相关论文: Machine Learning Optimized Search for the $Z'$ fro…

We consider machine learning techniques associated with the application of a Boosted Decision Tree (BDT) to searches at the Large Hadron Collider (LHC) for pair-produced lepton partners which decay to leptons and invisible particles. This…

We demonstrate that neural networks can be used to improve search strategies, over existing strategies, in LHC searches for light electroweak-charged scalars that decay to a muon and a heavy invisible fermion. We propose a new search…

In this study, we apply LHC data to constrain the extension of the Standard Model by an anomaly-free $U(1)_{L_\mu-L_\tau}$ gauge group; this model contains a new gauge boson ($Z^\prime$) and a scalar dark matter particle ($\phi_{\rm DM}$).…

Nowadays there is an active discussion about the definition of Simplified Models of Dark Matter (SMDM) as a tool for interpreting LHC searches. Here we point out an additional simplified set-up which captures a very well motivated mechanism…

An $SU(2)_N$ extension ($N$ stands for neutral) of the Standard Model (SM) is proposed with an additional $U(1)=S^{'}$ global symmetry, which stabilizes the lightest of the vector boson ($X,\bar{X}$) as dark matter (DM) through unbroken…

The popularity of Machine Learning (ML) has been increasing in the last decades in almost every area, being the commercial and scientific fields the most notorious ones. Concerning particle physics, ML has been proved as a useful resource…

We study the simplest extensions of the Standard Model (SM) that originate Dark Matter (DM) candidates, built with the addition of real singlets and new ${Z}_2$ symmetries under which the models are invariant. In this type of models the…

The search for dark-matter (DM) candidates at high-energy colliders is one of the most promising avenues to understand the nature of this elusive component of the universe. Several searches at the Large Hadron Collider (LHC) have strongly…

The experiments searching for a hidden gauge sector with a leptophilic neutral gauge boson have already ruled out $U(1)_{L_e-L_\mu}$ as a feasible extension of the Standard Model (SM) gauge group ($\mathcal{G}_{\rm SM}$) for explaining the…

The study of collision events with missing energy as searches for the dark matter (DM) component of the Universe are an essential part of the extensive program looking for new physics at the LHC. Given the unknown nature of DM, the…

The $U(1)_{L_\mu-L_\tau}$ extended Standard Model (SM) is anomaly free, and contains a massive $Z^\prime$ boson. The associated Higgs, which generates the $Z'$'s mass via spontaneous symmetry breaking (SSB) can mix with the SM Higgs. The…

We investigate a WIMP dark matter (DM) candidate in the form of a singlino-dominated lightest supersymmetric particle (LSP) within the $Z_3$-symmetric Next-to-Minimal Supersymmetric Standard Model (NMSSM). This framework gives rise to…

The U(1) extended supersymmetric standard model (UMSSM) can accommodate a Higgs boson at 125 GeV without relying on large corrections from the top/stop sector. After imposing LHC results on the Higgs sector, on B-physics and on new particle…

Astrophysical and cosmological observations strongly suggest the existence of Dark Matter\,(DM). Experiments at the Large Hadron Collider\,(LHC) have the potential to probe the particle nature of the DM. In the present work, we investigate…

We use the framework of the p19MSSM to perform a fit to the mild excesses over the Standard Model background recently observed in three bins of the ATLAS 1-lepton + (b-)jets + MET search. We find a few types of spectra that can fit the…

The system of light electroweakinos and heavy squarks gives rise to one of the most challenging signatures to detect at the LHC. It consists of missing transverse energy recoiled against a few hadronic jets originating either from QCD…

In a truly model-independent approach, we reexamine a minimal extension of the Standard Model (SM) through the introduction of an additional $U(1)$ symmetry leading to a new neutral gauge boson ($Z'$), allowing its kinetic mixing with the…

We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical…

We study several simplified dark matter (DM) models and their signatures at the LHC using neural networks. We focus on the usual monojet plus missing transverse energy channel, but to train the algorithms we organize the data in 2D…

We present the results and prospects for searches beyond the Standard Model (SM) at the LHC by the ATLAS and CMS collaborations. The minimal supersymmetric extension of the SM has been investigated in various configurations and lower limits…