Spectropolarimetric analysis of an active region filament. I. Magnetic and dynamical properties from single component inversions

The determination of the magnetic filed vector in solar filaments is possible by interpreting the Hanle and Zeeman effects in suitable chromospheric spectral lines like those of the He I multiplet at 10830 A. We study the vector magnetic field of an active region filament (NOAA 12087). Spectropolarimetric data of this active region was acquired with the GRIS instrument at the GREGOR telescope and studied simultaneously in the chromosphere with the He I 10830 A multiplet and in the photosphere with the Si I 10827 A line. As it is usual from previous studies, only a single component model is used to infer the magnetic properties of the filament. The results are put into a solar context with the help of the Solar Dynamic Observatory images. Some results clearly point out that a more complex inversion had to be done. Firstly, the Stokes $V$ map of He I does not show any clear signature of the presence of the filament. Secondly, the local azimuth map follows the same pattern than Stokes $V$ as if the polarity of Stokes $V$ were conditioning the inference to very different magnetic field even with similar linear polarization signals. This indication suggests that the Stokes $V$ could be dominated by the below magnetic field coming from the active region, and not, from the filament itself. Those and more evidences will be analyzed in depth and a more complex inversion will be attempted in the second part of this series.Comment: 18 pages, 19 figures, accepted for publication in A&

Bayesian inference of solar and stellar magnetic fields in the weak-field approximation

The weak-field approximation is one of the simplest models that allows us to relate the observed polarization induced by the Zeeman effect with the magnetic field vector present on the plasma of interest. It is usually applied for diagnosing magnetic fields in the solar and stellar atmospheres. A fully Bayesian approach to the inference of magnetic properties in unresolved structures is presented. The analytical expression for the marginal posterior distribution is obtained, from which we can obtain statistically relevant information about the model parameters. The role of a-priori information is discussed and a hierarchical procedure is presented that gives robust results that are almost insensitive to the precise election of the prior. The strength of the formalism is demonstrated through an application to IMaX data. Bayesian methods can optimally exploit data from filter-polarimeters given the scarcity of spectral information as compared with spectro-polarimeters. The effect of noise and how it degrades our ability to extract information from the Stokes profiles is analyzed in detail.Comment: 16 pages, 5 figures, accepted for publication in Ap

Hierarchical analysis of the quiet Sun magnetism

Standard statistical analysis of the magnetic properties of the quiet Sun rely on simple histograms of quantities inferred from maximum-likelihood estimations. Because of the inherent degeneracies, either intrinsic or induced by the noise, this approach is not optimal and can lead to highly biased results. We carry out a meta-analysis of the magnetism of the quiet Sun from Hinode observations using a hierarchical probabilistic method. This model allows us to infer the statistical properties of the magnetic field vector over the observed field-of-view consistently taking into account the uncertainties in each pixel due to noise and degeneracies. Our results point out that the magnetic fields are very weak, below 275 G with 95% credibility, with a slight preference for horizontal fields, although the distribution is not far from a quasi-isotropic distribution.Comment: 9 pages, 4 figures, accepted for publication in A&

Analytical maximum likelihood estimation of stellar magnetic fields

The polarised spectrum of stellar radiation encodes valuable information on the conditions of stellar atmospheres and the magnetic fields that permeate them. In this paper, we give explicit expressions to estimate the magnetic field vector and its associated error from the observed Stokes parameters. We study the solar case where specific intensities are observed and then the stellar case, where we receive the polarised flux. In this second case, we concentrate on the explicit expression for the case of a slow rotator with a dipolar magnetic field geometry. Moreover, we also give explicit formulae to retrieve the magnetic field vector from the LSD profiles without assuming mean values for the LSD artificial spectral line. The formulae have been obtained assuming that the spectral lines can be described in the weak field regime and using a maximum likelihood approach. The errors are recovered by means of the hermitian matrix. The bias of the estimators are analysed in depth.Comment: accepted for publication in MNRA

