Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to the proton-proton baseline. However, the steeply falling production spectrum introduces a strong bias toward small energy losses that obfuscates a direct interpretation of the impact of medium effects in the measured jet ensemble. Modern machine learning techniques offer the potential to tackle this issue on a jet-by-jet basis. In this paper, we employ a convolutional neural network (CNN) to diagnose such modifications from jet images where the training and validation is performed using the hybrid strong/weak coupling model. By analyzing measured jets in heavy-...
Jet tomography has become a powerful tool for the study of properties of dense matter in high-energ...
Jet images are essential utilities in High Energy Physics (HEP) as they enable the extraction of cru...
Title: Exploring jet calibration with machine learning techniques Author: Patrik Novotný Institute: ...
Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by ...
An important aspect of the study of Quark-Gluon Plasma (QGP) in ultra-relativistic collisions of hea...
Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions...
Abstract : Jets produced in high-energy heavy-ion collisions are modified comp...
Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and ...
Over the last years, machine learning tools have been successfully applied to a wealth of problems i...
In this proceeding, we review our recent work using deep convolutional neural network (CNN) to ident...
Studies of fully-reconstructed jets in heavy-ion collisions aim at extracting thermodynamical and tr...
We define a new strategy to scan jet substructure in heavy-ion collisions. The scope is multifold: (...
Jet shapes and, furthermore, jet substructure observables are of utmost interest for the field of he...
Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modificatio...
The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used ...
Jet tomography has become a powerful tool for the study of properties of dense matter in high-energ...
Jet images are essential utilities in High Energy Physics (HEP) as they enable the extraction of cru...
Title: Exploring jet calibration with machine learning techniques Author: Patrik Novotný Institute: ...
Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by ...
An important aspect of the study of Quark-Gluon Plasma (QGP) in ultra-relativistic collisions of hea...
Highly energetic jets are sensitive probes for the kinematics and the topology of nuclear collisions...
Abstract : Jets produced in high-energy heavy-ion collisions are modified comp...
Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and ...
Over the last years, machine learning tools have been successfully applied to a wealth of problems i...
In this proceeding, we review our recent work using deep convolutional neural network (CNN) to ident...
Studies of fully-reconstructed jets in heavy-ion collisions aim at extracting thermodynamical and tr...
We define a new strategy to scan jet substructure in heavy-ion collisions. The scope is multifold: (...
Jet shapes and, furthermore, jet substructure observables are of utmost interest for the field of he...
Within the context of a hybrid strong/weak coupling model of jet quenching, we study the modificatio...
The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used ...
Jet tomography has become a powerful tool for the study of properties of dense matter in high-energ...
Jet images are essential utilities in High Energy Physics (HEP) as they enable the extraction of cru...
Title: Exploring jet calibration with machine learning techniques Author: Patrik Novotný Institute: ...