Due to the large and continuously growing number of experimental analyses available, users may quickly find themselves in the situation that the study they are particularly interested in has not (yet) been implemented officially into the Checkmate framework. However, the code includes a rather simple framework to allow users to add new analyses on their own. This document serves as a guide to this.
In addition, Checkmate serves as a powerful tool for testing and implementing new search strategies. To aid this process, many tools are included to allow a rapid prototyping of new analyses.
Website: ype="url" data-locatorKey="http://checkmate.hepforge.org/">http://checkmate.hepforge.org/
Program title: CheckMATE, AnalysisManager
Catalogue identifier: AEUT_v1_1
Program summary URL:ype="url" data-locatorKey="http://cpc.cs.qub.ac.uk/summaries/AEUT_v1_1.html">http://cpc.cs.qub.ac.uk/summaries/AEUT_v1_1.html
Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland
Licensing provisions: Standard CPC licence, ype="url" data-locatorKey="http://cpc.cs.qub.ac.uk/licence/licence.html">http://cpc.cs.qub.ac.uk/licence/licence.html
No. of lines in distributed program, including test data, etc.: 181436
No. of bytes in distributed program, including test data, etc.: 2169369
Distribution format: tar.gz
Programming language: C++, Python.
Computer: PC, Mac.
Operating system: Linux, Mac OS.
Catalogue identifier of previous version: AEUT_v1_0
Journal reference of previous version: Comput. Phys. Comm. 187(2015)227
Classification: 11.9.
External routines: ROOT, Python, Delphes (included with the distribution)
Does the new version supersede the previous version?: Yes
Nature of problem: The LHC has delivered a wealth of new data that is now being analysed. Both ATLAS and CMS have performed many searches for new physics that theorists are eager to test their model against. However, tuning the detector simulations, understanding the particular analysis details and interpreting the results can be a tedious and repetitive task. Furthermore, new analyses are being constantly published by the experiments and might be not yet included in the official CheckMATE distribution.
Solution method: The AnalysisManager within CheckMATE framework allows the user to easily include new experimental analyses as they are published by the collaborations. Furthermore, completely novel analyses can be designed and added by the user in order to test models at higher centre-of-mass energy and/or luminosity.
Reasons for new version: New features, bug fixes, additional validated analyses.
Summary of revisions: New kinematic variables M_CT, M_T2bl, m_T, alpha_T, razor; internal likelihood calculation; missing energy smearing; efficiency tables; validated tau-tagging; improved AnalysisManager and code structure; new analyses; bug fixes.
Restrictions: Only a subset of available experimental results have been implemented.
Additional comments: Checkmate is built upon the tools and hard work of many people. If Checkmate is used in your publication it is extremely important that all of the following citations are included,
Delphes 3 [1].
FastJet [2,3].
Anti-kt jet algorithm [4].
CLs prescription [5].
In analyses that use the MT2 kinematical discriminant we use the Oxbridge Kinetics Library [6,7] and the algorithm developed by Cheng and Han [8] which also includes the MT2bl variable [9].
In analyses that use the MCT family of kinematical discriminants we use MctLib [10,11] which also includes the MCT⊥ and MCTII variables [12].
All experimental analyses that were used to set limits in the study.
The Monte Carlo event generator that was used.
References:
J. de Favereau, C. Delaere, P Demin, A. Giammanco, V. Lematre, et al., “DELPHES 3, A modular framework for fast simulation of a generic collider experiment”, 2013.
M. Cacciari, G. P Salam, and G. Soyez, “FastJet User Manual”, Eur. Phys. J., vol. C72, p. 1896, 2012.
M. Cacciari and G. P Salam, ”Dispelling the N3 myth for the kt jet-finder”, Phys. Lett., vol. B641, pp. 57–61, 2006.
M. Cacciari, G. P Salam, and G. Soyez, “The Anti-k(t) jet clustering algorithm”, JHEP, vol. 0804, p. 063, 2008.
A. L. Read, “Presentation of search results: the cl’s technique”, Journal of Physics G: Nuclear and Particle Physics, vol. 28, no. 10, p. 2693, 2002.
C. Lester and D. Summers, “Measuring masses of semiinvisibly decaying particles pair produced at hadron colliders”, Phys. Lett., vol. B463, pp. 99–103, 1999.
A. Barr, C. Lester, and P Stephens, “m(T2): The Truth behind the glamour”, J. Phys., vol. G29, pp. 2343–2363, 2003.
H.-C. Cheng and Z. Han, “Minimal Kinematic Constraints and m(T2)”, JHEP, vol. 0812, p. 063, 2008.
Y. Bai, H.-C. Cheng, J. Gallicchio, and J. Gu, “Stop the Top Background of the Stop Search”, JHEP, vol. 1207, p. 110, 2012.
D. R. Tovey, “On measuring the masses of pair-produced semi-invisibly decaying particles at hadron colliders”, JHEP, vol. 0804, p. 034, 2008.
G. Polesello and D. R. Tovey, “Supersymmetric particle mass measurement with the boost-corrected contransverse mass”, JHEP, vol. 1003, p. 030, 2010.
K. T. Matchev and M. Park, “A General method for determining the masses of semi-invisibly decaying particles at hadron colliders”, Phys. Rev. Lett., vol. 107, p. 061801, 2011.