Related papers: Quark-Gluon tagging performance at the High-Lumino…
In high-energy physics, particle jet tagging plays a pivotal role in distinguishing quark from gluon jets using data from collider experiments. While graph-based deep learning methods have advanced this task beyond traditional…
The ATLAS experiment relies on real-time hadronic jet reconstruction and $b$-tagging to record fully hadronic events containing $b$-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm…
The separation of quark and gluon initiated jets can be an important way to improve the sensitivity in searches for new physics or in measurements of Higgs boson properties. We present a simplified version of the shower deconstruction…
The search for new physics at high energy accelerators has been at the crossroads with very little hint of signals suggesting otherwise. The challenges at a hadronic machine such as the LHC is compounded by the fact that final states are…
Measurements of jet substructure in ultra-relativistic heavy-ion collisions indicate that interactions with the quark-gluon plasma quench the jet showering process. Modern data-driven methods have shown promise in probing these…
This paper presents studies of the performance of several jet-substructure techniques, which are used to identify hadronically decaying top quarks with high transverse momentum contained in large-radius jets. The efficiency of identifying…
We study the production of an electroweak boson in association with jets, in processes where the jet with the highest transverse momentum is identified as quark-initiated. The quark/gluon tagging procedure is realised by a cut on a jet…
While the tracking detectors of the ATLAS and CMS experiments have shown excellent performance in Run 1 of LHC data taking, and are expected to continue to do so during LHC operation at design luminosity, both experiments will have to…
With the great promise of deep learning, discoveries of new particles at the Large Hadron Collider (LHC) may be imminent. Following the discovery of a new Beyond the Standard model particle in an all-hadronic channel, deep learning can also…
Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deployment challenges in high-data-throughput environments, such as the CERN LHC. The quadratic…
During the high-luminosity phase of the LHC (HL-LHC), planned to start around 2027, the accelerator is expected to deliver an instantaneous peak luminosity of up to $7.5\times10^{34}$ cm$^{-2}$s$^{-1}$. A total integrated luminosity of…
We develop taggers for multi-pronged jets that are simple functions of jet substructure (so-called `subjettiness') variables. These taggers can be approximately decorrelated from the jet mass in a quite simple way. Specifically, we use a…
Jet substructure observables, designed to identify specific features within jets, play an essential role at the Large Hadron Collider (LHC), both for searching for signals beyond the Standard Model and for testing QCD in extreme phase space…
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…
In the high luminosity era of the Large Hadron Collider, the HL-LHC, the instantaneous luminosity is expected to reach unprecedented values, resulting in about 200 proton-proton interactions in a typical bunch crossing. To cope with the…
The trigger selection capabilities of the ATLAS detector have been significantly enhanced for the LHC Run- 2 in order to cope with the higher event rates and with the large number of simultaneous interactions (pile-up) per protonproton…
Identifying and reconstructing hadronic $\tau$ decays ($\tau_{\textrm{h}}$) is an important task at current and future high-energy physics experiments, as $\tau_{\textrm{h}}$ represent an important tool to analyze the production of Higgs…
In order to increase its discovery potential, the Large Hadron Collider (LHC) accelerator will be upgraded in the next decade. The high luminosity LHC (HL-LHC) period demands new sensor technologies to cope with increasing radiation…
We present a topology-informed approach for classifying particle jets using persistent homology, a framework that captures the structural properties of point clouds. Particle jets produced in proton-proton collisions consist of cascades of…
Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. To establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark…