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We derive uncertainty relation inequalities according to the mutually unbiased measurements. Based on the calculation of the index of coincidence of probability distribution given by $d+1$ MUMs on any density operator $\rho$ in…

Quantum Physics · Physics 2015-06-09 Bin Chen , Shao-Ming Fei

We show that for fermion states, measurements of any two finite outcome particle quantum numbers (e.g.\ spin) are not constrained by a minimum total uncertainty. We begin by defining uncertainties in terms of the outputs of a measurement…

Quantum Physics · Physics 2012-12-07 Cael L. Hasse

Uncertainty relations are among the unique fingerprints of quantum physics, being direct expression of non-commutativity and complementarity. Entropic uncertainty relations arise in quantum information theory as the most natural expression…

Quantum Physics · Physics 2014-01-30 Cosmo Lupo , Seth Lloyd

Entropic uncertainty relations $H(A)+H(B)\geqslant \gamma$ give a nonzero lower bound $\gamma$ to the sum of the Shannon entropies $H$ of the outcome probabilities of incompatible observables $A$ and $B$. They are better than the…

Quantum Physics · Physics 2026-05-05 Alberto Riccardi , Lorenzo Maccone

The current study aims to examine uncertainty relations for measurements from generalized equiangular tight frames. Informationally overcomplete measurements are a valuable tool in quantum information processing, including tomography and…

Quantum Physics · Physics 2024-09-24 Alexey E. Rastegin

We derive two quantum uncertainty relations for position and momentum coarse-grained measurements. Building on previous results, we first improve the lower bound for uncertainty relations using the Renyi entropy, particularly in the case of…

Quantum Physics · Physics 2012-11-06 Łukasz Rudnicki , Stephen P. Walborn , Fabricio Toscano

Dissipative quantum systems are frequently described within the framework of the so-called "system-plus-reservoir" approach. In this work we assign their description to the Maximum Entropy Formalism and compare the resulting thermodynamic…

Statistical Mechanics · Physics 2017-01-04 Lisan M. M. Durão , Amir O. Caldeira

An uncertainty relation for the R\'enyi entropies of conjugate quantum observables is used to obtain a strong Heisenberg limit of the form ${\rm RMSE} \geq f(\alpha)/(\langle N\rangle+\frac12)$, bounding the root mean square error of any…

Quantum Physics · Physics 2022-11-21 Michael J. W. Hall

Uncertainty relations are central to quantum physics. While they were originally formulated in terms of variances, they have later been successfully expressed with entropies following the advent of Shannon information theory. Here, we…

Quantum Physics · Physics 2019-05-01 Anaelle Hertz , Nicolas J. Cerf

Most of the existing classification methods are aimed at minimization of empirical risk (through some simple point-based error measured with loss function) with added regularization. We propose to approach this problem in a more information…

Machine Learning · Computer Science 2015-01-22 Wojciech Marian Czarnecki , Jacek Tabor

We present novel bounds for estimating discrete probability distributions under the $\ell_\infty$ norm. These are nearly optimal in various precise senses, including a kind of instance-optimality. Our data-dependent convergence guarantees…

Statistics Theory · Mathematics 2024-02-14 Aryeh Kontorovich , Amichai Painsky

The electronic density \rho(r) in atoms, molecules and solids is, in general, a distribution that can be observed experimentally, containing spatial information projected from the total wave function. These density distributions can be…

Quantum Physics · Physics 2017-10-31 J. P. Restrepo Cuartas

Formalising the confrontation of opinions (models) to observations (data) is the task of Inferential Statistics. Information Theory provides us with a basic functional, the relative entropy (or Kullback-Leibler divergence), an asymmetrical…

Information Theory · Computer Science 2015-03-13 François Bavaud

Uncertainty relations and quantum entanglement are pivotal concepts in quantum theory. Beyond their fundamental significance in shaping our understanding of the quantum world, they also underpin crucial applications in quantum information…

Quantum Physics · Physics 2023-12-18 Yundu Zhao , Shan Huang , Shengjun Wu

Traditional thermodynamic trade-off relations usually apply to quantities that depend linearly on probability distributions. In contrast, many important information-theoretic measures, such as entropies, are nonlinear and therefore…

Statistical Mechanics · Physics 2026-02-17 Yoshihiko Hasegawa

Maximum entropy estimation is of broad interest for inferring properties of systems across many different disciplines. In this work, we significantly extend a technique we previously introduced for estimating the maximum entropy of a set of…

Data Analysis, Statistics and Probability · Physics 2016-01-05 Elliot A. Martin , Jaroslav Hlinka , Alexander Meinke , Filip Děchtěrenko , Jörn Davidsen

In this chapter we shall discuss the recent progresses of information theoretic tools in the context of free and confined harmonic oscillator. Confined quantum systems have provided appreciable interest in areas of physics, chemistry,…

Quantum Physics · Physics 2021-05-06 Neetik Mukherjee , Amlan K. Roy

A way to pose the entropic uncertainty principle for trace-preserving super-operators is presented. It is based on the notion of extremal unraveling of a super-operator. For given input state, different effects of each unraveling result in…

Quantum Physics · Physics 2015-05-19 Alexey E. Rastegin

Entropic uncertainty relations express the quantum mechanical uncertainty principle by quantifying uncertainty in terms of entropy. Central questions include the derivation of lower bounds on the total uncertainty for given observables, the…

Quantum Physics · Physics 2012-02-02 Sönke Niekamp , Matthias Kleinmann , Otfried Gühne

The Principle of Maximum Entropy is a rigorous technique for estimating an unknown distribution given partial information while simultaneously minimizing bias. However, an important requirement for applying the principle is that the…

Information Theory · Computer Science 2026-02-03 Kenneth Bogert , Matthew Kothe