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Evaluating probabilistic programming languages for simulating quantum correlations

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  • Abdul Karim Obeid
  • Peter D Bruza
  • Peter Wittek

Abstract

This article explores how probabilistic programming can be used to simulate quantum correlations in an EPR experimental setting. Probabilistic programs are based on standard probability which cannot produce quantum correlations. In order to address this limitation, a hypergraph formalism was programmed which both expresses the measurement contexts of the EPR experimental design as well as associated constraints. Four contemporary open source probabilistic programming frameworks were used to simulate an EPR experiment in order to shed light on their relative effectiveness from both qualitative and quantitative dimensions. We found that all four probabilistic languages successfully simulated quantum correlations. Detailed analysis revealed that no language was clearly superior across all dimensions, however, the comparison does highlight aspects that can be considered when using probabilistic programs to simulate experiments in quantum physics.

Suggested Citation

  • Abdul Karim Obeid & Peter D Bruza & Peter Wittek, 2019. "Evaluating probabilistic programming languages for simulating quantum correlations," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-37, January.
    • Handle: RePEc:plo:pone00:0208555
    DOI: 10.1371/journal.pone.0208555
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    References listed on IDEAS

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    1. Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
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