相关论文: Jet energy calibration with deep learning as a Kub…
Embedding symmetries in the architectures of deep neural networks can improve classification and network convergence in the context of jet substructure. These results hint at the existence of symmetries in jet energy depositions, such as…
Measurements of jet substructure in ultra-relativistic heavy ion collisions suggest that the jet showering process is modified by the interaction with quark gluon plasma. Modifications of the hard substructure of jets can be explored with…
The jet calibration of the Liquid-Argon-Calorimeter of the H1 Detector at HERA is described. In the measurement of high jet transverse energies systematic uncertainties as low as 2% can be reached in deep inelastic scattering with a high…
The jet quenching phenomenon in heavy ion collisions provides a strong evidence of the modification of parton shower in the quark-gluon plasma (QGP). Jet substructure observables can probe various aspects of the jet formation mechanism.…
A broad program of measurements is planned for heavy ion collisions in ATLAS. With up to a factor of 30 increase in collision energy compared to existing data, significant new insights are anticipated to be obtained with the first data…
Jets produced in high-energy heavy-ion collisions are modified compared to those in proton-proton collisions due to their interaction with the deconfined, strongly-coupled quark-gluon plasma (QGP). In this work, we employ machine learning…
State-of-the-art deep learning models have achieved significant performance levels on various benchmarks. However, the excellent performance comes at a cost of inefficient computational cost. Light-weight architectures, on the other hand,…
Process optimization in chemical engineering may be hindered by the limited availability of reliable thermodynamic data for fluid mixtures. Remarkable progress is being made in predicting thermodynamic mixture properties by machine learning…
From dedicated QCD studies to new physics background estimation, jets will be everywhere at the LHC. In these proceedings, we discuss two important recent series of improvements. In the first one, we introduce new algorithms and new…
Measurements are presented of the jet invariant mass and substructure in proton-proton collisions at sqrt{s} = 7 TeV with the ATLAS detector using an integrated luminosity of 37 pb-1. These results exercise the tools for distinguishing the…
Heavy flavor jets provide ideal tools to probe the mass effect on jet substructure in both vacuum and quark-gluon plasma (QGP). Energy-energy correlator (EEC) is an excellent jet substructure observable owning to its strong sensitivity to…
This paper investigates the prediction of vessels' arrival time to the pilotage area using multi-data fusion and deep learning approaches. Firstly, the vessel arrival contour is extracted based on Multivariate Kernel Density Estimation…
Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and process or device technologies are increasingly important to…
The energy loss of fast partons traversing the strongly interacting matter produced in high-energy nuclear collisions is one of the most interesting observables to probe the nature of the produced medium. The multipurpose Compact Muon…
Jet flavor tagging plays an important role in precise Standard Model measurement enabling the extraction of mass dependence in jet-quark interaction and quark-gluon plasma (QGP) interactions. They also enable inferring the nature of…
Foundation models are deep learning models pre-trained on large amounts of data which are capable of generalizing to multiple datasets and/or downstream tasks. This work demonstrates how data collected by the CMS experiment at the Large…
Energy-energy correlators (EECs) provide a sensitive probe of both perturbative and nonperturbative dynamics in relativistic heavy-ion collisions. Jet-medium interactions enhance particle multiplicity within the jet cone, which must be…
In this study, a comprehensive analysis of jets and underlying events as a function of charged particle multiplicity in proton-proton (pp) collisions at a center-of-mass energy of $\sqrt{s} = 7$ TeV is presented. Various Monte Carlo (MC)…
The internal structure of jets produced in pp collisions at the LHC is measured using the ATLAS detector in an inclusive jet sample corresponding to 35pb-1 of pp collisions at sqrt(s) = 7 TeV. Classical jet shape and energy flow…
The energy balance of a plasma holds fundamental information not only about basic plasma physics, but it is also important for tailoring plasmas to specific applications. Especially RF-driven atmospheric pressure plasma jets (APPJs)…