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The introduction of the Segment Anything Model (SAM) has paved the way for numerous semantic segmentation applications. For several tasks, quantifying the uncertainty of SAM is of particular interest. However, the ambiguous nature of the…
We discuss the phenomenology of models of dynamical electroweak symmetry breaking which attempt to generate the observed fermion mass spectrum. After briefly describing the variety of and constraints on proposed models, we concentrate on…
The NuTeV collaboration has extracted the electroweak parameter, $\stw$, from the measurement of the ratios of neutral current to charged current neutrino and antineutrino deep inelastic scattering interactions. We find that our…
I briefly review the basic challenges and virtues of models breaking the electroweak symmetry dynamically. I will then introduce the (ultra) minimal walking technicolor models whose construction has been made possible thanks to recent…
The standard model (SM) of particle physics represents a theoretical paradigm for the description of the fundamental forces of nature. Despite its broad applicability, the SM does not enable the description of all physically possible…
We study the gravitational waves (GWs) spectrum produced during the electroweak phase transition in a scale-invariant extension of the Standard Model (SM), enlarged by a dark $ U(1)_{D} $ gauge symmetry. This symmetry incorporates a vector…
The aim of the thesis is to study models of the electroweak symmetry breaking caused by dynamically generated masses of quarks and leptons. (1) We perform the basic analysis whether the main underlying idea, that the masses of only known…
The NuTeV collaboration has performed precision measurements of the ratio of neutral current to charged current cross-sections in high rate, high energy neutrino and anti-neutrino beams on a dense, primarily steel, target. The separate…
We study the electroweak and $U(1)^{'}$ symmetry breaking patterns in models with the particle content of supersymmetric $E_{6}$, including standard model singlets $S$ and exotic quarks $D,~\bar{D}$. Motivated by free fermionic string…
The NuTeV anomaly of a non-universal value of the fundamental parameter sin^2\theta_W in the electroweak theory has been interpreted as an indication for new physics beyond the Standard Model. However, the observed quantity depends on a…
A predictive framework for supersymmetry at the TeV scale is presented, which incorporates the Ciafaloni-Pomarol mechanism for the dynamical determination of the \mu parameter of the MSSM. It is replaced by (\lambda S), where S is a singlet…
Techniques from artificial intelligence and machine learning are increasingly employed in nuclear theory, however, the uncertainties that arise from the complex parameter manifold encoded by the neural networks are often overlooked.…
Gravitational waves from the collision of binary neutron stars provide a unique opportunity to study the behaviour of supranuclear matter, the fundamental properties of gravity, and the cosmic history of our Universe. However, given the…
In this thesis we investigated, at partonic level and leading order, the LHC potencial operating with $\sqrt{s}=14$ TeV and integrated luminosity of $L=100\;{fb}^{-1}$ to probe "pure" (without triple vertex contributions) anomalous…
To fully understand, analyze, and determine the behavior of dynamical systems, it is crucial to identify their intrinsic modal coordinates. In nonlinear dynamical systems, this task is challenging as the modal transformation based on the…
Recognizing the potential of effective field theories to posit multiple BSM scenarios in similar footing, with a possibility to compare them, we inspect the effects of 11 single scalar-multiplet extensions of the SM on the combined set of…
We describe a computational framework linking Uncertainty Quantification (UQ) methods for continuum problems depending on random parameters with Equation-Free (EF) methods for performing continuum deterministic numerics by acting directly…
The past decade has witnessed tremendous progress in the theoretical and computational tools that produce our understanding of nuclei. A number of microscopic calculations of nuclear electroweak structure and reactions have successfully…
Machine-learning models can be fooled by adversarial examples, i.e., carefully-crafted input perturbations that force models to output wrong predictions. While uncertainty quantification has been recently proposed to detect adversarial…
With the increased prevalence of neural operators being used to provide rapid solutions to partial differential equations (PDEs), understanding the accuracy of model predictions and the associated error levels is necessary for deploying…