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This study shows probabilistic programming can simulate quantum correlations in EPR experiments. While standard probability falls short, a hypergraph formalism enabled four frameworks to successfully model these quantum phenomena.

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Area of Science:

  • Quantum Physics
  • Computer Science
  • Computational Probability

Background:

  • Standard probabilistic programming struggles to model quantum correlations.
  • Quantum entanglement and the EPR paradox present unique simulation challenges.
  • Hypergraph formalisms offer a way to represent complex experimental constraints.

Purpose of the Study:

  • To investigate the efficacy of probabilistic programming languages in simulating quantum correlations.
  • To evaluate contemporary open-source probabilistic programming frameworks for quantum physics simulations.
  • To compare the qualitative and quantitative performance of different frameworks in modeling EPR experiments.

Main Methods:

  • Utilized a hypergraph formalism to define measurement contexts and constraints for EPR experiments.
  • Employed four open-source probabilistic programming frameworks for simulation.
  • Conducted both qualitative and quantitative analyses of the simulation results.

Main Results:

  • All four probabilistic programming languages successfully simulated quantum correlations in the EPR experiment.
  • No single framework demonstrated clear superiority across all evaluation dimensions.
  • The study identified key aspects for consideration when selecting probabilistic programs for quantum simulations.

Conclusions:

  • Probabilistic programming, augmented with formalisms like hypergraphs, is a viable tool for simulating quantum correlations.
  • Framework selection for quantum physics simulations depends on specific experimental needs and desired performance metrics.
  • Further research can refine these tools for more complex quantum system modeling.