
arXiv: 2012.05041
handle: 21.11116/0000-000A-8A61-D
We relate scattering amplitudes in particle physics to maximum likelihood estimation for discrete models in algebraic statistics. The scattering potential plays the role of the log-likelihood function, and its critical points are solutions to rational function equations. We study the ML degree of low-rank tensor models in statistics, and we revisit physical theories proposed by Arkani-Hamed, Cachazo and their collaborators. Recent advances in numerical algebraic geometry are employed to compute and certify critical points. We also discuss positive models and how to compute their string amplitudes.
18 pages
High Energy Physics - Theory, FOS: Physical sciences, Mathematics - Statistics Theory, Statistics Theory (math.ST), Algebraic statistics, scattering amplitudes, Mathematics - Algebraic Geometry, High Energy Physics - Theory (hep-th), Numerical algebraic geometry, likelihood equations, FOS: Mathematics, numerical nonlinear algebra, Algebraic Geometry (math.AG)
High Energy Physics - Theory, FOS: Physical sciences, Mathematics - Statistics Theory, Statistics Theory (math.ST), Algebraic statistics, scattering amplitudes, Mathematics - Algebraic Geometry, High Energy Physics - Theory (hep-th), Numerical algebraic geometry, likelihood equations, FOS: Mathematics, numerical nonlinear algebra, Algebraic Geometry (math.AG)
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