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Predicting the Yields of Photometric Surveys for Transiting Planets

Published online by Cambridge University Press:  01 May 2008

Thomas G. Beatty*
Affiliation:
Department of Physics and MIT Kavli Institute, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139 email: [email protected]
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Abstract

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Observing extrasolar planetary transits is one of the only ways that we may infer the masses and radii of planets outside the Solar System. As such, the detections made by photometric transit surveys are one of the only foreseeable ways that the areas of planetary interiors, system dynamics, migration, and formation will acquire more data. Predicting the yields of these surveys therefore serves as a useful statistical tool. Predictions allows us to check the efficiency of transit surveys (“are we detecting all that we should?”) and to test our understanding of the relevant astrophysics (“what parameters affect predictions?”). Furthermore, just the raw numbers of how many planets will be detected by a survey can be interesting in its own right. Here, we look at two different approaches to modeling predictions (forward and backward), and examine three different transit surveys (TrES, XO, and Kepler). In all cases, making predictions provides valuable insight into both extrasolar planets and the surveys themselves, but this must be tempered by an appreciation of the uncertainties in the statistical cut-offs used by the transit surveys.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2009

References

Beatty, T. G. & Gaudi, B. S. 2008, ArXiv e-prints, 804, arXiv:0804.1150Google Scholar
Brown, T. M. 2003, ApJ, 593, L125CrossRefGoogle Scholar
Charbonneau, D., Brown, T. M., Burrows, A., & Laughlin, G. 2007, Protostars and Planets V, 701Google Scholar
Cumming, A., Butler, R. P., Marcy, G. W., Vogt, S. S., Wright, J. T., & Fischer, D. A. 2008, PASP, 120, 531CrossRefGoogle Scholar
Fischer, D. A. & Valenti, J. 2005, ApJ, 622, 1102CrossRefGoogle Scholar
Fressin, F., Guillot, T., Morello, V., & Pont, F. 2007, A&A, 475, 729Google Scholar
Gillon, M., Courbin, F., Magain, P., & Borguet, B. 2005, A&A, 442, 731Google Scholar
Gould, A. & Morgan, C. W. 2003, ApJ, 585, 105CrossRefGoogle Scholar
Gould, A., Dorsher, S., Gaudi, B. S., & Udalski, A. 2006, AcA, 56, 1Google Scholar
Horne, K. 2003, ASP Conf. Ser. 294: Scientific Frontiers in Research on Extrasolar Planets, 294, 361Google Scholar
Marcy, G., Butler, R. P., Fischer, D., Vogt, S., Wright, J. T., Tinney, C. G., & Jones, H. R. A. 2005, Progress of Theoretical Physics Supplement, 158, 24CrossRefGoogle Scholar
McCullough, P. R., et al. 2006, ApJ, 648, 1228CrossRefGoogle Scholar
Pepper, J., Gould, A., & Depoy, D. L. 2003, AcA, 53, 213Google Scholar
Pepper, J. & Gaudi, B. S. 2005, ApJ, 631, 581CrossRefGoogle Scholar
Pont, F., Zucker, S., & Queloz, D. 2006, MNRAS, 1146Google Scholar
Santos, N. C., Israelian, G., & Mayor, M. 2004, A&A, 415, 1153Google Scholar
von Braun, K. & Ciardi, D. R. 2007, ArXiv e-prints, 711, arXiv:0711.4256Google Scholar