Related papers: Quark Gluon Jet Discrimination with Weakly Supervi…
Whether quark- and gluon-initiated jets are modified differently by the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has thus far eluded a definitive experimental answer. A crucial complication for…
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…
Jets are suppressed and modified in heavy ion collisions, which serve as powerful probes to the properties of the quark-gluon plasma (QGP). Attributed to the abundant information carried by the jet constituents and reconstructed…
Since the machine learning techniques are improving rapidly, it has been shown that the image recognition techniques in deep neural networks can be used to detect jet substructure. And it turns out that deep neural networks can match or…
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…
These lectures were presented at the 2024 QCD Masterclass in Saint-Jacut-de-la-Mer, France. They introduce and review fundamental theorems and principles of machine learning within the context of collider particle physics, focused on…
The modification of jets by interaction with the Quark Gluon Plasma has been extensively established through the comparison of observables computed for samples of jets produced in nucleus-nucleus collisions and proton-proton collisions. The…
The modification of quark- and gluon-initiated jets in the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has not yet received a definitive answer from experiments. In particular, the size of the…
Being able to distinguish light-quark jets from gluon jets on an event-by-event basis could significantly enhance the reach for many new physics searches at the Large Hadron Collider. Through an exhaustive search of existing and novel jet…
Energetic jets that traverse the quark-gluon plasma created in heavy-ion collisions serve as excellent probes to study this new state of deconfined QCD matter. Presently, however, our ability to achieve a crisp theoretical interpretation of…
Many physics analyses at the LHC are looking into processes where the signal jets are originating from quarks, while jets in the background are more gluon enriched. Based on observables sensitive to fundamental differences in the…
We present a survey of a comprehensive set of jet substructure observables commonly used to study the modifications of jets resulting from interactions with the Quark Gluon Plasma in Heavy Ion Collisions. The \jewel{} event generator is…
We investigate how effectively final-state jet substructure can discriminate between QCD Compton and quark-antiquark annihilation processes from photon-jet production in $pp$ collisions at $\sqrt{s}=13$ TeV. Using infrared- and…
We introduce a hybrid quantum-classical vision transformer architecture, notable for its integration of variational quantum circuits within both the attention mechanism and the multi-layer perceptrons. The research addresses the critical…
Modification of the hard jet substructure in terms of the Soft Drop jet grooming algorithm observables is studied for three different scenarios of jet quenching in a quark-gluon plasma: i) an explicit enhancement of the parton splitting…
Progress in the theoretical understanding of parton branching dynamics within an expanding Quark Gluon Plasma relies on detailed and fair comparisons with experimental data for reconstructed jets. Such comparisons are only meaningful when…
The past few years have seen a rapid development of machine-learning algorithms. While surely augmenting performance, these complex tools are often treated as black-boxes and may impair our understanding of the physical processes under…
Distinguishing quarks from gluons based on low-level detector output is one of the most challenging applications of multi-variate and machine learning techniques at the LHC. We first show the performance of our 4-vector-based LoLa tagger…
A likelihood-based discriminant for the identification of quark- and gluon-initiated jets is built and validated using 4.7 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}$ = 7 TeV collected with the ATLAS detector at the LHC. Data…
Deep learning has achieved remarkable success in jet classification tasks, yet a key challenge remains: understanding what these models learn and how their features relate to known QCD observables. Improving interpretability is essential…