Related papers: Exploring Scotogenic Parameter Spaces and Mapping …
The scotogenic model is one of the simplest scenarios for physics beyond the Standard Model that can account for neutrino masses and dark matter at the TeV scale. It contains another scalar doublet and three additional singlet fermions…
We study a 3-Higgs Doublet Model (3HDM) with an imposed Z3 symmetry, allowing for two Inert scalar doublets and one active Higgs doublet. The WIMP dark matter candidates correspond to two mass-degenerate states, H1 and A1, which possess…
We present a minimal sub-GeV thermal Dark Matter (DM) model where the DM primarily interacts with neutrinos and participates in neutrino mass generation through quantum loop corrections at one-loop level. We discuss the challenges in…
In complex simulation environments, certain parameter space regions may result in non-convergent or unphysical outcomes. All parameters can therefore be labeled with a binary class describing whether or not they lead to valid results. In…
We propose a multi-objective global pattern search algorithm for the task of locating and quantifying damage in flexible mechanical structures. This is achieved by identifying eigenfrequencies and eigenmodes from measurements and matching…
Non-zero neutrino mass and dark matter cast a shadow over the success of the Standard Model (SM) of Particle Physics. The most straightforward extension of the SM to explain these two phenomena is the Scotogenic model, where the SM particle…
In this work we are interested in stochastic particle methods for multi-objective optimization. The problem is formulated using parametrized, single-objective sub-problems which are solved simultaneously. To this end a consensus based…
Scotogenic models are among the most elegant and economic solutions that provide an explanation for two of the main open questions in particle physics: neutrino masses and dark matter (DM). In this work, after a brief discussion of the…
We present a novel Artificial Intelligence approach for Beyond the Standard Model parameter space scans by augmenting an Evolutionary Strategy with Novelty Detection. Our approach leverages the power of Evolutionary Strategies, previously…
We present a Python package together with a practical guide for the implementation of a lightweight diversity-enhanced genetic algorithm (GA) approach for the exploration of multi-dimensional parameter spaces. Searching a parameter space…
We introduce a two real scalar singlet extension of the two Higgs doublet model. We study the vacuum structure, the bounded from below conditions, the restrictions from the oblique parameters S,T and U, as well as the unitarity constraints.…
In this review statistical issues appearing in astrophysical searches for particle dark matter, i.e. indirect detection (dark matter annihilating into standard model particles) or direct detection (dark matter particles scattering in deep…
We propose the simplest possible renormalizable extension of the Standard Model - the addition of just one singlet scalar field - as a minimalist model for non-baryonic dark matter. Such a model is characterized by only three parameters in…
Discarding the prejudice about fine tuning, we propose a novel and efficient approach to identify relevant regions of fundamental parameter space in supersymmetric models with some amount of fine tuning. The essential idea is the mapping of…
Scotogenic models constitute an appealing solution to the generation of neutrino masses and to the dark matter mystery. In this work we consider a version of the Scotogenic model that breaks lepton number spontaneously. At this scope, we…
We perform a complete analysis of the consistency of the singlet-triplet scotogenic model, where both dark matter and neutrino masses can be explained. We determine the parameter space that yields the proper thermal relic density been in…
Automated decision-making is becoming key for automated characterization including electron and scanning probe microscopies and nano indentation. Most machine learning driven workflows optimize a single predefined objective and tend to…
The scotogenic model can simultaneously account for the presence of dark matter and the origin of neutrino masses. We assume that the flavor neutrino mass matrix has one zero element and Yukawa matrix elements are real in the scotogenic…
Meta-heuristics are powerful tools for solving optimization problems whose structural properties are unknown or cannot be exploited algorithmically. We propose such a meta-heuristic for a large class of optimization problems over discrete…
Addressing the issue of SVMs parameters optimization, this study proposes an efficient memetic algorithm based on Particle Swarm Optimization algorithm (PSO) and Pattern Search (PS). In the proposed memetic algorithm, PSO is responsible for…