Related papers: Probing stop pair production at the LHC with graph…
We study the potential of deep learning to resolve the combinatorial problem in SUSY-like events with two invisible particles at the LHC. As a concrete example, we focus on dileptonic $t \bar t$ events, where the combinatorial problem…
Most supersymmetric models predict new particles within the reach of the next generation of colliders. For an understanding of the model structure and the mechanism(s) of electroweak symmetry breaking, it is important to know the masses of…
Studies are presented of the selection of events consistent with top quark pair production in data recorded by the CMS detector at the LHC, corresponding to an integrated luminosity of 0.84+/-0.09 1/pb and at center-of-mass energy sqrt{s}=7…
Subgraph-wise sampling -- a promising class of mini-batch training techniques for graph neural networks (GNNs -- is critical for real-world applications. During the message passing (MP) in GNNs, subgraph-wise sampling methods discard…
The results of a search for top squark (stop) pair production in final states with one isolated lepton, jets, and missing transverse momentum are reported. The analysis is performed with proton--proton collision data at $\sqrt{s} = 8$ TeV…
We investigate the sensitivity of the LHC to flavour-changing neutral current interactions involving the top quark and a photon using a model-independent effective field theory framework, focusing on two complementary processes: single top…
We describe a method to help the search for a light stop squark [M(stop) + M(LSP) < M(top)] at the Fermilab Tevatron. Traditional search methods rely upon a series of stringent background-reducing cuts which, unfortunately, leave very few…
We propose a novel strategy for disentangling proton collisions at hadron colliders such as the LHC that considerably improves over the current state of the art. Employing a metric inspired by optimal transport problems as the cost function…
Searches for supersymmetry (SUSY) are performed using a sample of hadronic events produced in 8 TeV pp collisions at the CERN LHC. The searches are based on the MT2 variable, which is a measure of the transverse momentum imbalance in an…
The multi-TeV energies available at LHC have opened up the possibility to measure, for the first time, various large-mass elementary particles in nuclear collisions. The current study presents the first observation of top quark--the…
Source detection is crucial for capturing the dynamics of real-world infectious diseases and informing effective containment strategies. Most existing approaches to source detection focus on conventional pairwise networks, whereas recent…
We present the measurement of the production cross section for top quark pair ($t\bar{t}$) in pp collisions at $\sqrt{s}$ = 7 TeV using the data recorded with the ATLAS detector at the Large Hadron Collider (LHC). Events are selected in…
The results of many LHC searches for supersymmetric particles are interpreted using simplified models, in which one fixes the masses and couplings of most sparticles then scans over a few remaining masses of interest. We present a new…
Results are reported from a search for new physics processes in events containing a single isolated high-transverse-momentum lepton (electron or muon), energetic jets, and large missing transverse momentum. The analysis is based on a 4.98…
The interpretation of Large Hadron Collider (LHC) data in the framework of Beyond the Standard Model (BSM) theories is hampered by the need to run computationally expensive event generators and detector simulators. Performing statistically…
Message Passing Neural Networks (MPNNs) model local relations effectively but struggle to propagate information over long distances. Graph Transformers (GTs) mitigate this via global self-attention, yet their quadratic cost in the number of…
Message passing graph neural networks (GNNs) are a popular learning architectures for graph-structured data. However, one problem GNNs experience is oversquashing, where a GNN has difficulty sending information between distant nodes.…
Stop particles are expected to be the lightest squarks in supersymmetric theories and the search for these particles is an important experimental task. We therefore present the cross sections for the production processes $p\bar{p}/pp \to…
Narrowing the performance gap between optimal and feasible detection in inter-symbol interference (ISI) channels, this paper proposes to use graph neural networks (GNNs) for detection that can also be used to perform joint detection and…
We study the potential of hadron colliders in the search for the pair production of neutral Higgs bosons in the framework of the Minimal Supersymmetric Standard Model. Using analytical expressions for the relevant amplitudes, we perform a…