Temporal Quantum Correlations and Hidden Variable Models

Nonfiction, Science & Nature, Science, Physics, Quantum Theory, Computers, Advanced Computing, Information Technology
Cover of the book Temporal Quantum Correlations and Hidden Variable Models by Costantino Budroni, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Costantino Budroni ISBN: 9783319241692
Publisher: Springer International Publishing Publication: October 22, 2015
Imprint: Springer Language: English
Author: Costantino Budroni
ISBN: 9783319241692
Publisher: Springer International Publishing
Publication: October 22, 2015
Imprint: Springer
Language: English

In this thesis, the main approach to the characterization of the set of classical probabilities, the correlation polytope approach, is reviewed for different scenarios, namely, hidden variable models discussed by Bell (local), Kochen and Specker (non-contextual), and Leggett and Garg (macrorealist). Computational difficulties associated with the method are described and a method to overcome them in several nontrivial cases is presented. For the quantum case, a general method to analyze quantum correlations in the sequential measurement scenario is provided, which allows computation of the maximal correlations.

Such a method has a direct application for computation of maximal quantum violations of Leggett-Garg inequalities and it is relevant in the analysis of non-contextuality tests. Finally, possible applications of the results for quantum information tasks are discussed.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

In this thesis, the main approach to the characterization of the set of classical probabilities, the correlation polytope approach, is reviewed for different scenarios, namely, hidden variable models discussed by Bell (local), Kochen and Specker (non-contextual), and Leggett and Garg (macrorealist). Computational difficulties associated with the method are described and a method to overcome them in several nontrivial cases is presented. For the quantum case, a general method to analyze quantum correlations in the sequential measurement scenario is provided, which allows computation of the maximal correlations.

Such a method has a direct application for computation of maximal quantum violations of Leggett-Garg inequalities and it is relevant in the analysis of non-contextuality tests. Finally, possible applications of the results for quantum information tasks are discussed.

More books from Springer International Publishing

Cover of the book Learning Technology for Education in Cloud – The Changing Face of Education by Costantino Budroni
Cover of the book At the Size Limit - Effects of Miniaturization in Insects by Costantino Budroni
Cover of the book Topology-Based Modeling of Textile Structures and Their Joint Assemblies by Costantino Budroni
Cover of the book A Forward-Backward SDEs Approach to Pricing in Carbon Markets by Costantino Budroni
Cover of the book S=EX² by Costantino Budroni
Cover of the book Consensus Building Versus Irreconcilable Conflicts by Costantino Budroni
Cover of the book Embedded Systems Design for High-Speed Data Acquisition and Control by Costantino Budroni
Cover of the book Biblical Principles of Hiring and Developing Employees by Costantino Budroni
Cover of the book Mining Intelligence and Knowledge Exploration by Costantino Budroni
Cover of the book Syphilis and Subjectivity by Costantino Budroni
Cover of the book Progress in Medical Research by Costantino Budroni
Cover of the book Computer Aided Verification by Costantino Budroni
Cover of the book Asia-Pacific Security Challenges by Costantino Budroni
Cover of the book Poststructural and Narrative Thinking in Family Therapy by Costantino Budroni
Cover of the book Mathematics of Energy and Climate Change by Costantino Budroni
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy