The application of boosted decision trees and deep neural networks to the identification of hadronically-decaying W bosons and top quarks using high-level jet observables as inputs is investigated using Monte Carlo simulations. In the case of both boosted decision trees and deep neural networks, the use of machine learning techniques is found to improve the background rejection with respect to simple reference single jet substructure and mass taggers. Linear correlations between the resulting classifiers and the substructure variables are also presented
The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at...
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lor...
The top quark, the heaviest particle to date, plays a key role in the physics program of the LHC (La...
We present techniques for the identification of hadronically-decaying W bosons and top quarks using ...
By colliding protons and examining particles emitted from the collisions, the Large Hadron Collider ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
By colliding protons and examining the particle emitted from the collisions, the Large Hadron Collid...
Hadronic decays of vector bosons and top quarks are increasingly important to the ATLAS physics prog...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at...
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lor...
The top quark, the heaviest particle to date, plays a key role in the physics program of the LHC (La...
We present techniques for the identification of hadronically-decaying W bosons and top quarks using ...
By colliding protons and examining particles emitted from the collisions, the Large Hadron Collider ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
By colliding protons and examining the particle emitted from the collisions, the Large Hadron Collid...
Hadronic decays of vector bosons and top quarks are increasingly important to the ATLAS physics prog...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W ...
The performance of taggers for hadronically decaying top quarks and $W$ bosons in $pp$ collisions at...
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lor...
The top quark, the heaviest particle to date, plays a key role in the physics program of the LHC (La...