相关论文: Using Machine Learning to disentangle LHC signatur…

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…

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 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…

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…

Higgsino in supersymmetric standard models can play the role of dark matter particle. In conjunction with the naturalness criterion, the higgsino mass parameter is expected to be around the electroweak scale. In this work, we explore the…

If the dark matter (DM) consists of a weakly interacting massive particle (WIMP), it can be produced and studied at future collider experiments like those at the LHC. The production of collider-stable WIMPs is characterized by hard…

Simplified models of the dark matter (co)annihilation mechanism predict striking new collider signatures untested by current searches. These models, which were codified in the coannihilation codex, provide the basis for a dark matter (DM)…

Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…

Missing energy signals such as monojets are a possible signature of Dark Matter (DM) at colliders. However, neutrino interactions beyond the Standard Model may also produce missing energy signals. In order to conclude that new "missing…

The detection of Dark Matter (DM) remains a significant challenge in particle physics. This study exploits advanced machine learning models to improve detection capabilities of liquid xenon time projection chamber experiments, utilizing…

The inert 2-Higgs Doublet Model (i2HDM) is a well-motivated minimal consistent Dark Matter (DM) model, but it is rather challenging to test at the Large Hadron Collider (LHC) in the parameter space allowed by relic density and DM direct…

Dark matter (DM) has been searched for at colliders in a largely model independent fashion by looking for an excess number of events involving a single jet, or photon, and missing energy. We investigate the possibility of looking for…

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…

The XENON1T experiment uses a time projection chamber (TPC) with liquid Xenon to search for Weakly Interacting Massive Particles (WIMPs), a proposed Dark Matter particle, via direct detection. As this experiment relies on capturing rare…

We propose a novel dark matter (DM) detection strategy for the models with non-minimal dark sector. The main ingredients in the underlying DM scenario are a boosted DM particle and a heavier dark sector state. The relativistic DM impinged…

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…

Strong gravitational lensing is a promising probe of the substructure of dark matter halos. Deep learning methods have the potential to accurately identify images containing substructure, and differentiate WIMP dark matter from other well…

Assuming that dark matter is a weakly interacting massive particle (WIMP) species X produced in the early Universe as a cold thermal relic, we study the collider signal of pp or ppbar -> XXbar + jets and its distinguishability from…

Models in which the dark matter is very weakly coupled to the observable sector may explain the observed dark matter density, either as a "superWIMP" or as "asymmetric dark matter." Both types of models predict displaced vertices at…

The CYGNO experiment employs an optical-readout Time Projection Chamber (TPC) to search for rare low-energy interactions using finely resolved scintillation images. While the optical readout provides rich topological information, it…