis of PDEs · Mathematics 2014-11-04 Aingeru Fernández-Bertolin

In this article we consider linear operators satisfying a generalized commutation relation of a type of the Heisenberg-Lie algebra. It is proven that a generalized inequality of the Hardy's uncertainty principle lemma follows. Its…

Functional Analysis · Mathematics 2015-05-19 Toshimitsu Takaesu

The problem of diagonalization of Hamiltonians of N-dimensional boson systems by means of time-dependent canonical transformations (CT) is considered, the case of quadratic Hamiltonians being treated in greater detail. The unitary generator…

Quantum Physics · Physics 2007-05-23 D. A. Trifonov

The classical uncertainty principle of harmonic analysis states that a nontrivial function and its Fourier transform cannot both be sharply localized. It plays an important role in signal processing and physics. This paper generalizes the…

Information Theory · Computer Science 2017-08-02 Kit Ian Kou , Yan Yang , Cuiming Zou

In the present work the role that a generalized uncertainty principle could play in the quantization of the electromagnetic field is analyzed. It will be shown that we may speak of a Fock space, a result that implies that the concept of…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Abel Camacho

There has been remarkable progress over the past decade in establishing finite-sample, non-asymptotic bounds on recovering unknown system parameters from observed system behavior. Surprisingly, however, we show that the current…

Machine Learning · Statistics 2026-04-24 Yichen Zhou , Stephen Tu