Statistics – Computation
Scientific paper
Sep 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011ess.....2.1902k&link_type=abstract
American Astronomical Society, ESS meeting #2, #19.02
Statistics
Computation
Scientific paper
Exomoons represent a formidable and alluring challenge to exoplanetary science. The detection of such objects would be of major value to planetary formation theory, astrobiology and observational astronomy. Presently, it is conceived that transit timing methods offer the most plausible route to achieving a detection but achieving the necessary signal-to-noise remains daunting. Here, we present a new algorithm which dynamically models these transit timing effects plus the eclipses of the moon itself. Our new algorithm, LUNA, computes all known observational effects which a moon imparts on a light curve and thus achieves the maximum possible sensitivity. LUNA is completely analytic and executes in almost the same computational time as generating a planet alone. Therefore, LUNA will be a potent weapon in future exomoon searches. Example implementations of LUNA will be presented.
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