相关论文: Deep Learning Jet Image as a Probe of Light Higgsi…

Pair production of light top squarks at the 8-TeV LHC can be used to probe the gaugino-Higgsino sector of the Minimal Supersymmetric Standard Model. The case where the lightest neutralino is a mixture of Bino and Higgsino, satisfying the…

Jet substructure has emerged to play a central role at the Large Hadron Collider (LHC), where it has provided numerous innovative new ways to search for new physics and to probe the Standard Model in extreme regions of phase space. In this…

Strong gravitational lensing is a promising way of uncovering the nature of dark matter, by finding perturbations to images that cannot be well accounted for by modeling the lens galaxy without additional structure, be it subhalos (smaller…

The search for weakly interacting matter particles (WIMPs) is one of the main objectives of the High Luminosity Large Hadron Collider (HL-LHC). In this work we use Machine-Learning (ML) techniques to explore WIMP radiative decays into a…

Strongly interacting dark sectors predict novel LHC signatures such as semi-visible jets resulting from dark showers that contain both stable and unstable dark mesons. Distinguishing such semi-visible jets from large QCD backgrounds is…

Higgsino in supersymmetric standard models is known to be a promising candidate for dark matter in the Universe. Its phenomenological property is strongly affected by the gaugino fraction in the Higgsino-like state. If this is sizable, in…

Sophisticated machine learning techniques have promising potential in search for physics beyond Standard Model in Large Hadron Collider (LHC). Convolutional neural networks (CNN) can provide powerful tools for differentiating between…

We consider a minimal natural supersymmetric model based on an extra dimension with supersymmetry breaking provided by the Scherk-Schwarz mechanism. The lightest supersymmetric particle is a neutral, quasi-Dirac Higgsino and, unlike in…

A recently proposed class of supersymmetric models predicts rather light and nearly mass-degenerate higgsinos, while the other superparticles are significantly heavier. In this paper we study the early LHC phenomenology of a benchmark model…

We have explored Natural Supersymmetry (NSUSY) scenarios with low values of the $\mu$ parameter which are characterised by higgsino-like Dark Matter (DM) and compressed spectra for the lightest MSSM particles, $\chi^0_1$, $\chi^0_2$ and…

Jet interactions in a hot QCD medium created in heavy-ion collisions are conventionally assessed by measuring the modification of the distributions of jet observables with respect to the proton-proton baseline. However, the steeply falling…

The subtle and unique imprint of dark matter substructure on extended arcs in strong lensing systems contains a wealth of information about the properties and distribution of dark matter on small scales and, consequently, about the…

In this work, we deep-learn light charged Higgs signal in top quark decays which poses difficulties due to strong W boson contamination. We construct Deep Neural Networks (DNN) with appropriate architecture and determine signal extraction…

Natural SUSY scenarios with a low value of the $\mu$ parameter, are characterised by a higgsino-like dark matter candidate, and a compressed spectrum for the lightest higgsinos. We explore the prospects for probing this scenario at the 13…

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…

The idea that dark matter forms part of a larger dark sector is very intriguing, given the high degree of complexity of the visible sector. In this paper, we discuss lepton jets as a promising signature of an extended dark sector. As a…

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…

We investigate the possibility of applying machine learning techniques to images of strongly lensed galaxies to detect a low mass cut-off in the spectrum of dark matter sub-halos within the lens system. We generate lensed images of systems…

We study dark matter physics in the Minimal Supersymmetric Standard Model with non-universal gaugino masses at the unification scale. In this scenario, the specific ratio of wino and gluino masses realizes the electro-weak scale naturally…

The presence of two light higgsinos nearly degenerate in mass is one of the important characteristics of suspersymmetric models meeting the naturalness criteria. Probing such higgsinos at the LHC is very challenging, in particular when the…