In this page we explain how the data should be prepared for the analysis by RTModel. You can find some sample events already prepared in the directory events. These can be useful to see how an event directory should look like at the beginning or at the end of the modeling run.
Each microlensing event should have its own dedicated directory somewhere on your PC (e.g. /event001/).
This directory should contain a subdirectory named /Data.
The /Data directory should contain all photometric time series available for the analysis. Each series (data collected by a single telescope in one filter) corresponds to one file with extension .dat.
Note that each filename ending with a number will be interpreted as a dataset taken by the corresponding satellite (e.g. Spitzer1.dat). Ground dataset filenames should never end by a number! We will come back to fitting satellite datasets later on.
The content of each .dat file should be as in the following example:
# Mag err HJD-2450000
19.0232 0.012 8370.1223
19.0150 0.011 8370.2421
19.0034 0.011 8370.3697
18.9712 0.010 8370.4911
18.9592 0.011 8370.6114
18.9109 0.009 8370.8234
18.8798 0.009 8371.0092
...
The first line is a header specifying the content of the columns.
RTModel accepts both input in magnitudes or fluxes.
If the header contains the keyword "Mag", then RTModel assumes that each line contains magnitude, error and Heliocentric Julian Date - 2450000 for each individual photometric measurement.
If the header DOES NOT contain the keyword "Mag", then RTModel assumes that each line contains flux, error and Heliocentric Julian Date - 2450000 for each individual photometric measurement.
Event coordinates are contained in a file with extension .coordinates (e.g. event001.coordinates) placed in the same /Data directory along with the photometry files.
The content of the file should be in the form HH:MM:SS.S +DD:PP:SS.S for right ascension and declination respectively, e.g. 18:00:23.32 -32:11:09.7.
Other optional input files are observations from satellite, limb darkening coefficients and normalizations for datasets, described in the corresponding pages. Astrophotometric datasetes are also discussed in a separate page.