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Title: OPTIMASS: A package for the minimization of kinematic mass functions with constraints

Abstract

Reconstructed mass variables, such as M2, M2C, M*T, and MT2 W, play an essential role in searches for new physics at hadron colliders. The calculation of these variables generally involves constrained minimization in a large parameter space, which is numerically challenging. We provide a C++ code, Optimass, which interfaces with the Minuit library to perform this constrained minimization using the Augmented Lagrangian Method. The code can be applied to arbitrarily general event topologies, thus allowing the user to significantly extend the existing set of kinematic variables. Here, we describe this code, explain its physics motivation, and demonstrate its use in the analysis of the fully leptonic decay of pair-produced top quarks using M2 variables.

Authors:
 [1];  [2];  [2];  [3];  [2];  [4];  [4];  [5]
  1. Institute for Basic Science (IBS), Daejeon (Korea)
  2. Univ. of Florida, Gainesville, FL (United States)
  3. Institute for Basic Science (IBS), Daejeon (Korea); Korea Advanced Institute of Science and Technology, Daejeon (Korea)
  4. European Organization for Nuclear Research (CERN), Geneva (Switzerland)
  5. Asia Pacific Center for Theoretical Physics, Pohang (Korea); Postech, Pohang (Korea); The Univ. of Tokyo, Chiba (Japan)
Publication Date:
Research Org.:
Univ. of Florida, Gainesville, FL (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1327323
Grant/Contract Number:  
SC0010296
Resource Type:
Accepted Manuscript
Journal Name:
Journal of High Energy Physics (Online)
Additional Journal Information:
Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2016; Journal Issue: 1; Journal ID: ISSN 1029-8479
Publisher:
Springer Berlin
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; supersymmetry; Hadron-Hadron scattering; Beyond Standard Model; top quark; particle and resonance production

Citation Formats

Cho, Won Sang, Gainer, James S., Kim, Doojin, Lim, Sung Hak, Matchev, Konstantin T., Moortgat, Filip, Pape, Luc, and Park, Myeonghun. OPTIMASS: A package for the minimization of kinematic mass functions with constraints. United States: N. p., 2016. Web. https://doi.org/10.1007/JHEP01(2016)026.
Cho, Won Sang, Gainer, James S., Kim, Doojin, Lim, Sung Hak, Matchev, Konstantin T., Moortgat, Filip, Pape, Luc, & Park, Myeonghun. OPTIMASS: A package for the minimization of kinematic mass functions with constraints. United States. https://doi.org/10.1007/JHEP01(2016)026
Cho, Won Sang, Gainer, James S., Kim, Doojin, Lim, Sung Hak, Matchev, Konstantin T., Moortgat, Filip, Pape, Luc, and Park, Myeonghun. Thu . "OPTIMASS: A package for the minimization of kinematic mass functions with constraints". United States. https://doi.org/10.1007/JHEP01(2016)026. https://www.osti.gov/servlets/purl/1327323.
@article{osti_1327323,
title = {OPTIMASS: A package for the minimization of kinematic mass functions with constraints},
author = {Cho, Won Sang and Gainer, James S. and Kim, Doojin and Lim, Sung Hak and Matchev, Konstantin T. and Moortgat, Filip and Pape, Luc and Park, Myeonghun},
abstractNote = {Reconstructed mass variables, such as M2, M2C, M*T, and MT2 W, play an essential role in searches for new physics at hadron colliders. The calculation of these variables generally involves constrained minimization in a large parameter space, which is numerically challenging. We provide a C++ code, Optimass, which interfaces with the Minuit library to perform this constrained minimization using the Augmented Lagrangian Method. The code can be applied to arbitrarily general event topologies, thus allowing the user to significantly extend the existing set of kinematic variables. Here, we describe this code, explain its physics motivation, and demonstrate its use in the analysis of the fully leptonic decay of pair-produced top quarks using M2 variables.},
doi = {10.1007/JHEP01(2016)026},
journal = {Journal of High Energy Physics (Online)},
number = 1,
volume = 2016,
place = {United States},
year = {2016},
month = {1}
}

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