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Related papers: A Local Mathematical Model for EPR-Experiments

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The extended semantic realism (ESR) model recently worked out by one of the authors embodies the mathematical formalism of standard (Hilbert space) quantum mechanics in a noncontextual framework, reinterpreting quantum probabilities as…

Quantum Physics · Physics 2014-11-13 Sandro Sozzo , Claudio Garola

A simulation is useful when the phenomenon of interest is either expensive to regenerate or irreproducible with the same context. Recently, Bayesian inference on the distribution of the simulation input parameter has been implemented…

Machine Learning · Computer Science 2022-11-07 Dongjun Kim , Kyungwoo Song , Seungjae Shin , Wanmo Kang , Il-Chul Moon , Weonyoung Joo

This article is based on lecture notes for the Marie Curie Training school "Initial Training on Numerical Methods for Active Matter". It provides an introductory overview of modeling approaches for active matter and is primarily targeted at…

Soft Condensed Matter · Physics 2021-02-26 L. Hecht , J. C. Ureña , B. Liebchen

The article presents new results on the Propagation-Separation Approach by Polzehl and Spokoiny [2006]. This iterative procedure provides a unified approach for nonparametric estimation, sup- posing a local parametric model. The adaptivity…

Methodology · Statistics 2013-12-03 Saskia Becker

The polarizable embedding (PE) model is a fragment-based quantum-classical approach aimed at accurate inclusion of environment effects in quantum-mechanical response property calculations. The aim of this tutorial is to give insight into…

Binary regression models represent a popular model-based approach for binary classification. In the Bayesian framework, computational challenges in the form of the posterior distribution motivate still-ongoing fruitful research. Here, we…

Computation · Statistics 2023-09-06 Augusto Fasano , Niccolò Anceschi , Beatrice Franzolini , Giovanni Rebaudo

In this paper we prove a nonlocal version of the Cordes-Niremberg estimates. We use it to extend our previous regularity results for fully nonlinear integro-differential equations to the variable coefficient case and several other settings…

Analysis of PDEs · Mathematics 2010-03-31 Luis Caffarelli , Luis Silvestre

We demonstrate that the EPR-Bohm probabilities can be easily obtained in the classical (but contextual) probabilistic framework by using the formula of interference of probabilities. From this point of view the EPR-Bell experiment is just…

Quantum Physics · Physics 2007-05-23 Andrei Khrennikov

The main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell-Lorentz electromagnetics and discuss its immediate analytical and numerical…

Generalized models provide a framework for the study of evolution equations without specifying all functional forms. The generalized formulation of problems has been shown to facilitate the analytical investigation of local dynamics and has…

Dynamical Systems · Mathematics 2014-06-24 Christian Kuehn , Stefan Siegmund , Thilo Gross

We provide a simplified form of Primal Augmented Lagrange Multiplier algorithm. We intend to fill the gap in the steps involved in the mathematical derivations of the algorithm so that an insight into the algorithm is made. The experiment…

Numerical Analysis · Computer Science 2014-01-02 B. Premjith , S. Sachin Kumar , Akhil Manikkoth , T V Bijeesh , K P Soman

Large-scale randomized experiments, sometimes called A/B tests, are increasingly prevalent in many industries. Though such experiments are often analyzed via frequentist $t$-tests, arguably such analyses are deficient: $p$-values are hard…

Methodology · Statistics 2020-03-27 F. Richard Guo , James McQueen , Thomas S. Richardson

The paper argues that a causal explanation of the correlated outcomes of EPR-type experiments is desirable and possible. It shows how Bohmian mechanics and the GRW mass density theory offer such an explanation in terms of a non-local common…

Quantum Physics · Physics 2013-12-11 Matthias Egg , Michael Esfeld

Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…

Machine Learning · Computer Science 2013-01-30 Luis E. Ortiz , Leslie Pack Kaelbling

Traditionally, mathematical knowledge is published in printed media such as books or journals. With the advent of the Internet, a new method of publication became available. To date, however, most online mathematical publications do not…

History and Overview · Mathematics 2011-03-01 Markus J. Pflaum , John Tuley

This article is geared towards theorists interested in estimating parameters of their theoretical models, and computing their own limits using available experimental data and elementary Mathematica code. The examples given can be useful…

High Energy Physics - Phenomenology · Physics 2011-10-25 Georgios Choudalakis

We illustrate the experimental, empirical, approach to mathematics (that contrary to popular belief, is often rigorous), by using parking functions and their "area" statistic, as a case study. Our methods are purely finitistic and…

Combinatorics · Mathematics 2018-06-08 Yukun Yao , Doron Zeilberger

A brief review of the Standard Model of particle physics is presented.

High Energy Physics - Phenomenology · Physics 2007-05-23 P. Aurenche

This paper proposes an algorithm for computing regularized solutions to linear rational expectations models. The algorithm allows for regularization cross-sectionally as well as across frequencies. A variety of numerical examples illustrate…

Econometrics · Economics 2020-10-28 Majid M. Al-Sadoon

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically…