Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-05T15:09:45.895Z Has data issue: false hasContentIssue false

6 - Tutorial: The analysis of colour-magnitude diagrams

Published online by Cambridge University Press:  05 November 2013

D. Valls-Gabaud
Affiliation:
France
David Martínez-Delgado
Affiliation:
Max-Planck-Institut für Astronomie, Heidelberg
Get access

Summary

6.1 Introduction

The plotting of the colors (or spectra) of stars as abscissae against their absolute magnitudes (total magnitudes) has become one of the most lucrative adventures in the study of star light.

Shapley (1960)

It is appropriate to recall, in the context of this volume, that just over a century ago the first color-magnitude diagram (CMD) was published. The author of this landmark paper was not Ejnar Hertzsprung nor Henry N. Russell, but Hans O. Rosenberg, a colleague of Karl Schwarzschild at Göttingen. Rosenberg had been working since 1907 on getting spectral properties of stars by measuring plates obtained with the Zeiss objective prism camera (Hermann, 1994). To maximize the number of spectra per plate, he observed the Pleiades cluster and obtained spectra for about 60 of them, over 1907–1909, noting that their inferred effective temperatures correlated with their apparent magnitudes in the first ever published CMD (Rosenberg, 1910). His goal was to “make the most accurate determination of the spectral types of stars in the Pleiades” by using a “physiological blend” of the depth and width of the Ca II K line (393.37 nm) with the Balmer Hδ and Hζ lines. He excluded the Ca II H line at 396.9 nm as it was blended with H∈ in the very low dispersion spectra he used (1.9 mm from Hγ to Hζ). With an exposure time of 90 minutes he could measure spectra down to the 10th photographic magnitude, finding that for the actual members of the Pleiades “there is a strict relation between the brightness and the spectral type, with no exception in the interval from the 3rd to the 9th magnitude.”

Type
Chapter
Information
Local Group Cosmology , pp. 192 - 225
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abraham, R. G., Ellis, R. S., Fabian, A. C., Tanvir, N. R., and Glazebrook, K. 1999. The star formation history of the Hubble sequence: spatially resolved color distributions of intermediate-redshift galaxies in the Hubble Deep Field. MNRAS, 303(Mar.), 641–658.Google Scholar
An, D., Terndrup, D. M., Pinsonneault, M. H., Paulson, D. B., Hanson, R. B., and Stauffer, J. R. 2007. The distances to open clusters from main-sequence fitting. III. Improved accuracy with empirically calibrated isochrones. ApJ, 655(Jan.), 233–260.Google Scholar
Aparicio, A. and Hidalgo, S. L. 2009. IAC-pop: finding the star formation history of resolved galaxies. AJ, 138(Aug.), 558–567.Google Scholar
Aparicio, A., Bertelli, G., Chiosi, C., and Garcia-Pelayo, J. M. 1990. CCD UBVR photometry of the old rich open cluster King 2 – comparison with theoretical models. A&A, 240(Dec.), 262–288.Google Scholar
Bailer-Jones, C. A. L. 2011. Bayesian inference of stellar parameters and interstellar extinction using parallaxes and multiband photometry. MNRAS, 411(Feb.), 435–452.Google Scholar
Baker, S. and Cousins, RD. 1984. Clarification of the use of chi-square and likelihood functions in fits to histograms. Nucl. Instrum. Methods, 221 (Feb.), 437–442.Google Scholar
Bayes, T. 1763. An essay toward solving a problem in the doctrine of chances. Phil. Trans. Roy. Soc., 53, 370–418.Google Scholar
Beaulieu, S. F., Freeman, K. C., Kalnajs, A. J., Saha, P., and Zhao, H. 2000. Dynamics of the Galactic Bulge Using Planetary Nebulae. AJ, 120(Aug.), 855–871.Google Scholar
