SFitter：根据LHC数据重建MSSM拉格朗日量
SFitter: Reconstructing the MSSM Lagrangian from LHC data
摘要：
一旦在大型强子对撞机上发现了超对称性，问题就出现了，拉格朗日量的基本参数是什么。因此，对这个问题的回答不应受到大尺度模型假设的影响。SFitter是专为此任务设计的工具。以LHC（可能ILC）数据作为输入，它使用新的加权马尔可夫链技术扫描TeV尺度MSSM参数空间。使用该扫描，它确定最佳拟合参数点的列表。此外，计算对数似然图，其可以被减少到低维的Frequentist的简档似然或贝叶斯概率图。
英文摘要：
Once supersymmetry is found at the LHC, the question arises what are the fundamental parameters of the Lagrangian. The answer to this question should thereby not be biased by assumptions on high-scale models. SFitter is a tool designed for this task. Taking LHC (and possibly ILC) data as input it scans the TeV-scale MSSM parameter space using its new weighted Markov chain technique. Using this scan it determines a list of best-fitting parameter points. Additionally a log-likelihood map is calculated, which can be reduced to lower-dimensional Frequentist's profile likelihoods or Bayesian probability maps.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
