Improving Synthetical Stellar Libraries using the Cross-Entropy Algorithm

Transcription

1 Improving Synthetical Stellar Libraries using the Cross-Entropy Algorithm Lucimara Martins Universidade Cruzeiro do Sul Colaboradores: Roberto Vitoriano, Paula Coelho, Anderson Caproni IWCCA Junho de 2011

2 Why do we need stellar libraries? Stars are the main source of energy in Resolution galaxies is not The analysis of galaxy spectra can reveal key parameters like metallicity, age and star-formation history Method largely used to do that: stellar population synthesis

3 Why do we need stellar libraries? Resolution is not

4 Why do we need stellar libraries? Resolution is not

5 Why do we need stellar libraries? Resolution is not

6 Why do we need stellar libraries? Stellar libraries are the main Resolution ingredient is not for stellar population models. Advantadge of synthetical libraries: any desired parameter coverage, specially any desired abundance pattern. Disadvantage: not good enough yet.

7 Synthetical Spectra Atmosphere Model Atomic Line List Resolution is not Molecular Line List Spectral Synthesis Stellar Spectra

8 What can we improve? Atmosphere Model Atomic Line List Resolution is not Molecular Line List Spectral Synthesis Stellar Spectra

9 What can we improve? Atmosphere Model Atomic Line List Resolution is not Molecular Line List Spectral Synthesis Stellar Spectra

10 What can we improve? Atmosphere Model Atomic Line List Resolution is not Molecular Line List Spectral Synthesis Stellar Spectra

11 What can we improve? Martins & Coelho (2007) Coelho et al. (2005) library is better for some indices that had atomic lines calibrated!

12 Teff 4500K 5000K Teff 7000K Teff >7000K

13 What can we improve?

14 What can we improve? Very few of these parameters were measured in laboratory very uncertain. Until today: calibration for these parameters are done manually Capable of producing significant improvements BUT: very slow and subjective, and can only be applied to reasonably strong lines.

15 What can we improve? We need a more robust and automatic technique Powerful statistic technique to deal with multi-extremal problems involving optimization: THE CROSS-ENTROPY ALGORITHM

16 The Problem

17 The Problem

18 The Cross-Entropy Method Was already used sucessfully in astro- physical problems like the study of sources with jet precession (Caproni et al. 2009) and fitting the color-magnitude diagram of open clusters (Monteiro et al. 2010).

19 The Cross-Entropy Method The basic procedures involved in the CE optimization: (i) Random generation of the initial parameter sample, obeying predefined criteria; (ii) Selection of the best samples based on some mathematical criterion; (iii) Random generation of updated parameter samples from the previous best candidates to be evaluated in the next iteration; (iv) Optimization process repeats steps (ii) and (iii) until a pre- specified stopping criterion is fulfilled.

20 The Cross-Entropy Method We wish to study a set of N d analytical model characterized by N p We want to find: x* = (p 1 *;; p 2 *;... p description of the data. observational data in terms of an parameters (p ; p 1 ; p 2 ;... p Np ).... p Np * ) - model provides the best Generation of N independent sets of models X= (x 1, x 2,... x N ) For each model Objective function S(x) Best models found ordering according to increasing values of S.

21 The Cross-Entropy Method From these best models (elite models) mean and standard deviation of the elite sample. New range for the parameters based on the elite sample, for each interaction. Until stop criteria: Number of iteractions or minimum sigma.

22 The Cross-Entropy Method

23 The Cross-Entropy Method Kurucz Model atmospheres, Synthe spectral models Calibrating the Method N atomic line lists Sun, Arcturus, Vega spectra Comparison with control models, generated with actual line list N elite solutions Best Line list Control models S/N = 400

24 The Cross-Entropy Method

25 Results Log gf Log VdW Log Stark

26 Results

27 Results

28 Results

29 Results The cross-entropy method is capable of recovering atomic parameters of lines just by comparing spectral models with observed spectra (high resolution, high S/N). Next step: calibrate line lists observations obtained this semester on VLT (UVES P.Coelho and R. Smiljanic) of fundamental stars.

30 Procura-se: Alunos de Mestrado