Machine learning techniques to select Be star candidates. An application in the OGLE-IV Gaia south ecliptic pole field

Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to train an automatic classification system. Quantities related to the magnitude density of the light curves and their Fourier coefficients have been chosen as features in previous studies. However, some of these features are not robust to the presence of outliers and the calculation of Fourier coefficients is computationally expensive for large data sets. We propose and evaluate the performance of a new robust set of features using supervised classifiers in order to look for new Be star candidates in the OGLE-IV Gaia south ecliptic pole field. We calculated the proposed set of features on six types of variable stars and on a set of Be star candidates reported in the literature. We evaluated the performance of these features using classification trees and random forests along with K-nearest neighbours, support vector machines, and gradient boosted trees methods. We tuned the classifiers with a 10-fold cross-validation and grid search. We validated the performance of the best classifier on a set of OGLE-IV light curves and applied this to find new Be star candidates. The random forest classifier outperformed the others. By using the random forest classifier and colour criteria we found 50 Be star candidates in the direction of the Gaia south ecliptic pole field, four of which have infrared colours consistent with Herbig Ae/Be stars. Supervised methods are very useful in order to obtain preliminary samples of variable stars extracted from large databases. As usual, the stars classified as Be stars candidates must be checked for the colours and spectroscopic characteristics expected for them

Nearest-Neighbor Distributions and Tunneling Splittings in Interacting Many-Body Two-Level Boson Systems

We study the nearest-neighbor distributions of the $k$-body embedded ensembles of random matrices for $n$ bosons distributed over two-degenerate single-particle states. This ensemble, as a function of $k$, displays a transition from harmonic oscillator behavior ($k=1$) to random matrix type behavior ($k=n$). We show that a large and robust quasi-degeneracy is present for a wide interval of values of $k$ when the ensemble is time-reversal invariant. These quasi-degenerate levels are Shnirelman doublets which appear due to the integrability and time-reversal invariance of the underlying classical systems. We present results related to the frequency in the spectrum of these degenerate levels in terms of $k$, and discuss the statistical properties of the splittings of these doublets.Comment: 13 pages (double column), 7 figures some in color. The movies can be obtained at http://link.aps.org/supplemental/10.1103/PhysRevE.81.03621

On the Reduced SU(N) Gauge Theory in the Weyl-Wigner-Moyal Formalism

Weyl-Wigner-Moyal formalism is used to describe the large-$N$ limit of reduced SU$(N)$ quenching gauge theory. Moyal deformation of Schild-Eguchi action is obtained.Comment: 24 pages, phyzzx file, no figures, version to appear in Int. J. Mod. Phys.

Two-particle quantum correlations in stochastically-coupled networks

Quantum walks in dynamically-disordered networks have become an invaluable tool for understanding the physics of open quantum systems. In this work, we introduce a novel approach to describe the dynamics of indistinguishable particles in noisy quantum networks. By making use of stochastic calculus, we derive a master equation for the propagation of two non-interacting correlated particles in tight-binding networks affected by off-diagonal dynamical disorder. We show that the presence of noise in the couplings of a quantum network creates a pure-dephasing-like process that destroys all coherences in the single-particle Hilbert subspace. Remarkably, we find that when two or more correlated particles propagate in the network, coherences accounting for particle indistinguishability are robust against the impact of noise, thus showing that it is possible, in principle, to find specific conditions for which many indistinguishable particles can traverse dynamically-disordered systems without losing their ability to interfere. These results shed light on the role of particle indistinguishability in the preservation of quantum coherence in dynamically-disordered quantum networks.Comment: 15 pages, 4 figure

Agronomic Evaluation of Twenty Ecotypes of \u3cem\u3eLeucaena\u3c/em\u3e spp. for Acid Soil Conditions in México

Leucaena leucocephala Lam. (de Witt) has been shown to be a good forage producer and to posses good persistence under grazing conditions in México tolerating well the management of local cattlemen (Quero et al., 2004). The Leucaena genus is native to Central America and Mexico (Hughes, 1998), but L. leucocephala is a low producer under acid soil conditions. The natural diversity is a good source of resistance to acid soil conditions resistance and to other adverse factors. Several Leucaena accessions were evaluated for production under acid soil conditions in tropical Mexico

Spontaneous Symmetry Breakdown in non-relativistic Quantum Mechanics

The advantages and disadvantages of some pedagogical non-relativistic quantum-mechanical models, used to illustrate spontaneous symmetry breakdown, are discussed. A simple quantum-mechanical toy model (a spinor on the line, subject to a magnetostatic interaction) is presented, that exhibits the spontaneous breakdown of an internal symmetry.Comment: 19 pages, 5 figures. arXiv admin note: substantial text overlap with arXiv:1111.1213. Equations (30) and (31) have been corrected. Other minor correction

Dynamics of Serial Manipulators using Dual Quaternion Algebra

This paper presents two approaches to obtain the dynamical equations of serial manipulators using dual quaternion algebra. The first one is based on the recursive Newton-Euler formulation and uses twists and wrenches instead of 3D vectors, which simplifies the classic procedure by removing the necessity of exhaustive geometrical analyses since wrenches and twists are propagated through high-level algebraic operations. Furthermore, the proposed formulation works for arbitrary types of joints and does not impose any particular convention for the propagation of twists. The second approach, based on Gauss's Principle of Least Constraint (GPLC), takes into account elements of the dual quaternion algebra and provides a linear relationship between twists derivatives and joint accelerations, which can be particularly useful in robot control. Differently from other approaches based on the GPLC, which have representational singularities or require constraints, our method does not have those drawbacks. We present a thorough methodology to obtain the computational cost of both algorithms and compared them with their classic counterparts. Although our current formulations are more computationally expensive, they are more general than their counterparts in the state of the art. Simulation results showed that both methods are as accurate as the classic recursive Newton-Euler algorithm.Comment: Submitted for publication (currently under review