Radial Velocity Data fitting

In summary, the conversation is about finding the best Keplerian fit to Radial velocity data using freeware. Suggestions for a program called Systemic Console and the possibility of programming it oneself are mentioned.
  • #1
Hi all,
I am attempting to find the best Keplerian fit to the Radial velocity data vs. Time such as this plot: http://austral.as.utexas.edu/planets/hd37605/hd37605.html
I was wondering whether anyone could suggest some freeware that might be able to help me out. Any information would be helpful.
If at all possible, suggestions for freeware that runs in windows would be awesome!
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  • #2
Do you have any interest in programming? If so, I could show you how to program such a beast yourself, so that it generates data that can be used to draw a similar graph in Gnuplot.
  • #3
Sorry for bringing up the old post but...


There is a program called Systemic Console that can be obtained @ www.oklo.org. There is a whole group of people that collaborate to find the best fits for a wide range of systems. And best of all, everything is free.


I would be interested if you could provide some sort of basic writeup of what would be needed to write such a program. I have been somewhat interested in programing for a while (although my skills are still extremely limited) and that sounds like it would be a very interesting/educational project.

1. What is radial velocity data fitting?

Radial velocity data fitting is a technique used in astronomy to measure the movement of stars or other celestial objects by analyzing the Doppler shift of their spectral lines. This method allows scientists to determine the speed and direction of an object's movement, and can also be used to detect the presence of orbiting exoplanets.

2. How is radial velocity data collected?

Radial velocity data is typically collected using a spectrograph, which splits light from a star into its component wavelengths. This produces a spectrum of the star's light, which can then be analyzed for changes in the position of spectral lines. These shifts in position are caused by the Doppler effect, which occurs when an object is moving towards or away from the observer.

3. What are the challenges of fitting radial velocity data?

Fitting radial velocity data can be challenging due to various factors such as instrumental effects, atmospheric conditions, and the presence of multiple objects in a system. These factors can introduce noise and make it difficult to accurately measure the velocity of an object. Additionally, the presence of exoplanets can cause subtle changes in the velocity of a star, which must be carefully accounted for in the data fitting process.

4. What techniques are used for radial velocity data fitting?

There are several techniques used for radial velocity data fitting, including cross-correlation, Fourier analysis, and least-squares fitting. These methods involve comparing the observed spectrum to a theoretical model and adjusting parameters until the best fit is achieved. Some techniques also involve the use of statistical tools, such as Bayesian analysis, to account for uncertainties in the data.

5. What can we learn from radial velocity data fitting?

Radial velocity data fitting can provide valuable information about the properties of stars and other celestial objects, such as their mass, rotation, and orbiting companions. This data can also be used to search for exoplanets and study their characteristics, such as size, mass, and orbital period. Additionally, by analyzing radial velocity data over time, scientists can track the long-term movement and evolution of objects in our universe.

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