Becker, S. A. and Mathews, G. J. 1983. A comparison between observed and theoretical H-R diagrams for the young LMC star cluster NGC 1866. ApJ, 270(July), 155–168.Google Scholar
Bell, E. F., and 17 colleagues. 2008. The accretion origin of the Milky Way's stellar halo. ApJ, 680(June), 295–311.Google Scholar
Bothun, G. D. 1986. Two-color CCD mapping of the luminous Type I irregular galaxy NGC 4449. AJ, 91 (Mar.), 507–516.Google Scholar
Breddels, M. A., and 23 colleagues. 2010. Distance determination for RAVE stars using stellar models. A&A, 511(Feb.), A90.Google Scholar
Brott, I., and 8 colleagues 2011. Rotating massive main-sequence stars. I. Grids of evolutionary models and isochrones. A&A, 530(June), A115.Google Scholar
Bruntt, H. and Southworth, J. 2008. A new level of photometric precision: WIRE observations of eclipsing binary stars. Journal of Physics Conference Series, 118(Oct.), 012012.Google Scholar
Burnett, B. and Binney, J. 2010. Stellar distances from spectroscopic observations: a new technique. MNRAS, 407(Sept.), 339–354.Google Scholar
Casagrande, L., Ramírez, I., Meléndez, J., Bessell, M., and Asplund, M. 2010. An absolutely calibrated Teff scale from the infrared flux method. Dwarfs and subgiants. A&A, 512(Mar.), A54.Google Scholar
Casagrande, L., Schönrich, R., Asplund, M., Cassisi, S., Ramírez, I., Meléndez, J., Bensby, T., and Feltzing, S. 2011. New constraints on the chemical evolution of the solar neighbourhood and Galactic disc(s). Improved astrophysical parameters for the Geneva-Copenhagen Survey. A&A, 530(June), A138.Google Scholar
Cerviño, M. and Luridiana, V. 2006. Confidence limits of evolutionary synthesis models. IV. Moving forward to a probabilistic formulation. A&A, 451(May), 475–498.Google Scholar
Cerviño, M. and Valls-Gabaud, D. 2003. On biases in the predictions of stellar population synthesis models. MNRAS, 338(Jan.), 481–496.Google Scholar
Cerviño, M. and Valls-Gabaud, D. 2009. On the initial cluster mass distribution inferred from synthesis models. Ap&SS, 324(Dec.), 91–94.Google Scholar
Cerviño, M., Valls-Gabaud, D., Luridiana, V., and Mas-Hesse, J. M. 2002. Confidence levels of evolutionary synthesis models. II. On sampling and Poissonian fluctuations. A&A, 381(Jan.), 51–64.Google Scholar
Chanamé, J. and Ramírez, I. 2012. Toward precise ages for single stars in the field. Gyrochronology constraints at several Gyr using wide binaries. I. Ages for initial sample. ApJ, 746(Feb.), 102.Google Scholar
Charlier, C.V.L. 1889. Publ. Astronomischen Gesell, 19, 1.
Cignoni, M. and Tosi, M. 2010. Star formation histories of dwarf galaxies from the color-magnitude diagrams of their resolved stellar populations. Advances in Astronomy, 2010.
Cignoni, M. and Shore, S. N. 2006. Restoring color-magnitude diagrams with the Richardson-Lucy algorithm. A&A, 454(Aug.), 511–516.Google Scholar
Cignoni, M., Degl'Innocenti, S., Prada Moroni, P. G., and Shore, S. N. 2006. Recovering the star formation rate in the solar neighborhood. A&A, 459(Dec.), 783–796.Google Scholar
Collins, G. W. II and Smith, R. C. 1985. The photometric effect of rotation in the A stars. MNRAS, 213(Apr.), 519–552.Google Scholar
Collins, G. W. II and Sonneborn, G. H. 1977. Some effects of rotation on the spectra of upper-main-sequence stars. ApJS, 34(May), 41–94.Google Scholar
Conti, A., and 8 colleagues. 2003. The star formation history of galaxies measured from individual pixels. I. The Hubble Deep Field North. AJ, 126(Nov.), 2330–2345.Google Scholar
Cousin, R. 1995. Am. J. Phys., 63, 398.
