Transformations for compositional data with zeros with an application to forensic evidence evaluation

In forensic science likelihood ratios provide a natural way of computing the value of evidence under competing propositions such as "the compared samples have originated from the same object" (prosecution) and "the compared samples have originated from different objects" (defence). We use a two-level multivariate likelihood ratio model for comparison of forensic glass evidence in the form of elemental composition data under three data transformations: the logratio transformation, a complementary log-log type transformation and a hyperspherical transformation. The performances of the three transformations in the evaluation of evidence are assessed in simulation experiments through use of the proportions of false negatives and false positives

Atmospheric Retrieval for Super-Earths: Uniquely Constraining the Atmospheric Composition with Transmission Spectroscopy

We present a retrieval method based on Bayesian analysis to infer the atmospheric compositions and surface or cloud-top pressures from transmission spectra of exoplanets with general compositions. In this study, we identify what can unambiguously be determined about the atmospheres of exoplanets from their transmission spectra by applying the retrieval method to synthetic observations of the super-Earth GJ 1214b. Our approach to infer constraints on atmospheric parameters is to compute their joint and marginal posterior probability distributions using the MCMC technique in a parallel tempering scheme. A new atmospheric parameterization is introduced that is applicable to general atmospheres in which the main constituent is not known a priori and clouds may be present. Our main finding is that a unique constraint of the mixing ratios of the absorbers and up to two spectrally inactive gases (such as N2 and primordial H2+He) is possible if the observations are sufficient to quantify both (1) the broadband transit depths in at least one absorption feature for each absorber and (2) the slope and strength of the molecular Rayleigh scattering signature. The surface or cloud-top pressure can be quantified if a surface or cloud deck is present. The mean molecular mass can be constrained from the Rayleigh slope or the shapes of absorption features, thus enabling to distinguish between cloudy hydrogen-rich atmospheres and high mean molecular mass atmospheres. We conclude, however, that without the signature of Rayleigh scattering--even with robustly detected infrared absorption features--there is no reliable way to tell if the absorber is the main constituent of the atmosphere or just a minor species with a mixing ratio of <0.1%. The retrieval method leads us to a conceptual picture of which details in transmission spectra are essential for unique characterizations of well-mixed atmospheres.Comment: 23 pages, 13 figures, accepted at ApJ, submitted to ApJ on Nov 4, 201

Organic Carbon Burial following the Middle Eocene Climatic Optimum (MECO) in the central - western Tethys

We present trace metal geochemistry and stable isotope records for the middle Eocene Alano di Piave section, NE Italy, deposited during magnetochron C18n in the marginal Tethys Ocean. We identify a $\sim$ 500 kyr long carbon isotope perturbation event we infer to be the middle Eocene Climatic Optimum (MECO) confirming the northern hemisphere expression and global occurrence of MECO. Interpreted peak climatic conditions are followed by the rapid deposition of two organic rich intervals ($\le$3\% TOC) and contemporaneous positive $\delta^{13}$C excursions. These two intervals are associated with increases in the concentration of sulphur and redox-sensitive trace metals, and low concentrations of Mn, as well as coupled with the occurrence of pyrite. Together these changes imply low, possibly dysoxic, bottom water O$_{2}$ conditions promoting increased organic carbon burial. We hypothesize that this rapid burial of organic carbon lowered global {\it p}CO$_{2}$ following the peak warming and returned the climate system to the general Eocene cooling trend

The Earliest Phases of Galaxy Evolution

In this paper we study the very early phases of the evolution of our Galaxy by means of a chemical evolution model which reproduces most of the observational constraints in the solar vicinity and in the disk. We have restricted our analysis to the solar neighborhood and present the predicted abundances of several elements (C, N, O, Mg, Si, S, Ca, Fe) over an extended range of metallicities $[Fe/H] = -4.0$ to $[Fe/H] = 0.0$ compared to previous models. We adopted the most recent yield calculations for massive stars taken from different authors (Woosley & Weaver 1995 and Thielemann et al. 1996) and compared the results with a very large sample of data, one of the largest ever used to this purpose. These data have been analysed with a new and powerful statistical method which allows us to quantify the observational spread in measured elemental abundances and obtain a more meaningful comparison with the predictions from our chemical evolution model. Our analysis shows that the ``plateau'' observed for the [$\alpha$/Fe] ratios at low metallicities ($-3.0< [Fe/H] <-1.0$) is not perfectly constant but it shows a slope, especially for oxygen. This slope is very well reproduced by our model with both sets of yields. This is not surprising since realistic chemical evolution models, taking into account in detail stellar lifetimes, never predicted a completely flat plateau. This is due either to the fact that massive stars of different mass produce a slightly different O/Fe ratio or to the often forgotten fact that supernovae of type Ia, originating from white dwarfs, start appearing already at a galactic age of 30 million years and reach their maximum at 1 Gyr.Comment: 32 pages, 9 figures, to be published in Ap

A phenomenological approach to multisource data integration: Analysing infrared and visible data

A new method is described for combining multisensory data for remote sensing applications. The approach uses phenomenological models which allow the specification of discriminatory features that are based on intrinsic physical properties of imaged surfaces. Thermal and visual images of scenes are analyzed to estimate surface heat fluxes. Such analysis makes available a discriminatory feature that is closely related to the thermal capacitance of the imaged objects. This feature provides a method for labelling image regions based on physical properties of imaged objects. This approach is different from existing approaches which use the signal intensities in each channel (or an arbitrary linear or nonlinear combination of signal intensities) as features - which are then classified by a statistical or evident approach

SP_Ace: a new code to derive stellar parameters and elemental abundances

Aims: We developed a new method of estimating the stellar parameters Teff, log g, [M/H], and elemental abundances. This method was implemented in a new code, SP_Ace (Stellar Parameters And Chemical abundances Estimator). This is a highly automated code suitable for analyzing the spectra of large spectroscopic surveys with low or medium spectral resolution (R=2,000-20,000). Methods: After the astrophysical calibration of the oscillator strengths of 4643 absorption lines covering the wavelength ranges 5212-6860\AA\ and 8400-8924\AA, we constructed a library that contains the equivalent widths (EW) of these lines for a grid of stellar parameters. The EWs of each line are fit by a polynomial function that describes the EW of the line as a function of the stellar parameters. The coefficients of these polynomial functions are stored in a library called the "$GCOG$ library". SP_Ace, a code written in FORTRAN95, uses the GCOG library to compute the EWs of the lines, constructs models of spectra as a function of the stellar parameters and abundances, and searches for the model that minimizes the $\chi^2$ deviation when compared to the observed spectrum. The code has been tested on synthetic and real spectra for a wide range of signal-to-noise and spectral resolutions. Results: SP_Ace derives stellar parameters such as Teff, log g, [M/H], and chemical abundances of up to ten elements for low to medium resolution spectra of FGK-type stars with precision comparable to the one usually obtained with spectra of higher resolution. Systematic errors in stellar parameters and chemical abundances are presented and identified with tests on synthetic and real spectra. Stochastic errors are automatically estimated by the code for all the parameters. A simple Web front end of SP_Ace can be found at http://dc.g-vo.org/SP_ACE, while the source code will be published soon.Comment: 36 pages, 34 figures, A&A accepte