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ASTR 5610, Majewski [SPRING 2018]. Lecture Notes

ASTR 5610 (Majewski) Lecture Notes



Binney & Merrifield, Section 3.3-3.4.

Another useful reference to the philosophical side of classification is W.W. Morgan's (1984) article in "The MK Process and Stellar Classification'', ed. R.F. Garrison.

Spectral classification may seem an arcane subject to the modern student, but it continues to play an important role in a number of ways:

Also important to understand the history of this subject...

Spectral classification:

Spectral classification has simpler goal. The "MK Philosophy" of classification can be applied to any kind of taxonomical system (and has been applied not only to stellar spectra, but galaxy typing, etc.):

The MK system is autonomous and expandable:

Classically, the two-dimensional, Morgan-Keenan system:

"The autonomy of each array (in the MK system) is achieved

through its liberation from dependence on the results of stellar

atmospheric computations -- or on any other theoretical models."

More than 90% of stars are classifiable in the extended MK system.


Spectrum of the Sun: Fraunhofer lines

From sci122/Programs/p27/p27.html.

Names of the most prominent lines identified by Fraunhofer:

A 7594 Molecular oxygen in earth's atmosphere
B 6867 Molecular oxygen in earth's atmosphere
C 6563 Halpha
*D1 5896 Sodium
*D2 5890 Sodium
E1 5270 Iron
**Eb 5183-5168 Magnesium
F 4861 Hbeta
*G 4308 Blend of band of methane and iron
*H 3968 Ionized calcium
*K 3933 Ionized calcium

*Still commonly used name (e.g., "sodium D lines (NaD)", "G band" and "calcium H and K lines (Ca II H+K)".
** In this case the name has morphed from "Eb" into "Mgb" to indicate that magnesium is the source of the line.

Classification of stellar spectra (a brief history and explanation):

Principal Spectral Class Sequence

Schematically, shown from 7000 to 4000 Å.

Actual spectral classification sequence from 4000-7000 Å.

Actual spectral classification sequence from 4000-7000 Ås. At the bottom are three special cases, an F4 type star that is very metal poor, a late type star (M4.5e) with emission lines from coronal activity, and an early type star (B1) with emission lines. NOAO/AURA/NSF image adapted from html/im0649.html.

These spectra were created by Mike Briley, University of Maryland in the late 1980's. They are computer synthesized models of star spectra. The spectra have been "flattened" to remove the very strong variation in the overall flux balance for stars of different temperatures (Wien's law), so that one can easily see the changing darkness of the different lines with temperature. Hot, "early-type" stellar spectra are at the top of the figure, and the late type, cool, stellar spectra at the bottom. In real life, the hot stars have most of their flux in the blue part of the spectrum, while the cool ones are very red. Enjoy the view and watch how some different dark absorption lines and molecular bands vary in strength with stellar effective temperature.
Corresponding one dimensional spectra shown in a part of the spectrum traditionally used to classify stars, from 3500 to 5000 Ås. Note that again the spectra have been made artificially flat for ease of comparison based on lines.

Actual stellar spectra, including the variation of flux by wavelength due to blackbody temperature, looks something like this.

Luminosity Effects in Stellar Spectra

E. Hertzsprung and H.N. Russell (1905-1913), working independently, discovered stars of the same spectral type can have vastly different luminosities (see HR Diagram below).

Secondary effects on the strengths of lines come about due to the pressure of the gas producing the lines because this determines the rate at which electrons may be captured by ions, and so effects the ionization equilibrium.

Atmospheric pressure relates to the weight of the atmosphere and this relates to the surface gravity at the photosphere of the star.

Abundance Effects in Stellar Spectra

Obviously, low abundance of a particular species in the atmosphere of a star also results in weak expression of lines from that species.

An example of a weak-lined star compare to the normal metallicity star of the same effective temperature.


Please read Binney & Merrifield Section 3.4 for a more complete description!

Detailed spectral analysis of (generally high resolution) has as a goal ascertaining three fundamental atmospheric parameters, which together define the spectral energy distribution:


The classical Hertzsprung-Russell Diagram (developed independently by these two astronomers) is a plot of spectral type versus luminosity.

In the example below:

Note however, because of the requirement to have stars of known distance, certain types of stars are not well represented in the classical HR diagram.

For the latter reasons, you should not necessarily interpret the classical HR diagram as representative of the luminosity function -- the balance of the numbers of stars per absolute magnitude.


The Figures below are modern versions of the HR diagram, but now in the more common guise of a color-magnitude diagram (in this case absolute magnitude, which makes it the same as the HR diagram on the ordinate).

Left: 4902 stars from HIPPARCOS Catalogue with relative distance precision of 5%. Right: 41704 stars with relative precision 20%.
Panels (a) and (b) are a comparison of the HR diagram in absolute Gaia magnitudes, MG, versus (B-V) for 43,546 stars that are in both HIPPARCOS and Gaia DR1, and that have less than 20% errors in both and less than 0.05 mag errors in both color and magnitude. Panel (a) uses Hipparcos (van Leeuwen 2007) parallaxes and panel (b) uses parallaxes as listed in Gaia DR1 (Brown et al. 2016). Panel (c) shows all 74,771 stars with relative parallax uncertainties better than 20% in Gaia DR1 alone (irrespective of HIPPARCOS). "All panels show the stars as individual symbols where possible and where the symbols overlap the relative source density is shown, with colors varying from purple (dark) to yellow (light) indicating increasing density on a logarithmic scale. The contours enclose 10, 30, and 50 per cent of the data." Figure and quote from Brown et al. (2016, A&A, 595, A2).
The main features visible in both the HIPPARCOS and Gaia CMDs are shaped and biased by the magnitude and distance (i.e., parallax precision) limits. The main features are annotated in the HIPPARCOS CMD below:

Just as in the classical HR diagram, the sequences in the HIPPARCOS CMD are somewhat smeared in the vertical dimension (though there are not discrete stripes because HIPPARCOS measured colors rather than discrete spectral types).

The vertical spreads along the sequences shown come from several effects (all that we will explore in various homework assignments in coming weeks):

Finally, here is a very interesting version of the Gaia CMD where the points are color-coded by the transverse velocity, which is derived from the combination of the Gaia parallax and proper motion.

"Observational HR diagram showing where stars with specific values of the transverse velocity tend to occur. The colour coding of the points is according to tangential velocity interval, as indicated in the legend (in km s-1)." Figure and caption from Brown et al. (2016, A&A, 595, A2).
This figure illustrates some very interesting and fundamental aspects of the variety of stellar populations in the solar neighborhood.

(Here "solar neighborhood" is defined by the median parallax of the sample of 10.7 mas -- which corresponds to a distance of 93 pc -- and with 90% of the stars with a parallax greater than 2.8 mas -- which corresponds to a distance of 357 pc.)

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Filter curves taken from All other material copyright © 2003,2008,2010,2012,2014,2016,2018 Steven R. Majewski. All rights reserved. These notes are intended for the private, noncommercial use of students enrolled in Astronomy 551 and Astronomy 5610 at the University of Virginia.