This project aims:
1) to get more efficient and accurate convergence and better
search algorithms to explore many-dimensional parameter space for the deepest
minimum;
2) to model eclipses of translucent clouds of material produced by collision
of stellar winds in the atmospheres of high-temperature stars where plasma
dominates over normal matter,
3) to incorporate hydrodynamic flow code to model systems with gas streams
between stars;
4) to include techniques to explore the effects of star spots and other
phenomena associated with active regions;
5) to survey star clusters and associations
for new variables; and
6) to follow up these discoveries with further study with RAO instruments.
Aim 5) requires an upgrade of a high-quality optical telescope originally designed for satellite tracking and the development of cameras and software, and 6) requires an infrared camera. Observations of starlight are to be combined with high quality spectroscopic data from the outside groups such as Latham's group based at CFA- Harvard. We plan to extend the modeling tools and techniques to young, massive objects which are still close to the regions of their births in the expanding stellar associations of the Milky Way; the location of such systems in ensembles provides a bootstrap for exploring both the systems and their wider environment and so the circumstances of their origins. The data capable of being modeled with the new tools will be from a wide variety of wavelengths from x-rays to microwaves, involving data from space and satellites as well as ground-based observatories.
Note that an important part of the program over the years has been to convert the RAO's Baker-Nunn satellite-tracking camera into a wide-field imaging camera to permit a broader search for variables stars among the young open clusters and associations of the Milky Way, and the construction of an IR camera.
Nearly all the long-range goals have been achieved, but the last (an IR camera developed with a donated engineering array has, unfortunately, not proven to be of sufficiently high sensitivity to be useful for stellar work).
Finally, an improved set of IR passbands (Young,
Milone, & Stagg 1994; Milone & Young 2005, 2007) is now available to get
the best possible precision from IR photometry, especially when
carried out from sites other than the highest and driest in the world.
(See: Astronomical Instrumentation & Techniques,
Optical & Infrared Photometry,
and
WD93K93 now employs Kurucz atmosphere models for a range of chemical
composition, each integrated over selected photometric passbands, and for narrow
ranges of ultraviolet flux from satellite observations. The improvements permit full
analysis of high-precision data from the far UV to the intermediate infrared for a
range of chemical compositions for the first time.
It is easy to provide an example of the superiority of these modern tools: in an
ongoing study of the 24.6d evolved but otherwise uncomplicated eclipsing system AI
Phoenicis, the masses and radii of the component stars have been determined now to
better than 1%. These are among the best stellar determinations ever obtained,
especially for evolved stars, but we intend to go further. Further improvements can
be anticipated as the calibration of the temperature scale improves. Even now, the
data place sharp constraints on model mixing length, age, and chemical composition.
For close binary stars, the case is usually complicated by interaction effects, so
special tools are needed to produce precise results. In the case of contact systems,
stars in the process of merging, in which an outer envelope is shared between the
component stars, evolution calculations must be invoked to estimate the loss in mass
from the system and the degree to which mass has transferred from one component
to the other. Here, too, however, work by Rucinski (1994, 1995) suggests
that such objects may be usable as standard candles.
The historical development of modern light curve analysis codes and our
contributions to it are discussed in several papers in Milone (1993), which also
describe the current state of the art of light curve modeling. As excellent as our
existing modeling tools and observing capabilities are, however, there are important
areas that need further improvement before their full potentials can be reached.
An efficient procedure for locating a solution once the general properties, and thus
the parameter constraints, are known is an important goal. Terrell developed
PC front-end software for use with WD93K93 which is capable of selecting solution
subsets with the smallest error predictions and resubmitting an altered input file.
However, as university servers become swamped because memory upgrades are
outpaced by increases in numbers of users, even slight inefficiencies will begin to
tell. For example, a typical simplex set of 150 iterations could
take as much as a day or two to run during Fall or Winter term
sessions, despite the high benchmarks of the IBM RS6000
system in use at the University of Calgary to late ~2004.
Thus, it is imperative that the code be highly
efficient for any platform on which it may be run.
Damped least squares (DLS) was invented a considerable while ago
(Levenberg 1944) and has been independently reinvented many times since then
(e.g., by Girard 1958; Wynne 1959; Marquardt 1963; Hoerl and Kennard
1970). The method has been variously described as an interpolation between
gradient methods and simple least-squares differential corrections, as a maximum-
neighborhood confidence region technique, or as a step-limiting method to prevent
solution blow-up in ill-conditioned problems. But it is best viewed as a means of
selecting only the well-determined eigenvectors of the matrix of the normal
equations (cf. Matsui and Tanaka 1992, 1994, 1995 as examples).