Craig, I. J. D. and Brown, J. C. 1986. Inverse Problems in Astronomy: A Guide to Inversion Strategies for Remotely Sensed Data. Bristol, England: Adam Hilger.
da Silva, L., and 8 colleagues. 2006. Basic physical parameters of a selected sample of evolved stars. A&A, 458(Nov.), 609–623.Google Scholar
da Silva, R. L., Fumagalli, M., and Krumholz, M. 2012. SLUG–stochastically lighting up galaxies. I. Methods and validating tests. ApJ, 745(Feb.), 145.Google Scholar
Dale, A. I. 1982. Arch. Hist. Exact Sci., 27, 23.
de La Fuente Marcos, R. and de La Fuente Marcos, C. 2004. On the correlation between the recent star formation rate in the Solar Neighbourhood and the glaciation period record on Earth. New A, 10(Nov.), 53–66.Google Scholar
Devorkin, D. H. 2000. Henry Norris Russell: Dean ofAmerican Astronomers. Princeton, N.J.: Princeton University Press.
Dolphin, A. E. 1997. A new method to determine star formation histories of nearby galaxies. New A, 2(Nov.), 397–409.Google Scholar
Dolphin, A. E. 2002. Numerical methods of star formation history measurement and applications to seven dwarf spheroidals. MNRAS, 332(May), 91–108.Google Scholar
Dose, V. 2003. Bayesian inference in physics: case studies. Rep. Pro. Phys., 66(Sept.), 1421–1461.Google Scholar
Duerbeck, H. W. ed. 2006. Organizations and Strategies in Astronomy, Vol. 7. Berlin: Springer Verlag.
Eskridge, P. B., and 10 colleagues. 2003. Ultraviolet-optical pixel maps of face-on spiral galaxies: clues for dynamics and star formation histories. ApJ, 586(Apr.), 923–938.Google Scholar
Flannery, B. P. and Johnson, B. C. 1982. A statistical method for determining ages of globular clusters by fitting isochrones. ApJ, 263(Dec.), 166–186.Google Scholar
Gallart, C., Zoccali, M., and Aparicio, A. 2005. The adequacy of stellar evolution models for the interpretation of the color-magnitude diagrams of resolved stellar populations. ARA&A, 43(Sept.), 387–434.Google Scholar
Gennaro, M., Prada Moroni, P. G., and Tognelli, E. 2012. Testing pre-main-sequence models: the power of a Bayesian approach. MNRAS, 420(Feb.), 986–1018.Google Scholar
Gleissberg, W. 1940. Pub. Istanbul Obs., 13, 2.
Gregory, P. C. 2005. Bayesian Logical Data Analysis for the Physical Sciences: A Comparative Approach with “Mathematica” Support. Cambridge, UK: Cambridge University Press.
Haffner, H. and Heckmann, O. 1937. Das farben-helligkeits-diagramm der praesepe auf grund neuer beobachtungen. Veroeffentlichungen der Universitaets-Sternwarte zu Goettingen, 4, 77–95.Google Scholar
Harmanec, P. and Prsa, A. 2011. Call to adopt a nominal set of astrophysical parameters and constants to improve the accuracy of fundamental physical properties of stars. PASP, 123(Aug.), 976–980.Google Scholar
Harris, J. and Zaritsky, D. 2001. A method for determining the star formation history of a mixed stellar population. ApJS, 136(Sept.), 25–40.Google Scholar
Hearnshaw, J. B. 1986. The Analysis of Starlight: One Hundred and Fifty Years of Astronomical Spectroscopy. Cambridge: Cambridge University Press.
Hermann, D. B. 1994. Ejnar Hertzsprung: Pionier der SternforschungBerlin: Springer-Verlag.
