Related papers: Learning to Identify Semi-Visible Jets
We propose a new class of dark-shower signatures in Standard Model extensions featuring Hidden Valleys or dark sectors coupled through an s-channel mediator. In this framework, unstable dark pions appear as long-lived particles (LLPs), with…
Jet quenching, the modification of jets by the quark-gluon plasma in heavy-ion collisions, provides a sensitive probe of the properties of the medium. A jet-by-jet discrimination study between proton-proton and lead-lead jets using energy…
We examine the robustness of collider phenomenology predictions for a dark sector scenario with QCD-like properties. Pair production of dark quarks at the LHC can result in a wide variety of signatures, depending on the details of the new…
It is an intriguing possibility that the cold dark matter of the Universe may consist of very light and very weakly interacting particles such as axion(-like particles) and hidden photons. This opens up (but also requires) new techniques…
In this paper, we address the task of detecting semantic parts on partially occluded objects. We consider a scenario where the model is trained using non-occluded images but tested on occluded images. The motivation is that there are…
We investigate the consequences of models where dark sector quarks could be produced at the LHC, which subsequently undergo a dark parton shower, generating jets of dark hadrons that ultimately decay back to Standard Model hadrons. This…
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…
We study collider signatures of a class of dark matter models with a GeV-scale dark Z'. At hadron colliders, the production of dark matter particles naturally leads to associated production of the Z', which can appear as a narrow jet after…
We propose a new search strategy for high-multiplicity hadronic final states. When new particles are produced at threshold, the distribution of their decay products is approximately isotropic. If there are many partons in the final state,…
Jet substructure provides one of the most exciting new approaches for searching for physics in and beyond the Standard Model at the Large Hadron Collider. Modern jet substructure searches are often performed with Neural Network (NN) taggers…
Many extensions of the standard model (SM) predict the existence of axion-like particles and/or dark Higgs in the sub-GeV scale. Two new sub-GeV particles, a scalar and a pseudoscalar, produced through the Higgs boson exotic decays, are…
The substructure of jets produced in an exclusive and a charm-induced dijet sample in photoproduction and in charged and neutral current interactions has been studied with the ZEUS detector at HERA. Jets were identified using the…
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…
Precise aircraft recognition in low-resolution remote sensing imagery is a challenging yet crucial task in aviation, especially combat identification. This research addresses this problem with a novel, scalable, and AI-driven solution. The…
Full jet reconstruction in relativistic heavy ion collisions provides new and unique insights to the physics of parton energy loss. Because of the large underlying event multiplicity in $A+A$ collisions, random and correlated fluctuations…
Jets are extended multipartonic systems and serve as a powerful tool for investigating the dynamics of emergent phenomena driven by many body QCD interactions. In heavy ion collisions, starting from their production during the perturbative…
The dark matter sector remains completely unknown. It is therefore crucial to keep an open mind regarding its nature and possible interactions. Focusing on the case of Weakly Interacting Massive Particles, in this work we make this general…
Mechanistic interpretability seeks to reverse engineer a trained neural network by identifying the minimal subset of internal components. We perform a mechanistic interpretability analysis of the Particle Transformer architecture, trained…
Weakly supervised learning of object detection is an important problem in image understanding that still does not have a satisfactory solution. In this paper, we address this problem by exploiting the power of deep convolutional neural…
Object detectors achieve strong performance under nominal imaging conditions but can fail silently when exposed to blur, noise, compression, adverse weather, or resolution changes. In safety-critical settings, it is therefore insufficient…