Related papers: Probing stop pair production at the LHC with graph…
Graph Neural Networks (GNNs) are the state-of-the-art model for machine learning on graph-structured data. The most popular class of GNNs operate by exchanging information between adjacent nodes, and are known as Message Passing Neural…
A search for production of the supersymmetric partners of the top quark, top squarks, is presented. The search is based on proton-proton collision events containing multiple jets, no leptons, and large transverse momentum imbalance. The…
We argue that evidence can be uncovered for stops between 300-600 GeV in 5 fb^-1 of 7 TeV proton-proton collisions if they decay into top quarks and light neutral particles. We also show that with 20 fb^-1 of 8 TeV running, discovery or…
Several new physics models including versions of supersymmetry (SUSY) characterized by $R$-parity violation (RPV) or with additional hidden sectors predict the production of events with top quarks, low missing transverse momentum, and many…
Run 1 data of the Large Hadron Collider (LHC) contain excessive events in the same-sign dilepton channel with b-jets and missing transverse energy (MET), which were observed by five separate analyses from ATLAS and CMS collaborations. We…
Results are presented from a search for natural gauge-mediated supersymmetry (SUSY) in a scenario in which the top squark is the lightest squark, the next-to-lightest SUSY particle is a bino-like neutralino, and the lightest SUSY particle…
Graph Neural Networks (GNNs) are popular deep learning models designed to process graph-structured data through recursive neighborhood aggregations in the message passing process. When applied to semi-supervised node classification, the…
Accurate and fast simulation of particle physics processes is crucial for the high-energy physics community. Simulating particle interactions with detectors is both time consuming and computationally expensive. With the proton-proton…
In this paper, the top quark pair production events are analyzed as a source of neutral Higgs bosons of two Higgs doublet model type I at LHC. The production mechanism is $pp \to H/A \to t\bar{t}$ assuming a fully hadronic final state…
We study the phenomenology of heavy neutral leptons (HNLs) at the LHC in effective field theory, concentrating on $d=6$ operators with top quarks. Depending on the operator choice and HNL mass, the HNLs will be produced either from…
Supersymmetry (SUSY) is a theory that gives an explanation for the strong and electroweak interactions from the grand unification scale down to the weak scale. The search for supersymmetric particles still continues at full speed at the LHC…
Graph Convolutional Networks (GCNs) are powerful for processing graph-structured data and have achieved state-of-the-art performance in several tasks such as node classification, link prediction, and graph classification. However, it is…
We study the graphs formed from instances of the stable matching problem by connecting pairs of elements with an edge when there exists a stable matching in which they are matched. Our results include the NP-completeness of recognizing…
A search for the production of a pair of top squarks at the LHC is presented. This search targets a region of parameter space where the kinematics of top squark pair production and top quark pair production are very similar, because of the…
Message Passing Neural Networks (MPNNs) hold a key position in machine learning on graphs, but they struggle with unintended behaviors, such as over-smoothing and over-squashing, due to irregular data structures. The observation and…
Message Passing Neural Networks (MPNNs) are instances of Graph Neural Networks that leverage the graph to send messages over the edges. This inductive bias leads to a phenomenon known as over-squashing, where a node feature is insensitive…
In the forthcoming years the LHC experiments are going to be upgraded to benefit from the substantial increase of the LHC instantaneous luminosity, which will lead to larger, denser events, and, consequently, greater complexity in…
The paper presents a solution to the problem of universal representation of graphs exemplifying communication network topologies with the help of neural networks. The proposed approach is based on message-passing neural networks (MPNN). The…
We present a measurement of the top pair production cross section in $p\bar{p}$ collisions at $\sqrt{s}$=1.96 TeV. We collect a data sample with an integrated luminosity of 194$\pm$11 pb$^{-1}$ with the CDF II detector at the Fermilab…
We have searched for the supersymmetric partner of the top quark (stop) in 107 pb^{-1} of p-pbar collisions at \sqrt{s}= 1.8 TeV collected by the Collider Detector at Fermilab (CDF). Within the framework of the Minimal Supersymmetric…