Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals

Details Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals

Dec 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004aas...20513505d&link_type=abstract

American Astronomical Society Meeting 205, #135.05; Bulletin of the American Astronomical Society, Vol. 36, p.1565

Other

Scientific paper

The NASA Space Interferometry Mission will measure the astrometric procession of nearby stars caused by the orbits of unseen planetary companions. The uncertainty in the orbit of a planetary companion is subject to the number, duration, and span of the observations, among other factors, and is best quantified using a Markov Chain Monte Carlo algorithm. MCMC fits to astrometric data are analogous to those of radial velocity surveys. MCMC allows non-Gaussian parameter distributions, which for some systems can uncover the correlations between orbital parameters, and can be extended to fit for multiple planet systems. MCMC can also project when the most beneficial measurements should be made for each star, providing SIM with the most efficient observation schedule.

Affiliated with

Also associated with

No associations

Rating

Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Fitting Astrometric Data With Markov Chain Monte Carlo: A Tool for Detecting Planetary Signals will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1643183