English
Related papers

Related papers: Fidelity-Based Smooth Min-Relative Entropy: Proper…

200 papers

The relative entropy between quantum states quantifies their distinguishability. The estimation of certain relative entropies has been investigated in the literature, e.g., the von Neumann relative entropy and sandwiched R\'enyi relative…

Quantum Physics · Physics 2026-02-24 Jinge Bao , Minbo Gao , Qisheng Wang

Coherent states (CS) quantum entropy can be split into two components. The dynamical entropy is linked with the dynamical properties of a quantum system. The measurement entropy, which tends to zero in the semiclassical limit, describes the…

chao-dyn · Physics 2009-10-28 Jaroslaw Kwapien , Wojciech Slomczynski , Karol Zyczkowski

A recent article introduced a hierarchy of quantities called $k$-fidelities that approximate the quantum process fidelity with increasing accuracy. The lowest approximation in this hiearchy is the $0$-fidelity. The authors gave a protocol…

Quantum Physics · Physics 2021-09-21 Karl Mayer

We investigate entropic uncertainty relations for two or more binary measurements, for example spin-$\frac{1}{2}$ or polarisation measurements. We argue that the effective anti-commutators of these measurements, i.e. the anti-commutators…

Quantum Physics · Physics 2014-07-30 Jędrzej Kaniewski , Marco Tomamichel , Stephanie Wehner

The quantum relative entropy is a measure of the distinguishability of two quantum states, and it is a unifying concept in quantum information theory: many information measures such as entropy, conditional entropy, mutual information, and…

Quantum Physics · Physics 2018-08-13 Mark M. Wilde

We derive entropic uncertainty relations for successive generalized measurements by using general descriptions of quantum measurement within two {distinctive operational} scenarios. In the first scenario, by merging {two successive…

Quantum Physics · Physics 2018-01-04 Kyunghyun Baek , Wonmin Son

Fluctuation relations are powerful equalities that hold far from equilibrium. However, the standard approach to include measurement and feedback schemes may become inapplicable in certain situations, including continuous measurements,…

Mesoscale and Nanoscale Physics · Physics 2019-09-05 Patrick P. Potts , Peter Samuelsson

We address the generalized uncertainty principle in scenarios of successive measurements. Uncertainties are characterized by means of generalized entropies of both the R\'{e}nyi and Tsallis types. Here, specific features of measurements of…

Quantum Physics · Physics 2018-05-30 Alexey E. Rastegin

Coherence and correlation are key features of the quantum system. Quantifying these quantities are astounding task in the framework of resource theory of quantum information processing. In this article, we identify an affinity-based metric…

Quantum Physics · Physics 2021-02-11 R. Muthuganesan , V. K. Chandrasekar , R. Sankaranarayanan

Measurement-based quantum repeaters employ entanglement distillation and swapping across links using locally prepared resource states of minimal size and local Bell measurements. In this Letter, we introduce a systematic protocol for…

Quantum Physics · Physics 2025-09-30 Yu Shi , Ashlesha Patil , Saikat Guha

Entanglement purification with two entangled resource pairs is widely employed in the literature on quantum repeater networks to counteract fidelity degradation introduced by noisy quantum memories and entanglement swapping across multiple…

Quantum Physics · Physics 2026-05-12 Anoosha Fayyaz , Prashant Krishnamurthy , Kaushik Seshadreesan , Amy Babay , David Tipper

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

Uncertainty quantification is a critical aspect of machine learning models, providing important insights into the reliability of predictions and aiding the decision-making process in real-world applications. This paper proposes a novel way…

Machine Learning · Computer Science 2024-01-02 Yusuf Sale , Paul Hofman , Lisa Wimmer , Eyke Hüllermeier , Thomas Nagler

Numerous entropy-type characteristics (functionals) generalizing R\'enyi entropy are widely used in mathematical statistics, physics, information theory, and signal processing for characterizing uncertainty in probability distributions and…

Statistics Theory · Mathematics 2011-03-28 David Källberg , Nikolaj Leonenko , Oleg Seleznjev

Quantum entanglement plays crucial roles in quantum information processing. Quantum entangled states have become the key ingredient in the rapidly expanding field of quantum information science. Although the nonclassical nature of…

Quantum Physics · Physics 2010-12-22 Ming Li , Shao-Ming Fei , Xianqing Li-Jost

Entanglement is not only the resource that fuels many quantum technologies but also plays a key role for some of the most profound open questions of fundamental physics. Experiments controlling quantum systems at the single quantum level…

Quantum Physics · Physics 2021-06-02 Bjarne Bergh , Martin Gärttner

We investigate the uncertainty principle for two successive projective measurements in terms of R\'enyi entropy based on a single quantum system. Our results cover a large family of the entropy (including the Shannon entropy) uncertainty…

Quantum Physics · Physics 2015-04-14 Jun Zhang , Yang Zhang , Chang-shui Yu

The relative entropy is a measure of the distinguishability of two quantum states. A great deal of progress has been made in the study of the relative entropy between an excited state and the vacuum state of a conformal field theory (CFT)…

High Energy Physics - Theory · Physics 2019-11-25 Ning Bao , Mudassir Moosa , Ibrahim Shehzad

The estimation of information measures of continuous distributions based on samples is a fundamental problem in statistics and machine learning. In this paper, we analyze estimates of differential entropy in $K$-dimensional Euclidean space,…

Information Theory · Computer Science 2021-11-29 Georg Pichler , Pablo Piantanida , Günther Koliander

Predictive inference requires balancing statistical accuracy against informational complexity, yet the choice of complexity measure is usually imposed rather than derived. We treat econometric objects as predictive rules, mappings from…

Statistics Theory · Mathematics 2026-02-16 Nicholas G. Polson , Daniel Zantedeschi