Hernandez, X. and Valls-Gabaud, D. 2008. A robust statistical estimation of the basic parameters of single stellar populations – I. Method. MNRAS, 383(Feb.), 1603–1618.Google Scholar
Hernandez, X., Gilmore, G., and Valls-Gabaud, D. 2000a. Non-parametric star formation histories for four dwarf spheroidal galaxies of the Local Group. MNRAS, 317(Oct.), 831–842.Google Scholar
Hernandez, X., Valls-Gabaud, D., and Gilmore, G. 1999. Deriving star formation histories: inverting Hertzsprung-Russell diagrams through a variational calculus maximum likelihood method. MNRAS, 304(Apr.), 705–719.Google Scholar
Hernandez, X., Valls-Gabaud, D., and Gilmore, G. 2000b. The recent star formation history of the Hipparcos solar neighbourhood. MNRAS, 316(Aug.), 605–612.Google Scholar
Hertzsprung, E. 1911. Ueber die Verwendung photographischer effektiver wellenlaengen zur bestimmung von farbenaequivalenten. POPot, 63.Google Scholar
Hess, R. 1924. Probleme der Astronomie. Festschrift fur Hugo v. Seeliger. Berlin: Springer Verlag.
Hobson, M. P., Jaffe, A. H., Liddle, A. R., Mukeherjee, P., and Parkinson, D. 2010. Bayesian Methods in Cosmology. Cambridge: Cambridge University Press.
Hurley, J. and Tout, C. A. 1998. The binary second sequence in cluster color-magnitude diagrams. MNRAS, 300(Nov.), 977–980.Google Scholar
Javiel, S. C., Santiago, B. X., and Kerber, L. O. 2005. Constraints on the star formation history of the Large Magellanic Cloud. A&A, 431 (Feb.), 73–85.Google Scholar
Jeffery, E. J., von Hippel, T., DeGennaro, S., van Dyk, D. A., Stein, N., and Jefferys, W. H. 2011. The white dwarf age of NGC 2477. ApJ, 730(Mar.), 35.Google Scholar
Jeffery, E. J., von Hippel, T., Jefferys, W. H., Winget, D. E., Stein, N., and De Gennaro, S. 2007. New techniques to determine ages of open clusters ussing white dwarfs. ApJ, 658(Mar.), 391–395.Google Scholar
Jørgensen, B. R. and Lindegren, L. 2005. Determination of stellar ages from isochrones: Bayesian estimation versus isochrone fitting. A&A, 436(June), 127–143.Google Scholar
Kassin, S. A., Frogel, J. A., Pogge, R. W., Tiede, G. P., and Sellgren, K. 2003. Stellar populations in NGC 4038/39 (the Antennae): exploring a galaxy merger pixel by pixel. AJ, 126(Sept.), 1276–1285.Google Scholar
Kerber, L. O. and Santiago, B. X. 2005. Physical parameters of rich LMC clusters from modeling of deep HST color-magnitude diagrams. A&A, 435(May), 77–93.Google Scholar
Kerber, L. O., Girardi, L., Rubele, S., and Cioni, M.-R. 2009. Recovery of the star formation history of the LMC from the VISTA survey of the Magellanic system. A&A, 499(June), 697–710.Google Scholar
Kerber, L. O., Javiel, S. C., and Santiago, B. X. 2001. Constraints on thick disc and halo parameters from HST photometry of field stars in the Galaxy. A&A, 365(Jan.), 424–430.Google Scholar
Kerber, L. O., Santiago, B. X., Castro, R., and Valls-Gabaud, D. 2002. Analysis of color-magnitude diagrams of rich LMC clusters: NGC 1831. A&A, 390(July), 121–132.Google Scholar
Lachaume, R., Dominik, C., Lanz, T., and Habing, H. J. 1999. Age determinations of main-sequence stars: combining different methods. A&A, 348(Aug.), 897–909.Google Scholar
Lanyon-Foster, M. M., Conselice, C. J., and Merrifield, M. R. 2007. Structure through color: a pixel approach toward understanding galaxies. MNRAS, 380(Sept.), 571–584.Google Scholar
Laplace, P.S.. 1812. Théorie analytique des probabilités. Paris: Courcier.
