Vertex finding by sparse model-based clustering

17th International Workshop on Advanced Computing and Analysis Techniques in Physics Research

物理学;计算机科学

Frühwirth, R.^1 ; Eckstein, K.^1 ; Frühwirth-Schnatter, S.^2

Institute of High Energy Physics, Austrian Academy of Sciences, Vienna, Austria^1

Institute for Statistics and Mathematics, Vienna University of Economics and Business, Austria^2

关键词: Bunch crossings;    Expectation-maximization algorithms;    Gaussian mixtures;    Markov chain Monte Carlo;    Sparse modeling;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/762/1/012055/pdf
DOI  :  10.1088/1742-6596/762/1/012055

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The application of sparse model-based clustering to the problem of primary vertex finding is discussed. The observed z-positions of the charged primary tracks in a bunch crossing are modeled by a Gaussian mixture. The mixture parameters are estimated via Markov Chain Monte Carlo (MCMC). Sparsity is achieved by an appropriate prior on the mixture weights. The results are shown and compared to clustering by the expectation-maximization (EM) algorithm.