Related papers: Reconstructing partonic kinematics at colliders wi…
Having access to the parton-level kinematics is important for understanding the internal dynamics of particle collisions. Here, we present new results aiming to an efficient reconstruction of parton collisions using machine-learning…
High Energy collider experiments are moving to the highest precision frontier quickly. The predictions of observables are based on the factorization formula which helps to connect small to large distances. These predictions can be…
We compute the next-to-leading order QCD corrections to the polarized (and unpolarized) cross sections for the production of a hadron accompanied by an opposite-side prompt photon. This process, being studied at RHIC, permits us to…
The accurate description of the internal structure of hadrons is a very challenging task. In order to compare the predictions with the highly-accurate experimental data, it is necessary to control any possible source of theoretical…
We use a Monte Carlo approach to study hadron azimuthal angular correlations in high energy proton-proton and central nucleus-nucleus collisions at the BNL Relativistic Heavy Ion Collider (RHIC) energies at mid-rapidity. We build a hadron…
Final states with a vector boson and a hadronic jet allow one to infer the Born-level kinematics of the underlying hard scattering process, thereby probing the partonic structure of the colliding protons. At forward rapidities, the parton…
The production of pairs of hadrons in hadronic collisions is studied using a next-to-leading-order Monte Carlo program based on the phase space slicing technique. Up-to-date fragmentation functions based on fits to LEP data are employed,…
Photon-photon collisions are investigated in the framework of the two-component Dual Parton Model. The model is shown to agree well to hadron production data from hadron-hadron and photon-hadron collisions. The multiparticle production in…
We compute the next-to-leading order corrections in $\alpha_s$ to prompt diphoton production in association with a jet at hadron colliders. We use a next-to-leading order general-purpose partonic Monte Carlo event generator that allows the…
The detailed comprehension of momentum fraction and energy dependence of proton structure functions is among the major difficulties in high-energy physics. Perturbative quantum chromodynamics (QCD) plays as an extensive foundation for…
A parton-model description of high-energy hadronic interactions in the presence of Lorentz violation is presented. This approach is used to study lepton-hadron and hadron-hadron interactions at large momentum transfer. Cross sections for…
The construction of a Monte Carlo generator for high energy hadronic and nuclear collisions is discussed in detail. Interactions are treated in the framework of the Reggeon Field Theory, taking into consideration enhanced Pomeron diagrams…
We present an analytical next-to-leading order QCD calculation of the partonic cross sections for the process $pp\rightarrow ({\text{jet}} \,h)X$, for which a specific hadron is observed inside a fully reconstructed jet. In order to obtain…
Herwig 7 is a general-purpose Monte Carlo generator of particle collisions comprising both hard perturbative as well as soft phenomenological physics. Herwig is therefore capable to describe the entire final state of hadronized particles in…
In certain situations, such as one-particle inclusive processes, it is possible to model the hadronization through Fragmentation Functions (FFs), which are universal non-perturbative functions extracted from experimental data through…
We present a next-to-leading order computation in QCD of one-jet and two-jet cross sections in polarized hadronic collisions. Our results are obtained in the framework of a general formalism that deals with soft and collinear singularities…
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…
Based on QCD-inspired models for multiple jets production, we developed a Monte Carlo program to study jet and the associated particle production in high energy $pp$, $pA$ and $AA$ collisions. The physics behind the program which includes…
The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of…
Modern machine learning is driving a paradigm shift in particle physics phenomenology at the Large Hadron Collider. This short review examines the transformative role of machine learning across the entire theoretical prediction pipeline,…