相关论文: Machine Learning Electroweakino Production
Background showers triggered by hadrons represent over 99.9% of all particles arriving at ground-based gamma-ray observatories. An important stage in the data analysis of these observatories, therefore, is the removal of hadron-triggered…
The estimation of the backgrounds for gluino signals in focus point supersymmetry is extended by including the backgrounds from the production of four third generation quarks in the analysis. We find that these backgrounds are negligible if…
Top quarks produced in multi-TeV processes will have large Lorentz boosts, and their decay products will be highly collimated. In semileptonic decay modes, this often leads to the merging of the b-jet and the hard lepton according to…
These proceedings summarize the results of four analyses which searched for squarks and gluinos in hadronic final states with missing transverse momentum in 2.3 fb$^{-1}$ of data in proton-proton collisions at $\sqrt{s}=13$ TeV collected in…
A search for events with jets and missing transverse energy is performed in a data sample of pp collisions collected at sqrt(s) = 7 TeV by the CMS experiment at the LHC. The analyzed data sample corresponds to an integrated luminosity of…
We study the LHC discovery potential for heavy Majorana neutrino singlets in the process pp -> W+ -> l+ N -> l+ l+ jj (l=e,mu) plus its charge conjugate. With a fast detector simulation we show that backgrounds involving two like-sign…
Ensuring a reliable communication in wireless networks strictly depends on the effective estimation of the link quality, which is particularly challenging when propagation environment for radio signals significantly varies. In such…
We pursue a scenario where the lighter top squark (stop) mass is accessible for the Large Hadron Collider (LHC) in the near future, while gluinos and first two generation squarks are heavier. At $\sqrt{s} = 8$ TeV, we investigate the…
Machine learning (ML) with in situ diagnostics offers a transformative approach to accelerate, understand, and control thin film synthesis by uncovering relationships between synthesis conditions and material properties. In this study, we…
Two-dimensional (2D) in-plane heterostructures including compositionally graded alloys and lateral heterostructures with defined interfaces display rich optoelectronic properties and offer versatile platforms to explore one-dimensional…
Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify…
Anomaly detection methods used in a recent search for new phenomena by CMS at the CERN LHC are presented. The methods use machine learning to detect anomalous jets produced in the decay of new massive particles. The effectiveness of these…
Multiple kernel learning (MKL) algorithms combine different base kernels to obtain a more efficient representation in the feature space. Focusing on discriminative tasks, MKL has been used successfully for feature selection and finding the…
Standard jet finding techniques used in elementary particle collisions have not been successful in the high track density of heavy-ion collisions. This paper describes a modified cone-type jet finding algorithm developed for the complex…
Jet measurements in heavy ion collisions at low jet momentum can provide constraints on the properties of the quark gluon plasma but are overwhelmed by a significant, fluctuating background. We build upon our previous work which…
First-principles computations are the driving force behind numerous discoveries of hydride-based superconductors, mostly at high pressures, during the last decade. Machine-learning (ML) approaches can further accelerate the future…
Associated production of the Higgs boson with a top-antitop pair is a key channel to gather further information on the nature of the newly discovered boson at the LHC. Experimentally, however, its observation is very challenging due to the…
With this article we introduce recent, improved machine learning methods from computer vision to the problem of event classification in particle physics. Supersymmetric scalar top decays to top quarks and weak scale bino-like neutralinos,…
In scenarios with relatively light down squarks, motivated, e.g., by SO(10) D terms, jets + missing $E_T$ signals can be observed at the luminosity upgraded Tevatron even if the squarks are much heavier than the gluinos and the common…
Global climate models (GCMs), typically run at ~100-km resolution, capture large-scale environmental conditions but cannot resolve convection and cloud processes at kilometer scales. Convection-permitting models offer higher-resolution…