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Title: Using Boosted Decision Trees to Separate Signal and Background in B to XsGamma Decays

Abstract

The measurement of the branching fraction of the flavor changing neutral current B {yields} X{sub s}{gamma} transition can be used to expose physics outside the Standard Model. In order to make a precise measurement of this inclusive branching fraction, it is necessary to be able to effectively separate signal and background in the data. In order to achieve better separation, an algorithm based on Boosted Decision Trees (BDTs) is implemented. Using Monte Carlo simulated events, ''forests'' of trees were trained and tested with different sets of parameters. This parameter space was studied with the goal of maximizing the figure of merit, Q, the measure of separation quality used in this analysis. It is found that the use of 1000 trees, with 100 values tested for each variable at each node, and 50 events required for a node to continue separating give the highest figure of merit, Q = 18.37.

Authors:
Publication Date:
Research Org.:
SLAC National Accelerator Lab., Menlo Park, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
892609
Report Number(s):
SLAC-TN-06-015
TRN: US0605903
DOE Contract Number:  
AC02-76SF00515
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; ALGORITHMS; FORESTS; NEUTRAL CURRENTS; PERFORMANCE; PHYSICS; STANDARD MODEL; TREES; Experiment-HEP,OTHER

Citation Formats

Barber, James, and /Massachusetts U., Amherst /SLAC. Using Boosted Decision Trees to Separate Signal and Background in B to XsGamma Decays. United States: N. p., 2006. Web. doi:10.2172/892609.
Barber, James, & /Massachusetts U., Amherst /SLAC. Using Boosted Decision Trees to Separate Signal and Background in B to XsGamma Decays. United States. https://doi.org/10.2172/892609
Barber, James, and /Massachusetts U., Amherst /SLAC. 2006. "Using Boosted Decision Trees to Separate Signal and Background in B to XsGamma Decays". United States. https://doi.org/10.2172/892609. https://www.osti.gov/servlets/purl/892609.
@article{osti_892609,
title = {Using Boosted Decision Trees to Separate Signal and Background in B to XsGamma Decays},
author = {Barber, James and /Massachusetts U., Amherst /SLAC},
abstractNote = {The measurement of the branching fraction of the flavor changing neutral current B {yields} X{sub s}{gamma} transition can be used to expose physics outside the Standard Model. In order to make a precise measurement of this inclusive branching fraction, it is necessary to be able to effectively separate signal and background in the data. In order to achieve better separation, an algorithm based on Boosted Decision Trees (BDTs) is implemented. Using Monte Carlo simulated events, ''forests'' of trees were trained and tested with different sets of parameters. This parameter space was studied with the goal of maximizing the figure of merit, Q, the measure of separation quality used in this analysis. It is found that the use of 1000 trees, with 100 values tested for each variable at each node, and 50 events required for a node to continue separating give the highest figure of merit, Q = 18.37.},
doi = {10.2172/892609},
url = {https://www.osti.gov/biblio/892609}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Sep 27 00:00:00 EDT 2006},
month = {Wed Sep 27 00:00:00 EDT 2006}
}