Lastennet, E. and Valls-Gabaud, D. 1996. A systematic study of the effects of unresolved binaries and rotation in open clusters. The Origins, Evolution, and Destinies of Binary Stars in Clusters, 90, 464.Google Scholar
Lastennet, E. and Valls-Gabaud, D. 2002. Detached double-lined eclipsing binaries as critical tests of stellar evolution. Age and metallicity determinations from the HR diagram. A&A, 396(Dec.), 551–580.Google Scholar
Lastennet, E., Fernandes, J., Valls-Gabaud, D., and Oblak, E. 2003. Disentangling discrepancies between stellar evolution theory and sub-solar mass stars. The influence of the mixing length parameter for the UV Psc binary. A&A, 409(Oct.), 611–618.Google Scholar
Lastennet, E., Valls-Gabaud, D., Lejeune, T., and Oblak, E. 1999. Consequences of HIPPARCOS parallaxes for stellar evolutionary models. Three Hyades binaries: V 818 Tauri, 51 Tauri, and theta (2) Tauri. A&A, 349(Sept.), 485–494.Google Scholar
Lebreton, Y. 2000. Stellar structure and evolution: deductions from Hipparcos. ARA&A, 38, 35–77.Google Scholar
Lee, J. H., Kim, S. C., Park, H. S., Ree, C. H., Kyeong, J., and Chung, J. 2011. Hubble Space Telescope pixel analysis of the interacting face-on spiral galaxy NGC 5194 (M51A). ApJ, 740(Oct.), 42.Google Scholar
Ludwig, H.-G., Freytag, B., and Steffen, M. 1999. A calibration of the mixing-length for solartype stars based on hydrodynamical simulations. I. Methodical aspects and results for solar metallicity. A&A, 346(June), 111–124.Google Scholar
Luri, X., Torra, J., and Figueras, F. 1992. The proximity parameter. A&A, 259(June), 382–385.Google Scholar
Maeder, A. 1974. Stellar evolution near the main sequence: on some systematic differences between cluster sequences and model calculations. A&A, 32(May), 177–190.Google Scholar
Maeder, A. and Meynet, G. 2012. Rotating massive stars: from first stars to gamma ray bursts. Reviews of Modern Physics, 84(Jan.), 25–63.Google Scholar
Maeder, A. and Peytremann, E. 1970. Stellar rotation. A&A, 7(July), 120.Google Scholar
Makarov, D. I. and Makarova, L. N. 2004. Modeling the star population of resolved galaxies. Astrophysics, 47(Apr.), 229–241.Google Scholar
Malkov, O. Y., Sichevskij, S. G., and Kovaleva, D. A. 2010. Parametrization of single and binary stars. MNRAS, 401 (Jan.), 695–704.Google Scholar
Mayne, N. J. and Naylor, T. 2008. Fitting the young main-sequence: distances, ages and age spreads. MNRAS, 386(May), 261–277.Google Scholar
Meissner, F. and Weiss, A. 2006. Global fitting of globular cluster age indicators. A&A, 456(Sept.), 1085–1096.Google Scholar
Meyer-Hofmeister, E. 1969. A theoretical Hertzsprung-Russell-diagram for the star cluster NGC 1866. A&A, 2(June), 143–150.Google Scholar
Mighell, K. J. 1999. Parameter estimation in astronomy with Poisson-distributed data. I. The statistic. ApJ, 518(June), 380–393.Google Scholar
Monteiro, H., Dias, W. S., and Caetano, T. C. 2010. Fitting isochrones to open cluster photometric data. A new global optimization tool. A&A, 516(June), A2.Google Scholar
Naylor, T. 2009. Are pre-main-sequence stars older than we thought?MNRAS, 399(Oct.), 432–442.Google Scholar
Naylor, T. and Jeffries, R. D. 2006. A maximum-likelihood method for fitting color-magnitude diagrams. MNRAS, 373(Dec.), 1251–1263.Google Scholar
Ng, Y. K. 1998. Stellar population synthesis diagnostics. A&AS, 132(Oct.), 133–143.Google Scholar
Ng, Y. K., Brogt, E., Chiosi, C., and Bertelli, G. 2002. Automatic observation rendering (AMORE). I. On a synthetic stellar population's color-magnitude diagram. A&A, 392(Sept.), 1129–1147.Google Scholar
Nielsen, A. V. 1969. Centaurus, 9, 219.