A search for magnetic fields on central stars in planetary nebulae

One of the possible mechanisms responsible for the panoply of shapes in planetary nebulae is the presence of magnetic fields that drive the ejection of ionized material during the proto-planetary nebula phase. Therefore, detecting magnetic fields in such objects is of key importance for understanding their dynamics. Still, magnetic fields have not been detected using polarimetry in the central stars of planetary nebulae. Circularly polarized light spectra have been obtained with the Focal Reducer and Low Dispersion Spectrograph at the Very Large Telescope of the European Southern Observatory and the Intermediate dispersion Spectrograph and Imaging System at the William Herschel Telescope. Nineteen planetary nebulae spanning very different morphology and evolutionary stages have been selected. Most of central stars have been observed at different rotation phases to point out evidence of magnetic variability. In this paper, we present the result of two observational campaigns aimed to detect and measure the magnetic field in the central stars of planetary nebulae on the basis of low resolution spectropolarimetry. In the limit of the adopted method, we can state that large scale fields of kG order are not hosted on the central star of planetary nebulae.Comment: Paper accepted to be published in Astronomy and Astrophysics on 20/01/201

Análisis de los suelos del piedemoente de la vertiente norte de la Sierra de Alhama (Granada, España)

[Resumen] El piedemonte que enlaza la sierra de Alhama y el poljé de Zafarraya puede considerarse como un glacis incipiente sobre el que desarrollan suelos cuya morfología es heredada del material parental. Los suelos son mayoritariamente Gleysoles y Regosoles, con o sin carbonatos, arcillosos y de fuerte consistencia, motivo que asociado al relieve justifica el alto índice de erosionabilidad y el que exijan un serio acondicionamiento para ser usado agricolamente. Dada la posición fisiográfica y la propia naturaleza edáfica, también se utiliza el terreno para almacenar agua de lluvia destinada a riego. En cuanto a la génesis, son suelos poco Desarrolla dos y el hecho evolutivo más significativo es la transformación de la arcilla heredada (ilita-interestratificados-esmectita).[Abstract] The footslope in between Alhama mountain rouge and Zafarraya polje could be considered as an incipient glacis which shows soil with an inherited morphology from the parent material developing over it. Soils are mainly Gleysols and Regosols, with or without carbonates, clayed and with a strong consistence; these characteristics asociated to relief are the justification of the high erodibility index and the excigence of a serious arranging to be farmerly used. With the fisiographic position and own edaphic nature given, even the land use could be in order to store rainfall water for irrigation. For genetical studies, these are low developed soils and the most significant thing in their evolution is the inherated clay transformation (illite-interstratified-smectite)

PCA detection and denoising of Zeeman signatures in stellar polarised spectra

Our main objective is to develop a denoising strategy to increase the signal to noise ratio of individual spectral lines of stellar spectropolarimetric observations. We use a multivariate statistics technique called Principal Component Analysis. The cross-product matrix of the observations is diagonalized to obtain the eigenvectors in which the original observations can be developed. This basis is such that the first eigenvectors contain the greatest variance. Assuming that the noise is uncorrelated a denoising is possible by reconstructing the data with a truncated basis. We propose a method to identify the number of eigenvectors for an efficient noise filtering. Numerical simulations are used to demonstrate that an important increase of the signal to noise ratio per spectral line is possible using PCA denoising techniques. It can be also applied for detection of magnetic fields in stellar atmospheres. We analyze the relation between PCA and commonly used well-known techniques like line addition and least-squares deconvolution. Moreover, PCA is very robust and easy to compute.Comment: accepted to be published in A&

Bayesian Inversion of Stokes Profiles

[abridged] Inversion techniques are the most powerful methods to obtain information about the thermodynamical and magnetic properties of solar and stellar atmospheres. In the last years, we have witnessed the development of highly sophisticated inversion codes that are now widely applied to spectro-polarimetric observations. The majority of these inversion codes are based on the optimization of a complicated non-linear merit function. However, no reliable and statistically well-defined confidence intervals can be obtained for the parameters inferred from the inversions. A correct estimation of the confidence intervals for all the parameters that describe the model is mandatory. Additionally, it is fundamental to apply efficient techniques to assess the ability of models to reproduce the observations and to what extent the models have to be refined or can be simplified. Bayesian techniques are applied to analyze the performance of the model to fit a given observed Stokes vector. The posterior distribution, is efficiently sampled using a Markov Chain Monte Carlo method. For simplicity, we focus on the Milne-Eddington approximate solution of the radiative transfer equation and we only take into account the generation of polarization through the Zeeman effect. However, the method is extremely general and other more complex forward models can be applied. We illustrate the ability of the method with the aid of academic and realistic examples. We show that the information provided by the posterior distribution turns out to be fundamental to understand and determine the amount of information available in the Stokes profiles in these particular cases.Comment: 15 pages, 12 figures, accepted for publication in A&