Statistics – Computation
Scientific paper
Oct 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011epsc.conf.1387p&link_type=abstract
EPSC-DPS Joint Meeting 2011, held 2-7 October 2011 in Nantes, France. http://meetings.copernicus.org/epsc-dps2011, p.1387
Statistics
Computation
Scientific paper
In this work we present a method that can be used as a tool for investigating such planetary systems in the framework of classic regression analysis. The base of the method is the employment of the Lie-integration method [3] that provides the solution of the differential equations (that describe the interacting planetary dynamics) in the form of power series and therefore provides a way to exploit the properties of the integrator for further analytical computations, such as error propagation calculations. This analytical description is rather relevant in the cases of not-so-well constrained orbital elements (for instance, mutual inclination): letting these parameters be varied might yield an unexpectedly high correlation that affects badly the otherwise efficient alternative methods, such as Monte- Carlo estimations. This analytical treatment aids us to perform almost any kind of regression analysis method as simple as it would be in case of well-known and or other well-behaved functions. Based on previously developed methods for similar types of analysis of radial velocity variations in multiple planetary systems [4], we present further possible applications discussing the above mentioned aspects of multiple transiting planetary systems. These applications include creating observation strategies for follow-up of Kepler discoveries after the mission, adaptive observation scheduling focusing on the more effective refinement of selected orbital parameters and of course, precise and accurate estimation of masses, orbital elements and their respective uncertainties.
Borkovits Tamás
Pal Abhijit
Szakats Robert
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