Exploring inequality violations by classical hidden variables numerically
نویسندگان
چکیده
منابع مشابه
Inequality Constraints in Causal Models with Hidden Variables
We present a class of inequality constraints on the set of distributions induced by local interventions on variables governed by a causal Bayesian network, in which some of the variables remain unmeasured. We derive bounds on causal effects that are not directly measured in randomized experiments. We derive instrumental inequality type of constraints on nonexperimental distributions. The result...
متن کاملNumerically Stable Hidden Markov Model Implementation
Application of Hidden Markov Models to long observation sequences entails the computation of extremely small probabilities. These probabilities introduce numerical instability in the computations used to determine the probability of an observed sequence given a model, the most likely sequence of states, and the maximum likelihood model updates given an observation sequence. This paper explains ...
متن کاملRange of Violations of Bell’s Inequality by Entangled Photon Pairs
Quantum entanglement is a key formal feature common to many of the well-known conceptual conundrums that arise in quantum mechanics including the famous paradoxes of Einstein, Podolsky, and Rosen (EPR) [1] and Schrödinger’s cat [2]. The latter is a particularly graphic illustration of the well-known measurement problem. Quantum entanglement (EPR-correlations) typically occurs when two or more q...
متن کاملHidden Variables or Hidden Theories?
We show that a modified Relativity Principle could explain in a " classical " way the strange correlations of entangled photons. We propose a gedanken experiment with balls and boxes that predicts the same distribution of probability of the Quantum Mechanics in the case of the EPR experiment with a pair of entangled photons meeting a pair of polarizers. In the light of this gedanken experiment,...
متن کاملLearning with hidden variables
Learning and inferring features that generate sensory input is a task continuously performed by cortex. In recent years, novel algorithms and learning rules have been proposed that allow neural network models to learn such features from natural images, written text, audio signals, etc. These networks usually involve deep architectures with many layers of hidden neurons. Here we review recent ad...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Annals of Physics
سال: 2013
ISSN: 0003-4916
DOI: 10.1016/j.aop.2013.08.011