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Title: Optimizing event selection with the random grid search

Abstract

In this paper, the random grid search (RGS) is a simple, but efficient, stochastic algorithm to find optimal cuts that was developed in the context of the search for the top quark at Fermilab in the mid-1990s. The algorithm, and associated code, have been enhanced recently with the introduction of two new cut types, one of which has been successfully used in searches for supersymmetry at the Large Hadron Collider. The RGS optimization algorithm is described along with the recent developments, which are illustrated with two examples from particle physics. One explores the optimization of the selection of vector boson fusion events in the four-lepton decay mode of the Higgs boson and the other optimizes SUSY searches using boosted objects and the razor variables.

Authors:
 [1];  [2]; ORCiD logo [3];  [4]
  1. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  2. Florida State Univ., Tallahassee, FL (United States)
  3. Kyungpook National Univ., Daegu (South Korea)
  4. Broad Institute, Boston, MA (United States)
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP)
OSTI Identifier:
1374711
Alternate Identifier(s):
OSTI ID: 1548656
Report Number(s):
FERMILAB-PUB-17-288-PPD; arXiv:1706.09907
Journal ID: ISSN 0010-4655; 1608169
Grant/Contract Number:  
AC02-07CH11359; SC0010102
Resource Type:
Accepted Manuscript
Journal Name:
Computer Physics Communications
Additional Journal Information:
Journal Volume: 228; Journal Issue: C; Journal ID: ISSN 0010-4655
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; Selection optimization; Grid search; LHC; Higgs; SUSY

Citation Formats

Bhat, Pushpalatha C., Prosper, Harrison B., Sekmen, Sezen, and Stewart, Chip. Optimizing event selection with the random grid search. United States: N. p., 2018. Web. doi:10.1016/j.cpc.2018.02.018.
Bhat, Pushpalatha C., Prosper, Harrison B., Sekmen, Sezen, & Stewart, Chip. Optimizing event selection with the random grid search. United States. https://doi.org/10.1016/j.cpc.2018.02.018
Bhat, Pushpalatha C., Prosper, Harrison B., Sekmen, Sezen, and Stewart, Chip. Tue . "Optimizing event selection with the random grid search". United States. https://doi.org/10.1016/j.cpc.2018.02.018. https://www.osti.gov/servlets/purl/1374711.
@article{osti_1374711,
title = {Optimizing event selection with the random grid search},
author = {Bhat, Pushpalatha C. and Prosper, Harrison B. and Sekmen, Sezen and Stewart, Chip},
abstractNote = {In this paper, the random grid search (RGS) is a simple, but efficient, stochastic algorithm to find optimal cuts that was developed in the context of the search for the top quark at Fermilab in the mid-1990s. The algorithm, and associated code, have been enhanced recently with the introduction of two new cut types, one of which has been successfully used in searches for supersymmetry at the Large Hadron Collider. The RGS optimization algorithm is described along with the recent developments, which are illustrated with two examples from particle physics. One explores the optimization of the selection of vector boson fusion events in the four-lepton decay mode of the Higgs boson and the other optimizes SUSY searches using boosted objects and the razor variables.},
doi = {10.1016/j.cpc.2018.02.018},
journal = {Computer Physics Communications},
number = C,
volume = 228,
place = {United States},
year = {2018},
month = {2}
}

Journal Article:

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Cited by: 1 work
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Figures / Tables:

FIG. 1 FIG. 1: A regular grid search (left) versus a random grid search (right) in a 2-dimensional space de ned by the discriminating variables $x$ and $y$. The triangles represent the signal events, the circles represent the background events and the lines show the values of $x$ and $y$ where themore » cuts are applied [27]. Geometrically, a cut-point is the intersection of the lines.« less

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