Related papers: Exploring Scotogenic Parameter Spaces and Mapping …
The problem of detecting anomalies in multiple processes is considered. We consider a composite hypothesis case, in which the measurements drawn when observing a process follow a common distribution with an unknown parameter (vector), whose…
In supersymmetric models with Dirac neutrinos, the lightest sneutrino can be an excellent thermal dark matter candidate when the soft sneutrino trilinear parameter is large. We focus on scenarios where the mass of the mixed sneutrino is of…
Understanding dark matter's elusive nature is crucial for the framework of particle physics and expanding the Standard Model. This analysis utilizes the High Altitude Water Cherenkov (HAWC) gamma ray Observatory to indirectly search for…
Population-based evolutionary algorithms have great potential to handle multiobjective optimisation problems. However, these algorithms depends largely on problem characteristics, and there is a need to improve their performance for a wider…
This study focuses on a combined analysis of various available inputs to constrain the parameter spaces of a simplified dark matter (SDM) model featuring a spin-0 mediator and fermionic dark matter (DM). The spin-0 mediator interacts with…
We consider the optimization of an uncertain objective over continuous and multi-dimensional decision spaces in problems in which we are only provided with observational data. We propose a novel algorithmic framework that is tractable,…
We introduce an optimization technique to discriminate signal and background in any phenomeno- logical study based on the cut and count-based method. The core ideas behind this technique are the introduction of a ranking scheme that can…
In this letter, we propose an extension of the scotogenic model where singlet Majorana particle can be dark matter (DM) without the need of a highly suppressed scalar coupling of the order $O(10^{-10})$. For that, the SM is extended with…
An extended seesaw model proposed to achieve low scale leptogenesis can resolve the excess positron and electron fluxes observed from PAMELA, ATIC and/or Fermi-LAT, and simultaneously accommodate some of recent experimental results for dark…
In solving multi-modal, multi-objective optimization problems (MMOPs), the objective is not only to find a good representation of the Pareto-optimal front (PF) in the objective space but also to find all equivalent Pareto-optimal subsets…
Constraining theoretical models with measuring the parameters of those from cosmic microwave background (CMB) anisotropy data is one of the most active areas in cosmology. WMAP, Planck and other recent experiments have shown that the six…
Precision measures of electroweak and flavour observables, at both low and high energies, are highly complementary to direct searches for New Physics at high-energy colliders. Despite the discovery of the Higgs boson at the Large Hadron…
Scotogenic models are among the most popular possibilities to link dark matter and neutrino masses. In this work we discuss a variant of the Scotogenic model that includes charged fermions and a doublet with hypercharge $3/2$. Neutrino…
We present an algorithm for multi-objective optimization of computationally expensive problems. The proposed algorithm is based on solving a set of surrogate problems defined by models of the real one, so that only solutions estimated to be…
This paper introduces a high-performance hybrid algorithm, called Hybrid Hypervolume Maximization Algorithm (H2MA), for multi-objective optimization that alternates between exploring the decision space and exploiting the already obtained…
The Standard Model of particle physics has been strengthened by the recent discovery of the long-awaited Higgs boson. The standard cosmological model has met the challenge of the high precision observations in cosmology and astroparticle…
Finding global optima in high-dimensional optimization problems is extremely challenging since the number of function evaluations required to sufficiently explore the search space increases exponentially with its dimensionality.…
We study the fundamental problem of selecting optimal features for model construction. This problem is computationally challenging on large datasets, even with the use of greedy algorithm variants. To address this challenge, we extend the…
Applying a likelihood analysis to the next-to-minimal supergravity-motivated model, we identify parameter space regions preferred by present experimental limits from collider, astrophysical, and low energy measurements. We then show that…
We study a feebly interacting massive particle realization of the Scotogenic Dirac Model in which the lightest neutral fermion $N_1$ serves as a dark matter candidate, produced via the freeze-in or super-WIMP mechanism. The model generates…