Stellar classification

Now that we have a simple model for the continuum spectrum of the stars based around the Planck curve, the temperature and the luminosity, we can make some observations and classifications of the stars. There are some constellations that dominate the night sky in both the northern and southern hemispheres and even a casual look should inspire wonder. Star hopping in the night sky should lead to the simplest observation not all stars have the same colour. A high-quality photograph of the constellation of Orion (see page 2 of the colour plate section) shows stars 

97 and 1.16, respectively. Plugging in the numbers into Equation 2.7 shows that Castor is emitting close to 50 per cent less light than Pollux - the brighter star has the smaller magnitude. 

So a star with a parallax angle of 0.1 arcsec is at a distance of 10 pc, which can be converted to SI units by knowing the Earth s orbit. One parsec is 3.26 

The closest star to our Sun is one of the three stars in the a centauri system called proxima centauri. The distance to proxima centauri is 4.34 ly, so the measured angle can be calculated from Equation 2.8  

The upper limit to the length scale is 326 ly and this seems superficially a long way, but putting this into astronomical context the Milky Way is greater than 100000 ly in diameter. The distance measurement works well for astronomically short distances but all larger distances are inferred. 

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Richard K. Clingempeel, Stellar classifications, http //oerlicon.freeyellow.eom/./ SuperNovae/Classifications.html... 

Stellar classification has been an important tool in stellar and Galactic astronomy since it provides empirical measure of the fundamental stellar parameters such as temperature, luminosity and metallicity. 

The massive surveys both ground based as well as from space missions provide large number of stellar spectra covering distant components of Galaxy. To understand the complex evolutionary history of our Galaxy, rapid and accurate methods of stellar classification are necessary. A short review of the automated procedures are presented here. The most commonly used automated spectral classification methods are based on (a) Minimum Distance Method (MDM) (b) Gaussian Probability Method (GPM) (c) Principal Component Analysis (PCA) and (d) Artificial Neural Network (ANN). We chose to describe only two of them to introduce the automated approach of classification. 

The book has been organized into three parts to address the major issues in cosmochemistry. Part I of the book deals with stellar structure, nucleosynthesis and evolution of low and intermediate-mass stars. The lectures by Simon Jeffery outline stellar evolution with discussion on the basic equations, elementary solutions and numerical methods. Amanda Karakas s lectures discuss nucleosynthesis of low and intermediate-mass stars covering nucleosynthesis prior to the Asymptotic Giant Branch (AGB) phase, evolution during the AGB, nucleosynthesis during the AGB phase, evolution after the AGB and massive AGB stars. The slow neutron-capture process and yields from AGB stars are also discussed in detail by Karakas. The lectures by S Giridhar provide some necessary background on stellar classification. 

Stellar classification of a spectrum is actually based upon the intensity ratio of pairs of lines which... 

Objects that radiate mainly at infrared wavelengths may do so because of their low temperature by astronomical standards. Objects that fall in this category start with stars of spectral classifications of K or cooler extending down the newly designated spectral classification of L. The sub-stellar classification ofBrown Dwarf links stars generating energy by nucleosynthesis to planets such as the giant and terrestrial planets in our own solar system. The planets such as the earth radiate like blackbodies at their surface... 

Classical astronomy is largely concerned with the classification of stars without regard to the details of their constituent plasmas (63). Only more recently have sateUite-bome observations begun to yield detailed data from the high temperature regions of other stellar plasmas. Cosmic plasmas of diverse size scales have been discussed (64). 

The evidence on which this theory of stellar evolution is based comes not only from known nuclear reactions and the relativistic equivalence of mass and energy, but also from the spectroscopic analysis of the light reaching us from the stars. This leads to the spectral classification of stars, which is the cornerstone of modem experimental astrophysics. The spectroscopic analysis of starlight reveals much information about the... 

The spectral features observed by astronomers have led to the classification of stars into seven broad classes outlined in Table 4.1, together with their surface temperatures. The highest-temperature class, class O, contains may ionised atoms in the spectrum whereas the older stars in class M have a much lower temperature and many more elements present in the spectrum of the star. Observation of a large number of the stars has lead to extensive stellar catalogues, recently extended by the increased sensitivity of the Hubble Space Telescope. Making sense of this vast quantity of information is difficult but in the early 19th century two astronomers... 

Multicolour photometric systems that have been used for various sorts of stellar and stellar-population classification are listed with their spectral reponse curves in the website... 

There are several bodies of information that feed into our understanding of stellar nucleosynthesis. We will start with a discussion of the classification of stars, their masses and mass distributions, and their lifetimes. From this information we can assess the relative importance of different types of stars to the nucleosynthesis of the elements in our solar system and in the galaxy. We will then discuss the life cycles of stars to give a framework for the discussion of nucleosynthesis processes. Next, we will review the nuclear pathways... 

Extrapolation of the hem lines to Z/N = 1 defines another recognizable periodic classification of the elements, inverse to the observed arrangement at Z/N = t. The inversion is interpreted in the sense that the wave-mechanical ground-state electronic configuration of the atoms, with sublevels / < d < p < s, is the opposite of the familiar s < p < d < f. This type of inversion is known to be effected under conditions of extremely high pressure [52]. It is inferred that such pressures occur in regions of high space-time curvature, such as the interior of massive stellar objects, a plausible site for nuclear synthesis. 

Classification Cold dense cloud Outflowing C-rich circum-stellar envelope Warm molecular cloud/star-forming region Giant molecular cloud... 

The key features of stars which are of interest to astronomers are their mass, their luminosity, their surface temperature, and their distance from us. These parameters are used to classify stars and place them into an evolutionary sequence. A widely used classification diagram, based on optical data for stars, is the Hertzsprung-Russell Diagram (the H-R diagram) which is a plot of stellar luminosity versus effective surface temperature. The luminosity of a star is a function of its radius and effective temperature. The surface temperature is determined from its color and is vastly different from temperatures in the core of the star. For example, our sun has a surface temperature of about 5,700 K but a core temperature of 14 million K. 

The ANN has been used in very large number of stellar applications. Vieira and Ponz [24] have used ANN on low-resolution IUE spectra and have determined SpT with an accuracy of 1.1 subclass. Bailer-Jones and Irwin [19] used ANN to classify spectra from Michigan Spectral Survey with an accuracy of 1.09 SpT. Prieto and co-workers [25] used ANN in their search of metal-poor stars. Snider and co-workers [26] used ANN for the three dimensional classification of metal-poor stars. 

It is very important to envisage an approach that would give quick, reliable spectral classifications (or stellar parameters) for stars falling in all regions of HR diagram. The pipeline procedures are being developed for the future ambitious missions such as GAIA and PAN-STARS. 

Astronomers classify stars according to their colors and (absorption) line spectra and luminosities. Meghnad Saha showed [2,3] the link between the classification scheme and temperature (and thermal ionization) of stellar atmosphere. 

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