Rhodium and copper 6-methylpicolinate complexes. Structural diversity and supramolecular interaction study

Seven new coordination compounds with 6-methylpicolinic acid (6-HMepic) and rhodium(III) or copper(II) of formula [Rh(6-Mepic)3] (1), [Rh(6-Mepic)2(H2O)Cl] (2), [Rh(6-HMepic)(6-Mepic)Cl2]·3.5(H2O) (3), [Cu(6-Mepic)2(H2O)]·H2O (4), [Cu(6-Mepic)2]n, (5), [Cu(6-Mepic)(6-HMepic)I] (6) and [Cu(6-Mepic)(6-HMepic)Cl] (7) have been obtained. Their syntheses have been rationalized, and their structural and supramolecular characteristics have been studied and compared with other similar rhodium and copper picolinate complexes previously reported, in order to stablish structural correlations and analogies. The electrical properties of coordination polymer [Cu(6-Mepic)2]n (5) have been also analyzed and it has been found that it shows a moderated electrical transport along the chain.We thank the financial support from the Spanish Ministerio de Economía y Competitividad (MAT2013-46502-C2-2P and MAT2013-46753-C2-1P). Also the scientific computing center (CCC) of the Autonoma University of Madrid for their tim

Scattering of surface plasmons by one-dimensional periodic nanoindented surfaces

In this work, the scattering of surface plasmons by a finite periodic array of one-dimensional grooves is theoretically analyzed by means of a modal expansion technique. We have found that the geometrical parameters of the array can be properly tuned to achieve optimal performance of the structure either as a Bragg reflector or as a converter of surface plasmons into light. In this last case, the emitted light is collimated within a few degrees cone. Importantly, we also show that a small number of indentations in the array are sufficient to fully achieve its functional capabilities.Comment: 5 pages, 5 figures; changed sign convention in some definition

A Comparative Study on the Use of Classification Algorithms in Financial Forecasting

Financial forecasting is a vital area in computational finance, where several studies have taken place over the years. One way of viewing financial forecasting is as a classification problem, where the goal is to find a model that represents the predictive relationships between predictor attribute values and class attribute values. In this paper we present a comparative study between two bio-inspired classification algorithms, a genetic programming algorithm especially designed for financial forecasting, and an ant colony optimization one, which is designed for classification problems. In addition, we compare the above algorithms with two other state-of-the-art classification algorithms, namely C4.5 and RIPPER. Results show that the ant colony optimization classification algorithm is very successful, significantly outperforming all other algorithms in the given classification problems, which provides insights for improving the design of specific financial forecasting algorithms

Entanglement detection in coupled particle plasmons

When in close contact, plasmonic resonances interact and become strongly correlated. In this work we develop a quantum mechanical model, using the language of continuous variables and quantum information, for an array of coupled particle plasmons. This model predicts that when the coupling strength between plasmons approaches or surpasses the local dissipation, a sizable amount of entanglement is stored in the collective modes of the array. We also prove that entanglement manifests itself in far-field images of the plasmonic modes, through the statistics of the quadratures of the field, in what constitutes a novel family of entanglement witnesses. This protocol is so robust that it is indeed independent of whether our own model is correct. Finally, we estimate the amount of entanglement, the coupling strength and the correlation properties for a system that consists of two or more coupled nanospheres of silver, showing evidence that our predictions could be tested using present-day state-of-the-art technology.Comment: 8 pages (6 main text + 2 supplemental), 3 figure