2018/10/31 by Stefano Bacchi, Bacchi, Stefano, Luca Curcuraci +3
Computer Science · Mathematics · Physics and Astronomy · #Data Analysis #FOS: Physical sciences #Quantum Information and Cryptography #Quantum Mechanics and Applications #Quantum Physics (quant-ph) #Statistics and Probability (physics.data-an) #advanced mathematical theories
paper · pdf · doi:10.48550/arxiv.1810.13443
openalex publication_date 2018/10/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We revise contextual probability theory and the associated inverse Born problem, solved by the Quantum-Like Representation Algorithm (QLRA) in case of two discrete random variables. After pointing out the special feature and limitations of QLRA for two binary random variables, we generalize the QLRA procedure to solve the inverse Born problem to the case of three binary random variables. We analyze the quantum spin model in the light of our results and showed that can be easily obtained from a contextual probability model. We furthermore study the inverse Born problem in the case of two continuous random variables, exploiting the general idea underlying QLRA.