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
amplitudes.