Magnetisation dynamics and tuneable GHz properties of unsaturated magnetic nanostructures

In this Thesis, investigations on spin wave propagation in sufficiently thick, magnetic unsaturated nanostructures of various shapes have been carried out. Analytical, numerical and experimental techniques in the time and the frequency domains have been used throughout this thesis. Unsaturated magnetic states are of high interest, more specifically the magnetic vortex configuration since the remanent state is typically dominated and stabilised by the shape anisotropy of the structure, with no need of strong or any bias fields. Due to the diversity of magnetic inhomogeneities, a high degree of reconfigurability by applying external low bias fields can be obtained. On the other hand, the inhomogeneous magnetic landscape becomes, very often, difficult to model analytically and therefore, propagating spin waves can turn out to be complicate to control in practice. The aim of this work has been twofold. Firstly, to explore the most prominent magnetisation dynamics found in thick enough magnetic patches, or ‘2.5-dimensional’ nanostructures. The explored propagating modes are exchange-dominated spin waves in the range of GHz, which allows us to obtain very short wavelength spin waves that can propagate along different ‘paths’ in the unsaturated landscape. The ‘thickness and shape-induced’ enhancing of these spin waves in structures in a flux closure configuration, suggests their use as highly tuneable spin wave emitters. Secondly, analytical and mathematical models are proposed for controlling the spin wave propagation in multidomain structures of various shapes and in domain walls. Their magnetic configuration is dominated by the shape anisotropy of the patch, which allows us to design particularized shapes to control the spin wave wavenumber (or equivalently, wavelength) while it propagates. Also, the modes are shown to be sensitive to bias fields, which further enhances their tuneability and reconfigurability. All this previous work is joint in the last part of the Thesis, more focused on potential applications for Magnonics, where spin waves are not necessarily seen as undesirable energy loss mechanisms in magnetic structures but as information carriers or the base of novel computing paradigms. Single, or interconnected unsaturated elements of various shapes are proposed to be the base of interesting highly tuneable spin wave devices.Engineering and Physical Sciences Research Council (EPSRC

Analysis of the Clearing Diversity-Preserving Mechanism

Clearing is a niching method inspired by the principle of assigning the available resources among a subpopulation to a single individual. The clearing procedure supplies these resources only to the best individual of each subpopulation: the winner. So far, its analysis has been focused on experimental approaches that have shown that clearing is a powerful diversity mechanism. We use empirical analysis to highlight some of the characteristics that makes it a useful mechanism and runtime analysis to explain how and why it is a powerful method. We prove that a (mu+1) EA with large enough population size and a phenotypic distance function always succeeds in optimising all functions of unitation for small niches in polynomial time, while a genotypic distance function requires exponential time. Finally, we prove that a (mu+1) EA with phenotypic and genotypic distances is able to find both optima in TWOMAX for large niches in polynomial expected time

Runtime analysis of crowding mechanisms for multimodal optimisation

Many real-world optimisation problems lead to multimodal domains and require the identification of multiple optima. Crowding methods have been developed to maintain population diversity, to investigate many peaks in parallel and to reduce genetic drift. We present the first rigorous runtime analyses of probabilistic crowding and generalised crowding, embedded in a (mu+1)EA. In probabilistic crowding the offspring compete with their parent in a fitness-proportional selection. Generalised crowding decreases the fitness of the inferior solution by a scaling factor during selection. We consider the bimodal function TwoMax and introduce a novel and natural notion for functions with bounded gradients. For a broad range of such functions we prove that probabilistic crowding needs exponential time with overwhelming probability to find solutions significantly closer to any global optimum than those found by random search. Even when the fitness function is scaled exponentially, probabilistic crowding still fails badly. Only if the exponential's base is linear in the problem size, probabilistic crowding becomes efficient on TwoMax. A similar threshold behaviour holds for generalised crowding on TwoMax with respect to the scaling factor. Our theoretical results are accompanied by experiments for TwoMax showing that the threshold behaviours also apply to the best fitness found

