In this paper, we study risk-averse models for multicriteria optimization problems under uncertainty. We use a weighted sum-based scalarization and take a robust approach by considering a set of scalarization vectors to address the ambiguity and inconsistency in the relative weights of each criterion. We model the risk aversion of the decision makers via the concept of multivariate conditional ...

The spontaneous scalarization during the stellar core collapse in massive scalar-tensor theories of gravity introduces extra polarizations (on top plus and cross modes) gravitational waves, whose amplitudes are determined by several model parameters. Observations such scalarization-induced waveforms therefore offer valuable probes into these gravity. Considering a triple-scalar interactions the...

Even though black hole scalarization is extensively studied recently, little has been done in the direction of understanding dynamics this process, especially rapidly rotating regime. In present paper, we focus exactly on problem by considering nonlinear scalar field while neglecting backreaction spacetime metric. This approach proven to give good results various scenarios and have explicitly d...

We study spontaneous scalarization of electrically charged extremal black holes in $D\geq 4$ spacetime dimensions. Such a phenomenon is caused by the symmetry breaking due to quartic interactions scalar -- Higgs potential and Stueckelberg interaction with electromagnetic gravitational fields, characterized couplings $a$ $b$, respectively. use entropy representation states vicinity horizon, appl...

Furstenberg [7] and Lyons and Sullivan [14] have shown how to discretize harmonic functions on a Riemannian manifold M whose Brownian motion satisfies a certain recurrence property called ∗-recurrence. We study analogues of this discretization for tensor fields which are harmonic in the sense of the covariant Laplacian. We show that, under certain restrictions on the holonomy of the connection,...

In this work, it is described a gait multiobjective optimization system that allows to obtain fast but stable robot quadruped crawl gaits. We combine bioinspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). A motion architecture based on CPGs oscillators is used to model the locomotion of the robot dog and a GA is used to search parameterizations of the CPGs parameters which ...