Nordström, B., and 8 colleagues. 2004. The Geneva-Copenhagen survey of the Solar neighbourhood. Ages, metallicities, and kinematic properties of 14,000 F and G dwarfs. A&A, 418(May), 989–1019.Google Scholar
Olsen, K. A. G. 1999. Star formation histories from Hubble Space Telescope color-magnitude diagrams of six fields of the Large Magellanic Cloud. AJ, 117(May), 2244–2267.Google Scholar
Patenaude, M. 1978. Age determinations of open clusters. A&A, 66(May), 225–239.Google Scholar
Perrin, M.-N., Cayrel de Strobel, G., Cayrel, R., and Hejlesen, P. M. 1977. Fine structure of the H-R diagram for 138 stars in the solar neighbourhood. A&A, 54(Feb.), 779–795.Google Scholar
Protassov, R., van Dyk, D. A., Connors, A., Kashyap, V. L., and Siemiginowska, A. 2002. Statistics, handle with care: detecting multiple model components with the likelihood ratio test. ApJ, 571 (May), 545–559.Google Scholar
Pont, F. and Eyer, L. 2004. Isochrone ages for field dwarfs: method and application to the age-metallicity relation. MNRAS, 351 (June), 487–504.Google Scholar
Popescu, B. and Hanson, M. M. 2009. MASSCLEAN-Massive Cluster Evolution and Analysis Package: description and tests. AJ, 138(Dec.), 1724–1740.Google Scholar
Popescu, B. and Hanson, M. M. 2010a. MASSCLEANcolors–Mass-dependent integrated colors for stellar clusters derived from 30 million Monte Carlo simulations. ApJ, 713(Apr.), L21–L27.Google Scholar
Popescu, B. and Hanson, M. M. 2010b. MASSCLEANage–stellar cluster ages from integrated colors. ApJ, 724(Nov.), 296–305.Google Scholar
Popescu, B., Hanson, M. M., and Elmegreen, B. G. 2012. Age and mass for 920 Large Magellanic Cloud clusters derived from 100 million Monte Carlo simulations. ApJ, 751(June), 122.Google Scholar
Ramírez, I. and Meléndez, J. 2005. The effective temperature scale of FGK stars. II. Teff:Color:[Fe/H] calibrations. ApJ, 626(June), 465–485.Google Scholar
Reddy, B. E., Tomkin, J., Lambert, D. L., and Allende Prieto, C. 2003. The chemical compositions of Galactic disc F and G dwarfs. MNRAS, 340(Mar.), 304–340.Google Scholar
Rengel, M., Mateu, J., and Bruzual, G. 2002. The determination of the age of globular clusters: a statistical approach. Extragalactic Star Clusters, 207, 716.Google Scholar
Renzini, A. 1998. The stellar populations of pixels and frames. AJ, 115(June), 2459–2465.Google Scholar
Renzini, A. and Buzzoni, A. 1983. Theoretical foundations of evolutionary population synthesis. A progress report. Mem. Soc. Astron. Italiana, 54, 739–745.Google Scholar
Robertson, J. W. 1974. Core-helium stars in young clusters in the Large Magellanic Cloud. ApJ, 191 (July), 67–78.Google Scholar
Rosenberg, H. 1910. Astron. Nach., 186, 71.
Rosenberg, H. 1929. Lichtelektrische photometrie. Handbuch der Astrophysik, 2, 380.Google Scholar
Rosenberg, H. O. 1936. Darkening at the limb and color index of an eclipsing variable (u Cephei). ApJ, 83(Mar.), 67.Google Scholar
Russell, H. N. 1912. Proc. Phil. Soc. Amer., 51, 569.
