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The aim of this article is to establish basic results in a conditional measure theory. The results are applied to prove that arbitrary kernels and conditional distributions are represented by measures in a conditional set theory. In…

Probability · Mathematics 2018-03-21 Asgar Jamneshan , Michael Kupper , Martin Streckfuß

Three notions of complementarity - operational, probabilistic, and value complementarity - are reanalysed with respect to the question of joint measurements and compared with reference to some examples of canonically conjugate observables.…

Quantum Physics · Physics 2011-01-04 P. Busch , P. J. Lahti

In this paper, a new definition of observability is introduced for PDEs. It is a quantitative measure of partial observability. The quantity is proved to be consistent if approximated using well posed approximation schemes. A first order…

Dynamical Systems · Mathematics 2011-11-28 Wei Kang

This article introduces the concepts of multi-observables and multi-instruments in quantum mechanics. A multi-observable $A$ (multi-instrument $\mathcal{I}$) has an outcome space of the form $\Omega =\Omega _1\times\cdots\times\Omega _n$…

Quantum Physics · Physics 2023-07-24 Stan Gudder

We explore further the suggestion to describe a pre- and post-selected system by a two-state, which is determined by two conditions. Starting with a formal definition of a two-state Hilbert space and basic operations, we systematically…

Quantum Physics · Physics 2009-10-28 B. Reznik , Y. Aharonov

We ask which is the best strategy to reveal uncertainty relations between comple- mentary observables of a continuous variable system for coarse-grained measurements. This leads to the derivation of new uncertainty relations for…

Quantum Physics · Physics 2015-05-30 Lukasz Rudnicki , Stephen P. Walborn , Fabricio Toscano

Information-theoretical quantities such as statistical distinguishability typically result from optimisations over all conceivable observables. Physical theories, however, are not generally considered valid for all mathematically allowed…

Quantum Physics · Physics 2018-05-28 Cédric Bény

We present the conceptual and technical background required to describe and understand the correlations and fluctuations of the empirical density and current of steady-state diffusion processes on all time scales -- observables central to…

Statistical Mechanics · Physics 2023-04-06 Cai Dieball , Aljaž Godec

The ``generic'' family of classical sequential growth dynamics for causal sets provides cosmological models of causal sets which are a testing ground for ideas about the, as yet unknown, quantum theory. In particular we can investigate how…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Graham Brightwell , H. Fay Dowker , Raquel S. Garcia , Joe Henson , Rafael D. Sorkin

Some scenarios require the computation of a predictive distribution of a new value evaluated on an objective function conditioned on previous observations. We are interested on using a model that makes valid assumptions on the objective…

Machine Learning · Computer Science 2021-01-21 Lucia Asencio-Martín , Eduardo C. Garrido-Merchán

We show that including both the system and the apparatus in the quantum description of the measurement process, and using the concept of conditional probabilities, it is possible to deduce the statistical operator of the system after a…

Quantum Physics · Physics 2008-11-29 R. Laura , L. Vanni

This paper generalizes the notion of stochastic order to a relation between probability measures over arbitrary measurable spaces. This generalization is motivated by the observation that for the stochastic ordering of two stationary Markov…

Probability · Mathematics 2008-06-24 Lasse Leskelä

We study representations of positive definite kernels $K$ in a general setting, but with view to applications to harmonic analysis, to metric geometry, and to realizations of certain stochastic processes. Our initial results are stated for…

Functional Analysis · Mathematics 2017-06-30 Palle Jorgensen , Feng Tian

Determining the measurement uncertainty region is a difficult problem for generic sets of observables. For this reason the literature on exact measurement uncertainty regions is focused on symmetric sets of observables, where the symmetries…

Quantum Physics · Physics 2019-09-12 Oliver Reardon-Smith

Obtaining the expectation value of an observable on a quantum computer is a crucial step in the variational quantum algorithms. For complicated observables such as molecular electronic Hamiltonians, a common strategy is to present the…

Quantum Physics · Physics 2022-04-20 Tzu-Ching Yen , Aadithya Ganeshram , Artur F. Izmaylov

Consider a probability measure supported by a regular geodesic ball in a manifold. For any p larger than or equal to 1 we define a stochastic algorithm which converges almost surely to the p-mean of the measure. Assuming furthermore that…

Probability · Mathematics 2011-06-28 Marc Arnaudon , Clément Dombry , Anthony Phan , Le Yang

Classical sequential growth models for causal sets provide an important step towards the formulation of a quantum causal set dynamics. The covariant observables in a class of these models known as generalised percolation have been…

General Relativity and Quantum Cosmology · Physics 2009-11-11 Fay Dowker , Sumati Surya

Analysing Quantum Measurement requires analysing the physics of amplification since amplification of phenomena from one scale to another scale is essential to measurement. There still remains the task of working this into an axiomatic…

Quantum Physics · Physics 2007-05-23 Joseph F. Johnson

We begin with a study of operations and the effects they measure. We define the probability that an effect $a$ occurs when the system is in a state $\rho$ by $P_\rho (a)= tr(\rho a)$. If $P_\rho (a)\ne 0$ and $\mathcal{I}$ is an operation…

Quantum Physics · Physics 2024-02-07 Stanley Gudder

In molecular dynamics and sampling of high dimensional Gibbs measures coarse-graining is an important technique to reduce the dimensionality of the problem. We will study and quantify the coarse-graining error between the coarse-grained…

Analysis of PDEs · Mathematics 2020-06-04 M. H. Duong , A. Lamacz , M. A. Peletier , A. Schlichting , U. Sharma
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