On the use of machine learning algorithms in the measurement of stellar magnetic fields

Regression methods based in Machine Learning Algorithms (MLA) have become an important tool for data analysis in many different disciplines. In this work, we use MLA in an astrophysical context; our goal is to measure the mean longitudinal magnetic field in stars (H_ eff) from polarized spectra of high resolution, through the inversion of the so-called multi-line profiles. Using synthetic data, we tested the performance of our technique considering different noise levels: In an ideal scenario of noise-free multi-line profiles, the inversion results are excellent; however, the accuracy of the inversions diminish considerably when noise is taken into account. In consequence, we propose a data pre-process in order to reduce the noise impact, which consists in a denoising profile process combined with an iterative inversion methodology. Applying this data pre-process, we have found a considerable improvement of the inversions results, allowing to estimate the errors associated to the measurements of stellar magnetic fields at different noise levels. We have successfully applied our data analysis technique to two different stars, attaining by first time the measurement of H_eff from multi-line profiles beyond the condition of line autosimilarity assumed by other techniques.Comment: Accepted for publication in A&

Mathematical theory of the Goddard trajectory determination system

Basic mathematical formulations depict coordinate and time systems, perturbation models, orbital estimation techniques, observation models, and numerical integration methods

Within and Between Group Variation of Individual Strategies in Common Pool Resources: Evidence from Field Experiments

With data from framed common pool resource experiments conducted with artisanal fishing communities in Colombia, we estimate a hierarchical linear model to investigate within-group and between-group variation in individual harvest strategies across several institutions. Our results suggest that communication serves to effectively coordinate individual strategies within groups, but that these coordinated strategies vary considerably across groups. In contrast, weakly enforced regulatory restrictions on individual harvests (as well as unregulated open access) produce significant variation in the individual strategies within groups, but these strategies are roughly replicated across groups so that there is little between-group variation.common pool resources, field experiments, communication, regulation, hierarchical linear models

Centralized and Decentralized Management of Local Common Pool Resources in the Developing World: Experimental Evidence from Fishing Communities in Colombia

This paper uses experimental data to test for a complementary relationship between formal regulations imposed on a community to conserve a local natural resource and nonbinding verbal agreements to do the same. Our experiments were conducted in the field in three regions of Colombia. Each group of five subjects played 10 rounds of an open access common pool resource game, and 10 additional rounds under one of five institutions— communication alone, two external regulations that differed by the level of enforcement, and communication combined with each of the two regulations. Our results suggest that the hypothesis of a complementary relationship between communication and external regulation is supported for some combinations of regions and regulations, but cannot be supported in general. We therefore conclude that the determination of whether formal regulations and informal communication are complementary must be made on a community-by-community basis.common pool resources, experiments, institutions, communication, regulation