Using Virtual Observatory techniques to search for Adaptive Optics suitable AGN

Until recently, it has been possible only for nearby galaxies to study the scaling relations between central black hole and host galaxy in detail. Because of the small number densities at low redshift, (luminous) AGN are underrepresented in such detailed studies. The advent of adaptive optics (AO) at large telescopes helps overcoming this hurdle, allowing to reach small linear scales over a wide range in redshift. Finding AO-suitable targets, i.e., AGN having a nearby reference star, and carrying out an initial multiwavelength classification is an excellent use case for the Virtual Observatory. We present our Virtual-Observatory approach to select an AO-suitable catalog of X-ray-emitting AGN at redshifts 0.1<z<1.Comment: 4 pages, 5 figures, submitted to "EURO-VO AIDA workshop: Multiwavelength astronomy and Virtual Observatory", ESAC, Spain, 1-3 Dec. 200

Speeding Up Evolutionary Multi-objective Optimisation Through Diversity-Based Parent Selection

Parent selection in evolutionary algorithms for multi-objective optimization is usually performed by dominance mechanisms or indicator functions that prefer non-dominated points, while the reproduction phase involves the application of diversity mechanisms or other methods to achieve a good spread of the population along the Pareto front. We propose to refine the parent selection on evolutionary multi-objective optimization with diversity-based metrics. The aim is to focus on individuals with a high diversity contribution located in poorly explored areas of the search space, so the chances of creating new non-dominated individuals are better than in highly populated areas. We show by means of rigorous runtime analysis that the use of diversity-based parent selection mechanisms in the Simple Evolutionary Multi-objective Optimiser (SEMO) and Global SEMO for the well known bi-objective functions OneMinMax and Lotz can significantly improve their performance. Our theoretical results are accompanied by additional experiments that show a correspondence between theory and empirical results

Collaborative lifelong learning and professional transfer. Case study: ECO European Project

This research reviews the formative model of the sMOOCs (social MOOC) characterized by the interaction and the implication of the participants who, relying on collective intelligence, look for the co-creation of knowledge in every educational action. The fieldwork focuses on the analysis of the “Step by Step” sMOOC of ECO Project (the second and third editions), that aims at the training of e-teachers and the transfer of learning to the professional field. The research methodology is mixed, with quantitative and qualitative techniques: it uses a semi-structured questionnaire, in order to compare possible bivariate correlations between the different variables; it conducts a content analysis of the fragments of messages written by the participants in the forums of the course. One of the most significant conclusions is the high degree of satisfaction of the participants with regard to the value of the course for their professional life. This form of transfer of the learning process leads to the proposal of a new modality for MOOCs, the tMOOC as “transferMOOC”

Geometrical design for pure current-driven domain wall nucleation and shifting

[EN]Nucleation of domain walls by current-driving a single domain wall, confined to the junction area of two symmetrical strips, is investigated using systematic micromagnetic simulations. Secondary domain walls (equivalently, bits encoded in domains) are simultaneously nucleated and driven by alternatively applying current pulses between two terminals in the structure. Simulations show that nanosecond-duration current pulses nucleate and drive series of robust up/down domains even under realistic conditions. These results demonstrate a technique for sequentially nucleating and shifting domain walls without using attached external “bit lines,” fields, or modifying the ferromagnetic strip

Current-Driven Domain Wall Motion in Curved Ferrimagnetic Strips Above and Below the Angular Momentum Compensation

[EN] Current driven domain wall motion in curved Heavy Metal/Ferrimagnetic/Oxide multilayer strips is investigated using systematic micromagnetic simulations which account for spinorbit coupling phenomena. Domain wall velocity and characteristic relaxation times are studied as functions of the geometry, curvature and width of the strip, at and out of the angular momentum compensation. Results show that domain walls can propagate faster and without a significant distortion in such strips in contrast to their ferromagnetic counterparts. Using an artificial system based on a straight strip with an equivalent current density distribution, we can discern its influence on the wall terminal velocity, as part of a more general geometrical influence due to the curved shape. Curved and narrow ferrimagnetic strips are promising candidates for designing high speed and fast response spintronic circuitry based on current-driven domain wall motion.Projects SA114P20 and SA299P18 from Junta de Castilla y Leon (JCyL) MAT2017-87072-C4-1-P and PID2020-117024GB-C41 from the Ministry of Economy, Spanish government MAGNEFI, from the European Commission (European Union