Numerous comparisons of methods for function optimisation (e.g., Meiron
1965; Pitha and Jones 1966; Kidger and Wynne 1967; Bard 1970; Gans 1976;
Hiebert 1981) have shown that DLS with multiplicative damping is among
the very best methods for nonlinear problems, and it is now generally recognized as
the first choice for nonlinear least-squares problems.
Young has used DLS for nearly 20 years to solve nonlinear least-squares
problems in planetary physics, spectroscopy, and astronomical photometry (Young
1982, Young & Young 1977a,b, 1978, 1979). It is now routinely used
in both Wilson's own updated version of his software, and in our
versions of it.
which contains the latest fully documented and public version, SHELLSPEC07.
Josef and I have summarized the current state of light curve modeling as we know it
in our paper "The Tools of the Trade and the Products they Produce: Modeling of
Eclipsing Binary Observable," in Short-Period Binary Stars: Observations,
Analyses, and Results," (2007), eds. E.F. Milone, D.A. Leahy, & D.W. Hobill,
(Dordrecht: Springer), pp. 195-219.
Bard, Y. (1970). SIAM. J. Numerical Analysis 7, 157.
Cherepashchuk, A.M. (1993). in Light Curve Modeling of Elipsing Binary Stars, Milone, ed., (New York: Springer-Verlag), p. 189.
Davidge, T., and Milone, E.F. (1984) ApJS, 55, 571.
Gans, P. (1976). Coord. Chem. Rev., 19, 99.
Girard, A. (1958). Rev. Opt., 37, 231.
Hiebert, K.L. (1981). ACM Trans. Math. Software, 7, 1.
Hill,G., and Rucinski, S. (1993). in Light Curve Modeling of Elipsing Binary Stars, Milone, ed., (New York: Springer-Verlag), 1993, p. 135.
Hill, Fisher, and Holmpen (1989). A&A , 218, 152.
Hoerl, A.E. and Kennard, R.W. (1970). Technometrics, 12, 55.
Kallrath, J. (1993). in Light Curve Modeling of Elipsing Binary Stars, Milone, ed., (New York: Springer-Verlag), p. 39.
Kallrath, J. and Milone, E.F. (1999). Modeling and analysis of Elipsing Binary Light Curves, (New York: Springer-Verlag),
Kaluzny, J. and Rucinski, S.M. (1994). MNRAS, 265, 34.
Kidger, M.J. and Wynne, C.G. (1967). Optica Acta, 14, 279.
Levenberg, K. (1944). Quart. J Applied Math., 2, 164.
Marquardt, D.W. (1963). SIAM J 11, 431.
Matsui, H., and Tanaka, K. (1992). Applied Optics, 31, 2241.
Matsui, H., and Tanaka, K. (1994). Applied Optics, 33, 2411.
Matsui, H., and Tanaka, K. (1995). Applied Optics, 34, 642.
Meiron, J. (1965). J. Optical Soc. America, 55, 1105.
Miller, B., Budaj, J., Richards, M., Koubsk, P., and Peters, G.J. (2007), ApJ, 656, 1075.
Milone, E.F., ed. (1993). Light Curve Modeling of Elipsing Binary Stars, (New York: Springer-Verlag).
Milone, E.F., and Kallrath, J. (2007). in Short-Period Binary Stars, in press.
Milone, E.F., and Young, A.T. (2005). PASP, 117, 485-502
Milone, E. F., Young, A. T. (2007). "Standardization and the Enhancement of Infrared Precision", in The Future of Photometric, Spectrophotometric and Polarimetric Standardization, ed. C. Sterken. ASP Conference Series, 364, 387-407.
Milone, E.F., Stagg, C.R., Sugars, B.A., McVean, J.R., Schiller, S.J., and Kallrath, J. (1995). AJ, 109, 359.
Pitha, J. and Jones, R.N. (1966). Can. J. Chemistry, 44, 3031.
Rucinski, S.M. (1994). PASP, 106, 462.
Schiller, S.J. & Milone, E.F. (1987). AJ, 93, 1471.
Schiller, S.J. & Milone, E.F. (1988). AJ, 95, 1466.
Terrell, D.C., and Wilson, R.E. (1993) in Light Curve Modeling of Elipsing Binary Stars, Milone, ed., (New York: Springer-Verlag), p. 27.
Terrell, D.C. (1994). Circumstellar Hydrodynamics and Spectral Radiation in Algols. PhD Thesis. (Gainesville: Univ. of Florida).
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Young, A.T. (1992). PEPSYS General Photometry Package, in MIDAS Users Guide. (Garching: European Southern Observatory).
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Young, L.D. Gray, and Young, A.T. (1977b). J. Quant. Spectroscopy & Radiative Transfer, 18, 185.
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Young, A.T., Milone, E.F., and Stagg, C.R. (1994). A&A, 105, 259.