Likelihood equations and scattering amplitudes

B. Sturmfels, Simon Telen
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引用次数: 30

Abstract

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.
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似然方程和散射振幅
我们将粒子物理中的散射振幅与代数统计中离散模型的最大似然估计联系起来。散射势的作用是对数似然函数,其临界点是有理函数方程的解。我们研究了统计学中低秩张量模型的ML度,并回顾了Arkani-Hamed, Cachazo及其合作者提出的物理理论。数值代数几何的最新进展被用于计算和证明临界点。我们还讨论了正模型以及如何计算它们的弦振幅。
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Journal of Algebraic Statistics
Journal of Algebraic Statistics STATISTICS & PROBABILITY-
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