activity
20092023
most citedObservation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC

10.9k citations · 23.1k across the 109 of their papers we have counts for

collaborators

109 papers

hep-ex2023★ 2 cited

Search for quantum black hole production in lepton+jet final states using proton-proton collisions at = 13 TeV with the ATLAS detector

ATLAS Collaboration

A search for quantum black holes in electron+jet and muon+jet invariant mass spectra is performed with 140 fb of data collected by the ATLAS detector in proton-proton collis…

hep-ex2022★ 3 cited

Measurement of the inclusive production cross section in the lepton+jets channel in collisions at = 7 TeV with the ATLAS detector using support vector machines

ATLAS Collaboration

A measurement of the top quark pair-production cross section in the lepton+jets decay channel is presented. It is based on 4.6 fb of TeV collision data…

cs.CL2021★ 2 cited

The Dawn of Quantum Natural Language Processing

Riccardo Di Sipio, Jia-Hong Huang, Samuel Yen-Chi Chen +2

In this paper, we discuss the initial attempts at boosting understanding human language based on deep-learning models with quantum computing. We successfully train a quantum-enhanc…

hep-ex2020★ 43 cited

Search for dark matter in association with an energetic photon in pp collisions at = 13 TeV with the ATLAS detector

ATLAS Collaboration

A search for dark matter is conducted in final states containing a photon and missing transverse momentum in protonproton collisions at = 13 TeV. The data, collected…

physics.ins-det2019★ 29 cited

Modelling radiation damage to pixel sensors in the ATLAS detector

ATLAS Collaboration

Silicon pixel detectors are at the core of the current and planned upgrade of the ATLAS experiment at the LHC. Given their close proximity to the interaction point, these detectors…

hep-ex2019★ 93 cited

DijetGAN: A Generative-Adversarial Network Approach for the Simulation of QCD Dijet Events at the LHC

Riccardo Di Sipio, Michele Faucci Giannelli, Sana Ketabchi Haghighat +1

A Generative-Adversarial Network (GAN) based on convolutional neural networks is used to simulate the production of pairs of jets at the LHC. The GAN is trained on events generated…