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Exploiting the notion of measurement-induced nonlocality [Phys.Rev. Lett. 106, 120401 (2011)], we introduce a new measure to quantify the nonbilocal correlation. We establish a simple relation between the nonlocal and nonbilocal measures…

Quantum Physics · Physics 2022-06-16 R. Muthuganesan , S. Balakrishnan , V. K. Chandrasekar

We analyze quantum state estimation for finite samples based on symmetry information. The used measurement concept compares an unknown qubit to a reference state. We describe explicitly an adaptive strategy, that enhances the estimation…

Quantum Physics · Physics 2009-11-13 Christof J. Happ , Matthias Freyberger

We give a bound to the precision in the estimation of a parameter in terms of the expectation value of an observable. It is an extension of the Cramer-Rao inequality and of the Heisenberg uncertainty relation, where the estimation precision…

Quantum Physics · Physics 2012-07-11 Vittorio Giovannetti , Seth Lloyd , Lorenzo Maccone

The quantum metric tensor was introduced for defining the distance in the parameter space of a system. However, it is also useful for other purposes, like predicting quantum phase transitions. Due to the physical information this tensor…

Quantum Physics · Physics 2016-05-27 J. Alvarez-Jimenez , J. D. Vergara

Regression tasks, notably in safety-critical domains, require proper uncertainty quantification, yet the literature remains largely classification-focused. In this light, we introduce a family of measures for total, aleatoric, and epistemic…

Machine Learning · Computer Science 2025-10-30 Christopher Bülte , Yusuf Sale , Gitta Kutyniok , Eyke Hüllermeier

Uncertainty principle plays a vital role in quantum physics. The Wigner-Yanase skew information characterizes the uncertainty of an observable with respect to the measured state. We generalize the uncertainty relations for two quantum…

Quantum Physics · Physics 2021-09-06 Qing-Hua Zhang , Jing-Feng Wu , Shao-Ming Fei

We introduce new measures of decoherence appropriate for evaluation of quantum computing designs. Environment-induced deviation of a quantum system's evolution from controlled dynamics is quantified by a single numerical measure. This…

Mesoscale and Nanoscale Physics · Physics 2010-10-12 Leonid Fedichkin , Arkady Fedorov , Vladimir Privman

This paper presents a detailed analysis of uncertainty matrices (i.e. measurement covariance matrices) associated with multiple complex-valued microwave scattering S-parameter measurements. The analysis is based on forming combinations of…

Instrumentation and Detectors · Physics 2018-09-20 Nick M. Ridler , Martin J. Salter

We present a quantum information theory that allows for a consistent description of entanglement. It parallels classical (Shannon) information theory but is based entirely on density matrices (rather than probability distributions) for the…

Quantum Physics · Physics 2009-10-30 Nicolas J. Cerf , Chris Adami

Unambiguous measurements play an important role in quantum information, with applications ranging from quantum key distribution to quantum state reconstruction. Recently, such measurements have also been used in quantum algorithms based on…

Quantum Physics · Physics 2025-11-05 Quentin Buzet , André Chailloux

Quantum incompatibility, referred as the phenomenon that some quantum measurements cannot be performed simultaneously, is necessary for various quantum information processing tasks, such as nonlocality and steering. When these applications…

Quantum Physics · Physics 2024-11-19 Xiaolin Zhang , Rui Qu , Zehong Chang , Yunlong Wang , Zhenyu Guo , Min An , Hong Gao , Fuli Li , Pei Zhang

The fact that quantum mechanics predicts stronger correlations than classical physics is an essential cornerstone of quantum information processing. Indeed, these quantum correlations are a valuable resource for various tasks, such as…

We study quantum steering experiments without assuming that the trusted party can perfectly control their measurement device. Instead, we introduce a scenario in which these measurements are subject to small imprecision. We show that small…

Quantum Physics · Physics 2024-02-19 Armin Tavakoli

Symmetries are a key concept to connect mathematical elegance with physical insight. We consider measurement assemblages in quantum mechanics and show how their symmetry can be described by means of the so-called discrete bundles. It turns…

Quantum Physics · Physics 2020-03-30 H. Chau Nguyen , Sébastien Designolle , Mohamed Barakat , Otfried Gühne

Proper quantification of predictive uncertainty is essential for the use of machine learning in safety-critical applications. Various uncertainty measures have been proposed for this purpose, typically claiming superiority over other…

Machine Learning · Computer Science 2025-12-16 Paul Hofman , Yusuf Sale , Eyke Hüllermeier

Measurement incompatibility describes two or more quantum measurements whose expected joint outcome on a given system cannot be defined. This purely non-classical phenomenon provides a necessary ingredient in many quantum information tasks…

Quantum Physics · Physics 2020-04-01 Francesco Buscemi , Eric Chitambar , Wenbin Zhou

In this essay, we argue that certain aspects of the measurement require revision in Quantum Gravity. Using entropic arguments, we propose that the number of measurement outcomes and the accuracy (or the range) of the measurement are limited…

High Energy Physics - Theory · Physics 2024-08-28 Juanca Carrasco-Martinez

Measurements are essential for the processing and protection of information in quantum computers. They can also induce long-range entanglement between unmeasured qubits. However, when post-measurement states depend on many non-deterministic…

Quantum correlations exhibit behaviour that cannot be resolved with a local hidden variable picture of the world. In quantum information, they are also used as resources for information processing tasks, such as Measurement-based Quantum…

Quantum Physics · Physics 2011-02-10 Matty J. Hoban , Earl T. Campbell , Klearchos Loukopoulos , Dan E. Browne

We address the problem of uncertainty quantification and propose measures of total, aleatoric, and epistemic uncertainty based on a known decomposition of (strictly) proper scoring rules, a specific type of loss function, into a divergence…

Machine Learning · Computer Science 2025-05-29 Paul Hofman , Yusuf Sale , Eyke Hüllermeier