Non-collinear Magnetic Textures Studied by Neutron Scattering

Non-collinear magnetic structures, where the magnetic moments do not align along a single axis, can lead to interesting physical phenomena and potential device applications. In this dissertation, two specific non-collinear magnetic textures are studied which includes soft/hard bilayer and skyrmions. Soft/hard magnetic bilayer thin films have been widely used in data storage technologies and permanent magnet applications. Here, we use polarized neutron reflectometry (PNR) to study magnetic configuration in soft-hard bilayer heterostructure thin films designed with different sample geometry and material properties under a range of temperatures and fields. Comparing the PNR results to the micromagnetic simulations reveals that the interfacial magnetic configuration is highly dependent on thickness and saturation magagnetization of soft layer materials and external factors (field and temperature) and has a relatively weak dependence on hard layer properties. Magnetic skyrmions, another example of non-collinear structures, exhibit unique, technologically relevant pseudo-particle behaviors which arise from their topological protection, including well-defined, three-dimensional dynamic modes that occur at microwave frequencies. In this work, we use small angle neutron scattering (SANS) to capture the dynamics in hybrid skyrmions and investigate the spin wave structure. Performing simultaneous ferromagnetic resonance and SANS, the diffraction pattern shows a large increase in low-angle scattering which is present only in the resonance condition. This scattering pattern is best fit using a mass fractal model, which suggests the spin waves form a long-range fractal network. Overall, this dissertation contributes to a deeper understanding of the complex behavior and potential applications of non-collinear magnetic structures, particularly in soft/hard bilayer heterostructures and magnetic skyrmions

Deductive Optimization of Relational Data Storage

Optimizing the physical data storage and retrieval of data are two key database management problems. In this paper, we propose a language that can express a wide range of physical database layouts, going well beyond the row- and column-based methods that are widely used in database management systems. We use deductive synthesis to turn a high-level relational representation of a database query into a highly optimized low-level implementation which operates on a specialized layout of the dataset. We build a compiler for this language and conduct experiments using a popular database benchmark, which shows that the performance of these specialized queries is competitive with a state-of-the-art in memory compiled database system

Towards Certain Fixes with Editing Rules and Master Data

A variety of integrity constraints have been studied for data cleaning. While these constraints can detect the presence of errors, they fall short of guiding us to correct the errors. Indeed, data repairing based on these constraints may not find certain fixes that are absolutely correct, and worse, may introduce new errors when repairing the data. We propose a method for finding certain fixes, based on master data, a notion of certain regions , and a class of editing rules . A certain region is a set of attributes that are assured correct by the users. Given a certain region and master data, editing rules tell us what attributes to fix and how to update them. We show how the method can be used in data monitoring and enrichment. We develop techniques for reasoning about editing rules, to decide whether they lead to a unique fix and whether they are able to fix all the attributes in a tuple, relative to master data and a certain region. We also provide an algorithm to identify minimal certain regions, such that a certain fix is warranted by editing rules and master data as long as one of the regions is correct. We experimentally verify the effectiveness and scalability of the algorithm. </jats:p