Tight Entropic Uncertainty Relations
- URL: http://arxiv.org/abs/2605.01832v1
- Date: Sun, 03 May 2026 11:57:25 GMT
- Title: Tight Entropic Uncertainty Relations
- Abstract summary: Entropic uncertainty relations $H(A)+H(B)geqslant $ give a nonzero lower bound $$ to the sum of the Shannon entropies $H$ of the outcome probabilities of incompatible observables $A$ and $B$.<n>They are better than the variance-based uncertainty relations because they only depend on the Born statistics of the outcomes and not on the outcomes themselves, and because bounds $$ typically are state independent.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Entropic uncertainty relations $H(A)+H(B)\geqslant γ$ give a nonzero lower bound $γ$ to the sum of the Shannon entropies $H$ of the outcome probabilities of incompatible observables $A$ and $B$. They are better than the variance-based uncertainty relations because they only depend on the Born statistics of the outcomes and not on the outcomes themselves, and because bounds $γ$ typically are state independent. Here we provide a state-independent lower bound $γ_s$ that is better than the textbook Maassen-Uffink bound and, in the limit of the parameter $s\to 2$, becomes asymptotically tight for all $A,B$. The bound can be extended to Renyi entropies.
Related papers
- Asymptotically Optimal Regret for Reinforcement Learning without Horizon Dependence [54.59847568544922]
We study horizon-free regret for finite-horizon time-homogeneous Markov decision processes with $A$ states, $A$ actions, horizon $H$, and per-trajectory total reward bounded by $1$.<n>We prove a regret upper bound [tilde O(sqrtSAK+S8A3)] with failure probability $$, where $K$ is the number of episodes and $tilde O(sqrtSAK+S3K)$ hides $mathsfpoly
arXiv Detail & Related papers (2026-07-22T07:42:19Z) - Scale-Sensitive Shattering: Learnability and Evaluability at Optimal Scale [54.65053906803857]
We study the optimal scale at which real-valued function classes exhibit uniform convergence and learnability.<n>Our main result establishes a scale-sensitive generalization of the fundamental theorem of PAC learning.<n>We also highlight several open questions on quantitative sample complexity and evaluability.
arXiv Detail & Related papers (2026-05-13T15:41:30Z) - Confidence uncertainty: position and momentum can be jointly determined with a guaranteed probability [6.911044030089646]
Heisenberg's uncertainty principle states that the position and momentum of a particle cannot be sharply determined simultaneously.<n>Standard-deviation and entropic formulations capture the spread of the probability distribution but say little about the probability itself contained in a small region.<n>We introduce the "confidence uncertainty" $cx(_x)$ as the minimal Lebesgue measure of the support set in which the particle is found with probability at least $_x$.
arXiv Detail & Related papers (2026-05-06T04:29:01Z) - Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression [65.82017723631897]
We show that scale-invariant upper bounds on self-normalized martingales are possible.<n>We derive a self-normalized concentration inequality free of the usual regularization penalties.
arXiv Detail & Related papers (2026-05-02T22:39:00Z) - Semicontinuity bounds for the von Neumann entropy and partial majorization [0.0]
We consider families of tight upper bounds on the difference $S(rho)-S(sigma)$ with the rank/energy constraint imposed on the state $rho$.<n>The upper bounds within these families depend on the parameter $m$ of partial majorization.
arXiv Detail & Related papers (2025-04-10T19:55:06Z) - Beyond likelihood ratio bias: Nested multi-time-scale stochastic approximation for likelihood-free parameter estimation [49.78792404811239]
We study inference in simulation-based models where the analytical form of the likelihood is unknown.<n>We use a ratio-free nested multi-time-scale approximation (SA) method that simultaneously tracks the score and drives the parameter update.<n>We show that our algorithm can eliminate the original bias $Obig(sqrtfrac1Nbig)$ and accelerate the convergence rate from $Obig(beta_k+sqrtfracalpha_kNbig)$.
arXiv Detail & Related papers (2024-11-20T02:46:15Z) - Some Remarks on the Regularized Hamiltonian for Three Bosons with
Contact Interactions [77.34726150561087]
We discuss some properties of a model Hamiltonian for a system of three bosons interacting via zero-range forces in three dimensions.
In particular, starting from a suitable quadratic form $Q$, the self-adjoint and bounded from below Hamiltonian $mathcal H$ can be constructed.
We show that the threshold value $gamma_c$ is optimal, in the sense that the quadratic form $Q$ is unbounded from below if $gammagamma_c$.
arXiv Detail & Related papers (2022-07-01T10:01:14Z) - Generalized uncertainty principle and Asymptotic Safe gravity [0.0]
We compute the Hawking temperature of a black hole in two different ways.
The relation between $beta$ and $om$, $xi$ allow us to transfer upper bounds from one parameter to the others.
arXiv Detail & Related papers (2022-04-15T10:45:33Z) - High Probability Bounds for a Class of Nonconvex Algorithms with AdaGrad
Stepsize [55.0090961425708]
We propose a new, simplified high probability analysis of AdaGrad for smooth, non- probability problems.
We present our analysis in a modular way and obtain a complementary $mathcal O (1 / TT)$ convergence rate in the deterministic setting.
To the best of our knowledge, this is the first high probability for AdaGrad with a truly adaptive scheme, i.e., completely oblivious to the knowledge of smoothness.
arXiv Detail & Related papers (2022-04-06T13:50:33Z) - Attainability and lower semi-continuity of the relative entropy of
entanglement, and variations on the theme [8.37609145576126]
The relative entropy of entanglement $E_Rite is defined as the distance of a multi-part quantum entanglement from the set of separable states as measured by the quantum relative entropy.
We show that this state is always achieved, i.e. any state admits a closest separable state, even in dimensions; also, $E_Rite is everywhere lower semi-negative $lambda_$quasi-probability distribution.
arXiv Detail & Related papers (2021-05-17T18:03:02Z) - Energy-Time Uncertainty Relation for Absorbing Boundaries [0.0]
We prove the uncertainty relation $sigma_T, sigma_E geq hbar/2$ between the time $T$ of detection of a quantum particle on the surface.
arXiv Detail & Related papers (2020-05-29T12:04:57Z) - A Simple Convergence Proof of Adam and Adagrad [74.24716715922759]
We show a proof of convergence between the Adam Adagrad and $O(d(N)/st)$ algorithms.
Adam converges with the same convergence $O(d(N)/st)$ when used with the default parameters.
arXiv Detail & Related papers (2020-03-05T01:56:17Z) - Curse of Dimensionality on Randomized Smoothing for Certifiable
Robustness [151.67113334248464]
We show that extending the smoothing technique to defend against other attack models can be challenging.
We present experimental results on CIFAR to validate our theory.
arXiv Detail & Related papers (2020-02-08T22:02:14Z) - Optimal upper bound of entropic uncertainty relation for mutually
unbiased bases [0.0]
We have obtained the optimal upper bound of entropic uncertainty relation for $N$ Mutually Unbiased Bases (MUBs)
Our result is valid for any state when $N$ is $d+1$, where $d$ is the dimension of the related system.
arXiv Detail & Related papers (2020-01-31T12:33:04Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.