Search results for "Symbo"
showing 10 items of 7541 documents
First light observations of the solar wind in the outer corona with the Metis coronagraph
2021
In this work, we present an investigation of the wind in the solar corona that has been initiated by observations of the resonantly scattered ultraviolet emission of the coronal plasma obtained with UVCS-SOHO, designed to measure the wind outflow speed by applying Doppler dimming diagnostics. Metis on Solar Orbiter complements the UVCS spectroscopic observations that were performed during solar activity cycle 23 by simultaneously imaging the polarized visible light and the H I Lyman-α corona in order to obtain high spatial and temporal resolution maps of the outward velocity of the continuously expanding solar atmosphere. The Metis observations, taken on May 15, 2020, provide the first H I …
Photometric variability of the Be star CoRoT-ID 102761769
2010
Classical Be stars are rapid rotators of spectral type late O to early A and luminosity class V-III, wich exhibit Balmer emission lines and often a near infrared excess originating in an equatorially concentrated circumstellar envelope, both produced by sporadic mass ejection episodes. The causes of the abnormal mass loss (the so-called Be phenomenon) are as yet unknown. For the first time, we can now study in detail Be stars outside the Earth's atmosphere with sufficient temporal resolution. We investigate the variability of the Be Star CoRoT-ID 102761769 observed with the CoRoT satellite in the exoplanet field during the initial run. One low-resolution spectrum of the star was obtained wi…
Study of a sample of faint Be stars in the exofield of CoRoT
2013
International audience; Context. Be stars are probably the most rapid rotators among stars in the main sequence (MS) and, as such, are excellent candidates to study the incidence of the rotation on the characteristics of their non-radial pulsations, as well as on their internal structure. Pulsations are also thought to be possible mechanisms that help the mass ejection needed to build up the circumstellar disks of Be stars.Aims. The purpose of this paper is to identify a number of faint Be stars observed with the CoRoT satellite and to determine their fundamental parameters, which will enable us to study their pulsation properties as a function of the location in the HR diagram and to searc…
High-resolution stimulated Raman spectroscopy and analysis of the nu2, nu5 and 2 nu6 bands of 34SF6
2006
9 p.Special Issue: Nineteenth Colloquium on High Resolution Molecular Spectroscopy, Salamanca 11–16 September 2005
Structural characterization and chemical composition of aragonite and vaterite in freshwater cultured pearls
2008
AbstractVaterite and aragonite polymorphs in freshwater cultured pearls from mussels of the genus Hyriopsis (Unionidae) were structurally and compositionally characterized by Raman spectroscopy, Micro computer tomography, high resolution field emission scanning electron microscopy, electron microprobe analysis and laser ablation inductively coupled plasma mass spectrometry. The appearance of vaterite in pearls is related to the initial stages of biomineralization, although we demonstrate that vaterite can not be a precursor to aragonite. It is not related to a particular crystal habit and therefore does not have a structural functionality in the pearls. Larger contents of elements typically…
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Automatic emulator and optimized look-up table generation for radiative transfer models
2017
This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…
Multioutput Automatic Emulator for Radiative Transfer Models
2018
This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…
Optimal modalities for radiative transfer-neural network estimation of canopy biophysical characteristics: Evaluation over an agricultural area with …
2011
International audience; Neural networks trained over radiative transfer simulations constitute the basis of several operational algorithms to estimate canopy biophysical variables from satellite reflectance measurements. However, only little attention was paid to the training process which has a major impact on retrieval performances. This study focused on the several modalities of the training process within neural network estimation of LAI, FCOVER and FAPAR biophysical variables. Performances were evaluated over both actual experimental observations and model simulations. The SAIL and PROSPECT radiative transfer models were used here to simulate the training and the synthetic test dataset…
Efficient remote sensing image classification with Gaussian processes and Fourier features
2017
This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.