Observation of the Triplet Spin-Valve Effect in a Superconductor-Ferromagnet Heterostructure

The theory of superconductor-ferromagnet (S-F) heterostructures with two ferromagnetic layers predicts the generation of a long-range, odd-in-frequency triplet pairing at non-collinear alignment (NCA) of the magnetizations of the F-layers. This triplet pairing has been detected in a Nb/Cu41Ni59/nc-Nb/Co/CoOx spin-valve type proximity effect heterostructure, in which a very thin Nb film between the F-layers serves as a normal conducting (nc) spacer. The resistance of the sample as a function of an external magnetic field shows that for not too high fields the system is superconducting at a collinear alignment of the Cu41Ni59 and Co layer magnetic moments, but switches to the normal conducting state at a NCA configuration. This indicates that the superconducting transition temperature Tc for NCA is lower than the fixed measuring temperature. The existence of a minimum Tc, at the NCA regime below that one for parallel or antiparallel alignments of the F-layer magnetic moments, is consistent with the theoretical prediction of a singlet superconductivity suppression by the long-range triplet pairing generation.Comment: 7 pages, 4 fgures, Submitted to Physical Review Letter

A study of the sea level elevation in the Tropical Atlantic as observed in the neighbohoods of the Brazilian Northeast coastline

Our knowledge on the climate of the past still is sufficiently critical, limiting itself in the majority of the times to last the ten thousand years. Still thus, great part of this knowledge is proceeding from results of simulation through computer using numerical modeling (Paleo-modeling). In some few observational cases, as in the case of the GRIP - Greenland Ice Core Project, this knowledge is extended in the maximum, a hundred thousand years. The models are used (and they have certain ability) mainly to explain "the fast" variations of the temperature in the glacial and interglacial periods. It has time sufficiently, the scientific community has called the attention for the harmful effect for the humanity, that they will occur as consequence of a change of the global climate that certainly will come as resulted of the planetary heating that if has verified in the last decades. Among others, the increase of the level of the world-wide oceans, had to the agreed effect of the thawing of polar ice and mountains, consequent liquid water addition, as well as also of the volumetric dilatation of the which had oceanic mass to the increase of the temperature, probably he will be one of the effect more significant than certainly it goes to modify our agreement on the subject. It is tried to show in this article that this time already arrived or it is very close to arrive.Pages: 259-26

Tensor-based time-delay estimation for second and third generation global positioning system

Global Navigation Satellite Systems (GNSS), such as GPS, Galileo, GLONASS, and BeiDou, are vital for safety-critical applications such as civilian aviation and autonomous vehicles. These applications demand very accurate positioning, especially in scenarios in which multipath components are present. In this paper, we propose a semi-algebraic framework for approximate Canonical Polyadic Decomposition via simultaneous matrix diagonalization (SECSI) with Higher Order Singular Value Decomposition (HOSVD) low-rank approximation for time-delay estimation for antenna array based GNSS receivers. The HOSVD-SECSI based approach outperforms all the state-of-the-art tensor-based algorithms for time-delay estimation, mainly, for scenarios with highly correlated or coherent signals and in case of more than two multipath components

Tensor-Based Subspace Tracking for Time-Delay Estimation in GNSS Multi-Antenna Receivers

Although Global Navigation Satellite Systems (GNSS) receivers currently achieve high accuracy when processing their geographic location under line of sight (LOS), multipath interference and noise degrades the accuracy considerably. In order to mitigate multipath interference, receivers based on multiple antennas became the focus of research and technological development. In this context, tensor-based approaches based on Parallel Factor Analysis (PARAFAC) models have been proposed in the literature, providing optimum performance. State-of-the-art techniques for antenna array based GNSS receivers compute singular value decomposition (SVD) for each new sample, implying into a high computational complexity, being, therefore, prohibitive for real-time applications. Therefore, in order to reduce the computational complexity of the parameter estimates, subspace tracking algorithms are essential. In this work, we propose a tensor-based subspace tracking framework to reduce the overall computational complexity of the highly accurate tensor-based time-delay estimation process