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Machine Learning (ML) techniques have been employed for the high energy physics (HEP) community since the early 80s to deal with a broad spectrum of problems. This work explores the prospects of using Deep Learning techniques to estimate…
Experiments involving proton-proton collisions at energies $\sqrt{s_{NN}}$ = 0.9, 2.76 and 7 TeV in Large Hadron Collider (LHC) have produced a vast amount of high-precision data. Here, in this work, we have chosen to analyse the two…
The signal for a highly boosted heavy resonance competing against a background of light parton jets at the LHC can be enhanced by analyzing subjets in the "fat" jet that possibly contains the heavy resonance. Three methods for doing this…
We study a large-$p_T$ three-photon production in proton-proton collisions at the LHC. We use the leading order (LO) approximation of the parton Reggeization approach consistently merged with the next-to-leading order corrections originated…
The large center of mass energy and increasing statistical precision for a wide range of hadronic final state observables at the HERA lepton-proton collider has provided a detailed testing ground for QCD dynamics. Fully flexible…
Jet suppression is considered to be an excellent probe of QCD matter created in ultra-relativistic heavy ion collisions. Our theoretical predictions of jet suppression, which are based on our recently developed dynamical energy loss…
Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36-81 fb$^{-1}$ of proton-proton collision data with a centre-of-mass energy of $\sqrt{s}=13$ TeV collected by the ATLAS detector…
One of the important perturbative ("hard") probes of hot and dense QCD matter is the medium-induced energy loss of energetic partons, so called "jet quenching", which is predicted to be very different in cold nuclear matter and in QGP, and…
A status report on the jet quenching physics in heavy-ion collisions is given as it appears after more than 10 years of collecting and analysing data at the Relativistic Heavy Ion Collider (RHIC) and ~1.5 years of physics at the Large…
In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators.…
Since the beginning of 2010 the LHC provides p+p collisions at the highest center of mass energies to date, allowing to study high $\pT$ particle production and jet properties in a new energy regime. For a clear interpretation and the…
We expose the role of collisional energy loss on high $p_T$ photon data measured by PHENIX collaboration by calculating photon yield in jet plasma interaction. The phase space distribution of the participating jet is dynamically evolved by…
In this work we demonstrate that significant gains in performance and data efficiency can be achieved in High Energy Physics (HEP) by moving beyond the standard paradigm of sequential optimization or reconstruction and analysis components.…
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…
The identification of jets originating from b quarks is crucial both for the searches for new physics and for the measurement of standard model processes. The Compact Muon Solenoid (CMS) collaboration at the Large Hadron Collider (LHC) has…
Hard QCD processes in ultrarelativistic heavy-ion collisions become increasingly relevant and they can be used as probes of the dense matter formed during the violent scatterings. We will discuss how one can use these hard probes to study…
Elliptic flow of hard partons (P>5 GeV), squeeze-out of soft partons (P<=5 GeV) and produced particles are predicted in the framework of the HIJING model. They are caused due to jet quenching and heterogeneity of the interaction region.
The discovery of collectivity in proton-proton collisions, is one of the most puzzling outcomes from the two first runs at LHC, as it points to the possibility of creation of a Quark-Gluon Plasma, earlier believed to only be created in…
A machine learning technique is used to fit multiplicity distributions in high-energy proton-proton collisions and applied to make predictions for collisions at higher energies. The method is tested with Monte Carlo event generator events.…
Jet measurements in heavy ion collisions can provide constraints on the properties of the quark gluon plasma, but the kinematic reach is limited by a large, fluctuating background. We present a novel application of symbolic regression to…