Even though the environment at future e+e- colliders is practically QCD background free, there is a large number of processes with high cross-sections and/or similar topology as the Higgs signal of interest. Maximization of the achievable precision of measurements in the Higgs sector and beyond calls for optimized event selection with respect to the statistical significance. This is where the Multivariate Analysis (MVA) is employed, separating the signal from numerous backgrounds on the basis of their kinematic and other properties. In this paper, we discuss the basics of MVA, its application and performance, in examples of several Higgs analyses done in our group using full simulation of the CLIC data.
TY - CONF
AU - Vidaković, Ivana
AU - Radulović, Mirko
AU - Stevanović, Jasna
AU - Kačarević, Goran
PY - 2023
UR - https://vinar.vin.bg.ac.rs/handle/123456789/11937
AB - Even though the environment at future e+e- colliders is practically QCD background free, there is a large number of processes with high cross-sections and/or similar topology as the Higgs signal of interest. Maximization of the achievable precision of measurements in the Higgs sector and beyond calls for optimized event selection with respect to the statistical significance. This is where the Multivariate Analysis (MVA) is employed, separating the signal from numerous backgrounds on the basis of their kinematic and other properties. In this paper, we discuss the basics of MVA, its application and performance, in examples of several Higgs analyses done in our group using full simulation of the CLIC data.
C3 - Proceedings of Science
T1 - Application of Multivariate Analysis in Separation of Higgs Boson Signal at future e+e- colliders
VL - 427
SP - 193246
DO - 10.22323/1.427.0101
ER -
@conference{
author = "Vidaković, Ivana and Radulović, Mirko and Stevanović, Jasna and Kačarević, Goran",
year = "2023",
abstract = "Even though the environment at future e+e- colliders is practically QCD background free, there is a large number of processes with high cross-sections and/or similar topology as the Higgs signal of interest. Maximization of the achievable precision of measurements in the Higgs sector and beyond calls for optimized event selection with respect to the statistical significance. This is where the Multivariate Analysis (MVA) is employed, separating the signal from numerous backgrounds on the basis of their kinematic and other properties. In this paper, we discuss the basics of MVA, its application and performance, in examples of several Higgs analyses done in our group using full simulation of the CLIC data.",
journal = "Proceedings of Science",
title = "Application of Multivariate Analysis in Separation of Higgs Boson Signal at future e+e- colliders",
volume = "427",
pages = "193246",
doi = "10.22323/1.427.0101"
}
Vidaković, I., Radulović, M., Stevanović, J.,& Kačarević, G.. (2023). Application of Multivariate Analysis in Separation of Higgs Boson Signal at future e+e- colliders. in Proceedings of Science, 427, 193246.
https://doi.org/10.22323/1.427.0101
Vidaković I, Radulović M, Stevanović J, Kačarević G. Application of Multivariate Analysis in Separation of Higgs Boson Signal at future e+e- colliders. in Proceedings of Science. 2023;427:193246.
doi:10.22323/1.427.0101 .
Vidaković, Ivana, Radulović, Mirko, Stevanović, Jasna, Kačarević, Goran, "Application of Multivariate Analysis in Separation of Higgs Boson Signal at future e+e- colliders" in Proceedings of Science, 427 (2023):193246,
https://doi.org/10.22323/1.427.0101 . .
