scholarly journals QCD Hard Scattering Results from PHENIX at RHIC

2004 ◽  
pp. 61-69
Author(s):  
David d’Enterria
Keyword(s):  
Hard Scattering

scholarly journals General recipe to form input space for deep learning analysis of HEP scattering processes

2020 ◽  
Vol 35 (21) ◽  
pp. 2050119
Author(s):  
Lev Dudko ◽  
Georgi Vorotnikov ◽  
Petr Volkov ◽  
Maxim Perfilov ◽  
Andrei Chernoded ◽  
...  
Keyword(s):  
Deep Learning ◽  
Multivariate Data Analysis ◽  
Hard Scattering ◽  
Input Space ◽  
Low Level ◽  
Multivariate Technique ◽  
Deep Learning Neural Network ◽  
Learning Analysis ◽  
Sophisticated Analysis ◽  
Kinematic Properties

Deep learning neural network (DNN) technique is one of the most efficient and general approach of multivariate data analysis of the collider experiments. The important step of the analysis is the optimization of the input space for multivariate technique. In the paper we propose the general recipe how to form the set of low-level observables sensitive to the differences in hard scattering processes at the colliders. It is shown in the paper that without any sophisticated analysis of the kinematic properties one can achieve close to optimal performance of DNN with the proposed general set of low-level observables.

scholarly journals Threshold resummation for QCD hard scattering

1997 ◽  
Author(s):  
Nikolaos Kidonakis ◽  
George Sterman
Keyword(s):  
Hard Scattering ◽  
Threshold Resummation

scholarly journals αs from global fits of parton distribution functions

2016 ◽  
Vol 31 (25) ◽  
pp. 1630023 ◽  
Author(s):  
S. Alekhin ◽  
J. Blümlein ◽  
S.-O. Moch
Keyword(s):  
Inelastic Scattering ◽  
Deep Inelastic Scattering ◽  
Parton Distribution ◽  
Distribution Functions ◽  
Scattering Data ◽  
Hard Scattering ◽  
Coupling Constant ◽  
Parton Distribution Functions ◽  
The Status

The status of the determination of the strong coupling constant [Formula: see text] from deep-inelastic scattering and related hard scattering data is reviewed.

Sign in / Sign up

Export Citation Format

Share Document