Magnetism of Co overlayers and nanostructures on W(001): A first-principles study

The magnetic properties of Co nanostructures and a Co monolayer on W(001) have been studied in the framework of density functional theory. Different geometries such as planar and three-dimensional clusters have been considered, with cluster sizes varying between 2 and 13 atoms. The calculations were performed using the real-space linear muffin-tin orbital method (RS-LMTO-ASA). With respect to the stability of the magnetic state, we predict an antiferromagnetic (AFM) structure for the ground state of the planar Co clusters and a ferromagnetic (FM) state for the three-dimensional clusters. For the three-dimensional clusters, one of the AFM arrangements leads to frustration due to the competing FM and AFM exchange interactions between different atoms in the cluster, and gives rise to a non-collinear state with energy close to that of the FM ground state. The relative role of the Co-Co and Co-W exchange interactions is also investigated. (C) 2007 Elsevier B.V. All rights reserved.

Hyperfine and magnetic properties of Fe-Cu clusters and Fe precipitates embedded in a Cu matrix

Using the first-principles real-space linear muffin-tin orbital method within the atomic sphere approximation (RS-LMTO-ASA) we study hyperfine and local magnetic properties of substituted pure Fe and Fe-Cu clusters in an fcc Cu matrix. Spin and orbital contributions to magnetic moments, hyperfine fields and the Mossbauer isomer shifts at the Fe sites in Fe precipitates and Fe-Cu alloy clusters of sizes up to 60 Fe atoms embedded in the Cu matrix are calculated and the influence of the local environment on these properties is discussed.

Slicing the metric space to provide quick indexing of complex data in the main memory

Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

Polar orthogonal representations of real reductive algebraic groups

We prove that a polar orthogonal representation of a real reductive algebraic group has the same closed orbits as the isotropy representation of a pseudo-Riemannian symmetric space. We also develop a partial structural theory of polar orthogonal representations of real reductive algebraic groups which slightly generalizes some results of the structural theory of real reductive Lie algebras. (c) 2008 Elsevier Inc. All rights reserved.