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In this work we introduce the randomness which is truly quantum mechanical in nature arising as an act of measurement. For a composite classical system we have the joint entropy to quantify the randomness present in the total system and…

Quantum Physics · Physics 2018-05-25 Indranil Chakrabarty , Abhishek Deshpande , Sourav Chatterjee

Weighted Updating generalizes Bayesian updating, allowing for biased beliefs by weighting the likelihood function and prior distribution with positive real exponents. I provide a rigorous foundation for the model by showing that…

Probability · Mathematics 2016-02-09 Jesse Aaron Zinn

Ultimately, any explanation of quantum measurement must be extendable to relativistic quantum mechanics (RQM), since many precisely confirmed experimental results follow from quantum field theory (QFT), which is based on RQM. Certainly, the…

Quantum Physics · Physics 2025-04-08 Ed Seidewitz

The conventional postulate for the probabilistic interpretation of quantum mechanics is asymmetric in preparation and measurement, making retrodiction reliant on inference by use of Bayes' theorem. Here, a more fundamental symmetric…

Quantum Physics · Physics 2009-11-07 David T. Pegg , Stephen M. Barnett , John Jeffers

Quantum mechanics and information theory are among the most important scientific discoveries of the last century. Although these two areas initially developed separately it has emerged that they are in fact intimately related. In this…

Quantum Physics · Physics 2009-11-07 V. Vedral

Majorization uncertainty relations are derived for arbitrary quantum operations acting on a finite-dimensional space. The basic idea is to consider submatrices of block matrices comprised of the corresponding Kraus operators. This is an…

Quantum Physics · Physics 2016-08-02 Alexey E. Rastegin , Karol Życzkowski

The entropic uncertainty principle as outlined by Maassen and Uffink for a pair of non-degenerate observables in a finite level qusystem is generalized here to the case of a pair of arbitrary quantum measurements. In particular, our result…

Quantum Physics · Physics 2007-05-23 M Krishna , K R Parthasarathy

The quantification of aleatoric and epistemic uncertainty in terms of conditional entropy and mutual information, respectively, has recently become quite common in machine learning. While the properties of these measures, which are rooted…

Machine Learning · Computer Science 2023-06-27 Lisa Wimmer , Yusuf Sale , Paul Hofman , Bern Bischl , Eyke Hüllermeier

Uncertainty relation usually is one of the most important features in quantum mechanics, and is the backbone of quantum theory, which distinguishes from the rule in classical counterpart. Specifically, entropy-based uncertainty relations…

Quantum Physics · Physics 2020-03-05 Zhi-Yong Ding , Huan Yang , Dong Wang , Hao Yuan , Jie Yang , Liu Ye

Quantum measurements are not deterministic. For this reason quantum measurements are repeated for a number of shots on identically prepared systems. The uncertainty in each measurement depends on the number of shots and the expected outcome…

Quantum Physics · Physics 2025-03-12 Pieter Thijs Eendebak

What is information? Is it physical? We argue that in a Bayesian theory the notion of information must be defined in terms of its effects on the beliefs of rational agents. Information is whatever constrains rational beliefs and therefore…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

These lectures deal with the problem of inductive inference, that is, the problem of reasoning under conditions of incomplete information. Is there a general method for handling uncertainty? Or, at least, are there rules that could in…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Ariel Caticha

We revisit the maximum-entropy inference of the state of a finite-level quantum system under linear constraints. The constraints are specified by the expected values of a set of fixed observables. We point out the existence of…

Quantum Physics · Physics 2016-05-17 Stephan Weis

Analytic continuation of numerical data obtained in imaginary time or frequency has become an essential part of many branches of quantum computational physics. It is, however, an ill-conditioned procedure and thus a hard numerical problem.…

Strongly Correlated Electrons · Physics 2016-08-18 Dominic Bergeron , A. -M. S. Tremblay

We develop a quantum version of the probability estimation framework [arXiv:1709.06159] for randomness generation with quantum side information. We show that most of the properties of probability estimation hold for quantum probability…

Quantum Physics · Physics 2023-02-06 Emanuel Knill , Yanbao Zhang , Honghao Fu

Various noise models have been developed in quantum computing study to describe the propagation and effect of the noise which is caused by imperfect implementation of hardware. Identifying parameters such as gate and readout error rates are…

Quantum Physics · Physics 2022-11-08 Muqing Zheng , Ang Li , Tamás Terlaky , Xiu Yang

Measurement is a fundamental notion in the usual approximate quantum mechanics of measured subsystems. Probabilities are predicted for the outcomes of measurements. State vectors evolve unitarily in between measurements and by reduction of…

General Relativity and Quantum Cosmology · Physics 2014-01-14 James B. Hartle

We introduce quantum correlations measures based on the minimal change in unified entropies induced by local rank-one projective measurements, divided by a factor that depends on the generalized purity of the system in the case of…

Quantum Physics · Physics 2016-08-03 G. M. Bosyk , G. Bellomo , S. Zozor , M. Portesi , P. W. Lamberti

We use the method of Maximum (relative) Entropy to process information in the form of observed data and moment constraints. The generic "canonical" form of the posterior distribution for the problem of simultaneous updating with data and…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Adom Giffin , Ariel Caticha

A Bayesian approach is developed to determine quantum mechanical potentials from empirical data. Bayesian methods, combining empirical measurements and "a priori" information, provide flexible tools for such empirical learning problems. The…

Quantum Physics · Physics 2009-11-06 J. C. Lemm , J. Uhlig