Related papers: Identification of heavy, energetic, hadronically d…
A search for a massive $W'$ gauge boson decaying to a top quark and a bottom quark is performed with the ATLAS detector in $pp$ collisions at the LHC. The dataset was taken at a centre-of-mass energy of $\sqrt{s} = 8$ TeV and corresponds to…
We briefly review common tools and methods to identify boosted, hadronically decaying top quarks at the LHC experiments. This includes generic jet substructure variables, specific top identification algorithms, and recent developments in…
Dusty plasma is a mixture of ions, electrons, and macroscopic charged particles that is commonly found in space and planetary environments. The particles interact through Coulomb forces mediated by the surrounding plasma, and as a result,…
A search for heavy resonances decaying into a Higgs boson ($H$) and a new particle ($X$) is reported, utilizing 36.1 fb$^{-1}$ of proton-proton collision data at $\sqrt{s} =$ 13 TeV collected during 2015 and 2016 with the ATLAS detector at…
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…
A search for signatures of a dark analog to quantum chromodynamics is performed. The analysis targets long-lived dark mesons that decay into standard-model particles, with a high branching fraction of the dark mesons decaying into muons.…
Machine learning (ML) can be used to construct surrogate models for the fast prediction of a property of interest. ML can thus be applied to chemical projects, where the usual experimentation or calculation techniques can take hours or days…
The photon flux resulting from high-energy electron beam interactions with high field systems, such as in the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, may give deep insight into the electron beam's underlying…
A search for dark matter (DM) particles produced in association with a hadronically decaying vector boson is performed using $pp$ collision data at a centre-of-mass energy of $\sqrt{s}=13$ TeV corresponding to an integrated luminosity of…
Results of a search for the standard model Higgs boson produced in association with a top quark pair ($\mathrm{t\overline{t}}$H) in final states with electrons, muons, and hadronically decaying $\tau$ leptons are presented. The analyzed…
Future electron-positron colliders will play a leading role in the precision measurement of Higgs boson couplings which is one of the central interests in particle physics. Aiming at maximizing the performance to measure the Higgs couplings…
Results are presented from a search in the dijet final state for new massive narrow resonances decaying to pairs of W and Z bosons or to a W/Z boson and a quark. Results are based on data recorded in proton-proton collisions at $\sqrt{s} =$…
The Higgs boson couplings to bottom and top quarks have been measured and agree well with the Standard Model predictions. Decays to lighter quarks and gluons, however, remain elusive. Observing these decays is essential to complete the…
After successful discovery of the Higgs boson, the Large Hadron Collider (LHC) would confront the major challenge in searching for new physics and new particles. Any such observation necessitates the determination of mass and other quantum…
A tau lepton identification algorithm, DeepTau, based on convolutional neural network techniques, has been developed in the CMS experiment to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) from quark or gluon…
A search is made for a vector-like $T$ quark decaying into a Higgs boson and a top quark in 13 TeV proton-proton collisions using the ATLAS detector at the Large Hadron Collider with a data sample corresponding to an integrated luminosity…
Since the discovery of the Higgs boson, testing the many possible extensions to the Standard Model has become a key challenge in particle physics. This paper discusses a new method for predicting the compatibility of new physics theories…
Machine learning (ML) models utilizing structure-based features provide an efficient means for accurate property predictions across diverse chemical spaces. However, obtaining equilibrium crystal structures typically requires expensive…
Machine learning techniques are increasingly being applied toward data analyses at the Large Hadron Collider, especially with applications for discrimination of jets with different originating particles. Previous studies of the power of…
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…