Russell, H. N. 1914a. Relations between the spectra and other characteristics of the stars. Popular Astronomy, 22(May), 275–294.Google Scholar
Russell, H. N. 1914b. Relations between the spectra and other characteristics of the stars. Popular Astronomy, 22(June), 331–351.Google Scholar
Russell, H. N. 1931. Notes on the constitution of the stars. MNRAS, 91(June), 951–966.Google Scholar
Russell, H. N., Dugan, R. S., and Stewart, J. Q. 1927. Book Review: Splendour of the Heavens, a Popular Authoritative Astronomy. Popular Astronomy, 355.
Saha, P. 1998. A method for comparing discrete kinematic data and N-Body simulations. AJ, 115(Mar.), 1206–1211.Google Scholar
Saha, P. 2003. Book Review: Principles of Data Analysis / Capella Archive, 2003. The Observatory, 123, 398.Google Scholar
Salaris, M. and Cassisi, S. 2005. Evolution of Stars and Stellar Populations. New York: Wiley.
Santos, N. C., Lovis, C., Pace, G., Melendez, J., and Naef, D. 2009. Metallicities for 13 nearby open clusters from high-resolution spectroscopy of dwarf and giant stars. Stellar metallicity, stellar mass, and giant planets. A&A, 493(Jan.), 309–316.Google Scholar
Schaltenbrand, R. A. 1974. Three-color photometry of SA 94 in the RGU system. A&AS, 18(Oct.), 27.Google Scholar
Sevenster, M., Saha, P., Valls-Gabaud, D., and Fux, R. 1999. New constraints on a triaxial model of the Galaxy. MNRAS, 307(Aug.), 584–594.Google Scholar
Shapley, H. 1960. Source Book in Astronomy, 1900–1950. Cambridge: Harvard University Press.
Siess, L., Forestini, M., and Dougados, C. 1997. Synthetic Hertzsprung-Russell diagrams of open clusters. A&A, 324(Aug.), 556–565.Google Scholar
Smith, R. W. 1977. Russell and stellar evolution – his “Relations between the spectra and other characteristics of the stars”. Dudley Observatory Reports, 13, 9–13.Google Scholar
Soderblom, D. R. 2010. The ages of stars. ARA&A, 48(Sept.), 581–629.Google Scholar
Southworth, J. 2011. Homogeneous studies of transiting extrasolar planets – IV. Thirty systems with space-based light curves. MNRAS, 417(Nov.), 2166–2196.Google Scholar
Stello, D., and 24 colleagues. 2009. Radius determination of Solar-type stars using asteroseismology: what to expect from the Kepler Mission. ApJ, 700(Aug.), 1589–1602.Google Scholar
Strand, K. A. 1968. Ejnar Hertzsprung, 1873–1967. PASP, 80(Feb.), 51.Google Scholar
Syer, D. and Saha, P. 1994. Bookmakers' odds for the sky distribution of gamma-ray bursts. ApJ, 427(June), 714–717.Google Scholar
Takeda, G., Ford, E. B., Sills, A., Rasio, F. A., Fischer, D. A., and Valenti, J. A. 2007. Structure and evolution of nearby stars with planets. II. Physical properties of 1,000 cool stars from the SPOCS Catalog. ApJS, 168(Feb.), 297–318.Google Scholar
Tolstoy, E. and Saha, A. 1996. The interpretation of color-magnitude diagrams through numerical simulation and Bayesian inference. ApJ, 462(May), 672.Google Scholar
Tolstoy, E., Hill, V., and Tosi, M. 2009. Star-formation histories, abundances, and kinematics of dwarf galaxies in the Local Group. ARA&A, 47(Sept.), 371–425.Google Scholar
Torres, G. 2010. On the use of empirical bolometric corrections for stars. AJ, 140(Nov.), 1158–1162.Google Scholar
Torres, G., Andersen, J., and Giménez, A. 2010. Accurate masses and radii of normal stars: modern results and applications. A&A Rev., 18(Feb.), 67–126.Google Scholar
