Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userStellar Inversion Techniques
68
0
0.0
(
0
)
Authors
Daniel R. Reese
Ask ChatGPT about the research
No Arabic abstract
Stellar seismic
rate research
Read More
The solar metallicity issue is a long-lasting problem of astrophysics, impacting multi- ple fields and still subject to debate and uncertainties. While spectroscopy has mostly been used to determine the solar heavy elements abundance, helioseismologists at- tempted providing a seismic determination of the metallicity in the solar convective enveloppe. However, the puzzle remains since two independent groups prodived two radically different values for this crucial astrophysical parameter. We aim at provid- ing an independent seismic measurement of the solar metallicity in the convective enveloppe. Our main goal is to help provide new information to break the current stalemate amongst seismic determinations of the solar heavy element abundance. We start by presenting the kernels, the inversion technique and the target function of the inversion we have developed. We then test our approach in multiple hare-and-hounds exercises to assess its reliability and accuracy. We then apply our technique to solar data using calibrated solar models and determine an interval of seismic measurements for the solar metallicity. We show that our inversion can indeed be used to estimate the solar metallicity thanks to our hare-and-hounds exercises. However, we also show that further dependencies in the physical ingredients of solar models lead to a low accuracy. Nevertheless, using various physical ingredients for our solar models, we determine metallicity values between 0.008 and 0.014.
Stellar elemental abundances are important for understanding the fundamental properties of a star or stellar group, such as age and evolutionary history, as well as the composition of an orbiting planet. However, as abundance measurement techniques have progressed, there has been little standardization between individual methods and their comparisons. As a result, different stellar abundance procedures determine measurements that vary beyond quoted error for the same elements within the same stars (Hinkel et al. 2014). The purpose of this paper is to better understand the systematic variations between methods and offer recommendations for producing more accurate results in the future. We have invited a number of participants from around the world (Australia, Portugal, Sweden, Switzerland, and USA) to calculate ten element abundances (C, O, Na, Mg, Al, Si, Fe, Ni, Ba, and Eu) using the same stellar spectra for four stars (HD361, HD10700, HD121504, HD202206). Each group produced measurements for each of the stars using: 1) their own autonomous techniques, 2) standardized stellar parameters, 3) standardized line list, and 4) both standardized parameters and line list. We present the resulting stellar parameters, absolute abundances, and a metric of data similarity that quantifies homogeneity of the data. We conclude that standardization of some kind, particularly stellar parameters, improves the consistency between methods. However, because results did not converge as more free parameters were standardized, it is clear there are inherent issues within the techniques that need to be reconciled. Therefore, we encourage more conversation and transparency within the community such that stellar abundance determinations can be reproducible as well as accurate and precise.
This document aims at reviewing the different types of clustering algorithms and substructures detection techniques in order to study the spatial and kinematic clustering of stars and detect the gas components in molecular clouds. It is the deliverable: Report on Optimal Substructure Techniques for Stellar, Gas and Combined Samples, for the EU H2020 (COMPET-5-2015 - Space) project (A Gaia and Herschel Study of the Density Distribution and Evolution of Young Massive Star Clusters), Grant Agreement Number: 687528, with abbreviated code name StarFormMapper (SFM) project. The document is organized in the following sections: 1. General Introduction 2. Clustering of Discrete Distributions 3. Clustering of Continuous Distributions 4. Clustering in Astrophysics 5. StarFormMapper 6. Summary and Conclusions
Observations of the Sun in the visible spectral range belong to standard measurements obtained by instruments both on the ground and in the space. Nowadays, both nearly continuous full-disc observations with medium resolution and dedicated campaigns of high spatial, spectral and/or temporal resolution constitute a holy grail for studies that can capture (both) the long- and short-term changes in the dynamics and energetics of the solar atmosphere. Observations of photospheric spectral lines allow us to estimate not only the intensity at small regions, but also various derived data products, such as the Doppler velocity and/or the components of the magnetic field vector. We show that these measurements contain not only direct information about the dynamics of solar plasmas at the surface of the Sun but also imprints of regions below and above it. Here, we discuss two examples: First, the local time-distance helioseismology as a tool for plasma dynamic diagnostics in the near subsurface and second, the determination of the solar atmosphere structure during flares. The methodology in both cases involves the technique of inverse modelling.
Inversion codes are computer programs that fit a model atmosphere to the observed Stokes spectra, thus retrieving the relevant atmospheric parameters. The rising interest in the solar chromosphere, where spectral lines are formed by scattering, requires developing, testing, and comparing new non-local thermal equilibrium (NLTE) inversion codes. We present a new NLTE inversion code that is based on the analytical computation of the response functions. We named the code SNAPI, which is short for spectropolarimetic NLTE analytically powered inversion. SNAPI inverts full Stokes spectrum in order to obtain a depth-dependent stratification of the temperature, velocity, and the magnetic field vector. It is based on the so-called node approach, where atmospheric parameters are free to vary in several fixed points in the atmosphere, and are assumed to behave as splines in between. We describe the inversion approach in general and the specific choices we have made in the implementation. We test the performance on one academic problem and on two interesting NLTE examples, the Ca,II,8542 and Na,I,D spectral lines. The code is found to have excellent convergence properties and outperforms a finite-difference based code in this specific implementation by at least a factor of three. We invert synthetic observations of Na lines from a small part of a simulated solar atmosphere and conclude that the Na lines reliably retrieve the magnetic field and velocity in the range $-3<log tau < -0.5$.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
