We introduce an efficient framework for computing the distance between collider events using the tools of Linearized Optimal Transport (LOT). This preserves many of the advantages of the recently-introduced Energy Mover's Distance, which quantifies the "work" required to rearrange one event into another, while significantly reducing the computational cost. It also furnishes a Euclidean embedding amenable to simple machine learning algorithms and visualization techniques, which we demonstrate in a variety of jet tagging examples. The LOT approximation lowers the threshold for diverse applications of the theory of optimal transport to collider physics.
Correlation functions of net-proton multiplicity distributions in Au + Au collisions at energies available at the BNL Relativistic Heavy Ion Collider from a multiphase transport model
Mass-dependent transport of hadron species from soft to hard (nonjet to jet) spectrum components within small collision systems at the large hadron collider
在以前的分析中，我们发展了一个两组分（软+硬）模型（TCM），用于计算5 TeV $p$ -Pb和13 TeV $p$ - $p$碰撞的识别强子（PID）谱。光谱数据通常在其统计不确定性范围内描述。模型中的系数$z_{si}(n_s)$和$z_{hi}(n_s)$表示强子种$i$在总软$\bar ρ_s$和硬$\bar ρ_h$电荷密度中的分数，并且随事件指数$n_s = Δη\bar ρ_s$显著变化。这封信报告说，这些系数的变化与$n_s$意味着运输的强子物种从软组分到硬组分，越来越多的喷流生产，而保存的总粒子数为每个物种的统计模型预测。输运的程度与强子质量成正比。
Thermodynamic and Transport Properties of Matter Formed in $pp$, $p$-Pb, Xe-Xe and Pb-Pb Collisions at the Large Hadron Collider using Color String Percolation Model
Photon and dilepton production at the Facility for Antiproton and Ion Research and the beam energy scan program at the Relativistic Heavy-Ion Collider using coarse-grained microscopic transport simulations
Characterizing nuclear modification effects in high-energy O-O collisions at energies available at the CERN Large Hadron Collider: A transport model perspective