Tosi, M., Greggio, L., Marconi, G., and Focardi, P. 1991. Star formation in dwarf irregular galaxies – Sextans B. AJ, 102(Sept.), 951–974.Google Scholar
Trotta, R. 2008. Bayes in the sky: Bayesian inference and model selection in cosmology. Contemporary Physics, 49(Mar.), 71–104.Google Scholar
Valenti, J. A. and Fischer, D. A. 2005. Spectroscopic properties of cool stars (SPOCS). I. 1,040 F, G, and K dwarfs from Keck, Lick, and AAT planet search programs. ApJS, 159(July), 141–166.Google Scholar
VandenBerg, D. A., Bergbusch, P. A., and Dowler, P. D. 2006. The Victoria-Regina stellar models: evolutionary tracks and isochrones for a wide range in mass and metallicity that allow for empirically constrained amounts ofconvective core overshooting. ApJS, 162(Feb.), 375–387.Google Scholar
VandenBerg, D. A., Casagrande, L., and Stetson, P. B. 2010. An examination of recent transformations to the BV(RI)C photometric system from the perspective of stellar models for old stars. AJ, 140(Oct.), 1020–1037.Google Scholar
van Dyk, D. A., Degennaro, S., Stein, N., Jefferys, W. H., and von Hippel, T. 2009. Statistical analysis of stellar evolution. Annals of Applied Statistics, 3, 117–143.Google Scholar
Vergely, J.-L., Köppen, J., Egret, D., and Bienaymé, O. 2002. An inverse method to interpret color-magnitude diagrams. A&A, 390(Aug.), 917–929.Google Scholar
Vogt, H. 1926. Die beziehung zwischen den massen und den absoluten leuchtkraften der sterne. Astronomische Nachrichten, 226(Jan.), 301.Google Scholar
von Hippel, T. 2005. From young and hot to old and cold: comparing white dwarf cooling theory to main-sequence stellar evolution in open clusters. ApJ, 622(Mar.), 565–571.Google Scholar
von Hippel, T., Jefferys, W. H., Scott, J., Stein, N., Winget, D. E., De Gennaro, S., Dam, A., and Jeffery, E. 2006. Inverting color-magnitude diagrams to access precise star cluster parameters: a Bayesian approach. ApJ, 645(July), 1436–1447.Google Scholar
Waterfield, R. L. 1956. Report of his observatory. MNRAS, 116, 217.Google Scholar
Waterfield, R. L. 1956. J. Brit. Astr. Assoc., 67, 1.
Wilson, R. E. and Hurley, J. R. 2003. Impersonal parameters from Hertzsprung-Russell diagrams. MNRAS, 344(Oct.), 1175–1186.Google Scholar
Yadav, R. K. S., and 9 colleagues. 2008. Ground-based CCD astrometry with wide-field imagers. II. A star catalog for M 67: [email protected] m MPG/ESO astrometry, FLAMES@VLT radial velocities. A&A, 484(June), 609–620.Google Scholar
Yıldız, M. 2007. Models of α Centauri A and B with and without seismic constraints: time dependence of the mixing-length parameter. MNRAS, 374(Feb.), 1264–1270.Google Scholar
Yıldız, M., Yakut, K., Bakis, H., and Noels, A. 2006. Modeling the components of binaries in the Hyades: the dependence of the mixing-length parameter on stellar mass. MNRAS, 368(June), 1941–1948.Google Scholar
Young, P. A., Mamajek, E. E., Arnett, D., and Liebert, J. 2001. Observational tests and predictive stellar evolution. ApJ, 556(july), 230–244.Google Scholar
Yuk, I.-S. and Lee, M. G. 2007. Modeling star formation history and chemical evolution of resolved galaxies. ApJ, 668(Oct.), 876–890.Google Scholar
Zwitter, T., and 25 colleagues. 2010. Distance determination for RAVE stars using stellar models. II. Most likely values assuming a standard stellar evolution scenario. A&A, 522(Nov.), A54.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×