相关论文: Exploring Scotogenic Parameter Spaces and Mapping …
The Scotogenic model is a popular scenario that induces radiative Majorana neutrino masses and includes a weakly-interacting dark matter candidate. We classify all possible ultraviolet extensions of the Scotogenic model in which (i) the…
The neutrino mass and dark matter (DM) problems are addressed in a Standard Model extension where the type-II seesaw and scotogenic mechanisms coexist. The model features a flavour $\mathcal{Z}_8$ discrete symmetry which is broken down to a…
The search for a Dark Matter particle is the new grail and hard-sought nirvana of the particle physics community. From the theoretical side, it is the main challenge to provide a consistent and model-independent tool for comparing the…
Recently, a number of competitive methods have tackled unsupervised representation learning by maximising the mutual information between the representations produced from augmentations. The resulting representations are then invariant to…
In flavored dark matter models, dark matter can scatter off of nuclei through Higgs and photon exchange, both of which can arise from renormalizable interactions and individually lead to strong constraints from direct detection. While these…
After the observation in 2012 of a new scalar particle closely resembling the Higgs boson of the Standard Model of particle physics, there is a general consensus that there must be Physics Beyond the Standard Model, with present experiments…
We systematically study and classify scotogenic models with a local U(1) gauge symmetry. These models give rise to radiative neutrino masses and a stable dark matter candidate, but avoid the theoretical problems of global and discrete…
We show that Ma's scotogenic model, which is arguably one of the simplest settings containing a Dark Matter candidate and generating a naturally suppressed active neutrino mass at 1-loop level, suffers from a potentially severe…
Artificial intelligence (AI) can accelerate the design of materials by identifying correlations and complex patterns in data. However, AI methods commonly attempt to describe the entire, immense materials space with a single model, while it…
Within the framework of the Minimal Supersymmetric Standard Model (MSSM), we explore a decoupling of the parameters into separate sectors that determine consistency with collider data, the abundance of dark matter, and potential signatures…
Parameter-free stochastic optimization aims to design algorithms that are agnostic to the underlying problem parameters while still achieving convergence rates competitive with optimally tuned methods. While some parameter-free methods do…
We propose an extended $3+1$ Higgs doublet model where the Standard Model (SM) gauge structure is enhanced by the discrete symmetry $Q_6 \times Z_2 \times Z_4$, and the fermion content is extended with right-handed Majorana neutrinos. The…
In the present work, the scotogenic model is constructed applying non invertible $Z_M$ symmetries. The stability of dark matter and the scotogenic structure of the neutrino mass matrix is achieved via the new non-group symmetry. The…
Artificial neural networks have gone through a recent rise in popularity, achieving state-of-the-art results in various fields, including image classification, speech recognition, and automated control. Both the performance and…
Machine learning has achieved remarkable success over the past couple of decades, often attributed to a combination of algorithmic innovations and the availability of high-quality data available at scale. However, a third critical component…
This paper presents a methodological framework for training, self-optimising, and self-organising surrogate models to approximate and speed up multiobjective optimisation of technical systems based on multiphysics simulations. At the hand…
This article addresses the problem of multi-object tracking by using a non-deterministic model of target behaviors with hard constraints. To capture the evolution of target features as well as their locations, we permit objects to lie in a…
The Scotogenic model is an economical scenario that generates neutrino masses at the 1-loop level and includes a dark matter candidate. This is achieved by means of an ad-hoc $\mathbb{Z}_2$ symmetry, which forbids the tree-level generation…
In all but the most trivial optimization problems, the structure of the solutions exhibit complex interdependencies between the input parameters. Decades of research with stochastic search techniques has shown the benefit of explicitly…
We study future lepton collider prospects for testing predictive models of leptophilic dark matter candidates with a thermal origin. We calculate experimental milestones for testing the parameter space compatible with freeze-out and the…