Determination of stellar physical parameters using VOSA

Step 3.- Cut and paste in a file the list of objects in “VOSA format” included in vosa_usecase1.txt

 

 

 

Step 4.- Upload the file in VOSA (“File to upload”). Give a description (free text) and do not forget to select “magnitudes” as file type. Then, click “Upload”. The message “your-file-name” has been succesfully uploaded! will appear. Click “Continue”.

 

 

 

Step5.- Skip the tag “Objects”. With the next tag (“VO Phot.”) we can complement our “user photometry” with photometry found in VO services. For this use case, click “unmark All” and select only 2MASS, WISE and APASS. Then, click “Query selected services” at the bottom of the page. Once this is done, a summary table with the VO photometry (in flux units) will appear.

 

 

 

Step6.- This tag gives us the possibility of visualising/modifying the SED before the model fitting. Bad photometric points / upper limits can be deleted / not included in the fitting by cliking on the corresponding check box and click on “Apply changes”. If VOSA detects an infrared excess, the photometric points are drawn in black and are not considered in the fitting process. The user can manually overrride it and specify a new limit in the “Excess” panel. Veiling can also be taking into account: Photometric points bluewards than the wavelength included in the “Apply UV/blue excess up to” box will not be included in the fit. For this use case, do not make any change.

 

 

 

Step7.- In the next tag (“Chi-2 Fit”), different grids of theoretical models covering different ranges of physical parameters are displayed. For this case, click “unmark All” and select only the “BT-Settl-CIFIST”. To save time, do not tick either “Include model spectrum in fit plots?” or “Estimate fit parameter uncertainties using an estatistical approach”. Finally, click on “Next:Select model params”.

 

Step8.- In this window, we can refine the range of physical parameters that will be used for the fit. We will make the following assumption:

Teff: 2000-5000K

logg: 3.5-5.0

meta=0.

Then, click on “Next: Make the fit”.

 

Step9.- We can now see a summary table with the best fit results. Click on “Show graphs” to have a look at the graphics. The effective temperatures and logg obtained after the fitting are:

LOri0005: Teff: 3900K logg: 3.5

LOri0029: Teff: 3600K logg:4.0

LOri0048: Teff: 3600K logg: 4.0

LOri0158: Teff: 3300K logg:4.5

LOri0162: Teff: 2350K logg:3.5

 

 

Step10.- Alternatively, you can perform a Bayesian fitting using the “Bayes analysis” tag. To do so, we select the same collection of models and range of physical parameters as in Step9. Then, click “Make the fit”. A summary table with information on the model with the highest probability is shown. For each object, the information is graphically displayed by clicking on the object name (top left panel).

LOri0005: Teff: 3900K(99.97 %) logg:3.5 (97.03%)

LOri0029: Teff:3600K (37.85 %) logg:4.0 (36.90%)

LOri0048: Teff: 3600K (44.44 %) logg:4.0 (62.33%)

LOri0158: Teff: 3300K (80.24 %) logg: 4.5 (50.72%)

LOri0162: Teff: 2350K (71.72 %) logg: 3.5 (38.14%) 

 

 

Step11.- In order to estimate ages and masses for our objects we will make use of the “HR Diag.” tab. Click on “Make the HR diagram”. Ages derived for LOri0005, LOri0029 and LOri0048 are consistent with the age of the cluster (upper limit: 12-16 My).

 

 

 

Step12.- You can save different type of results (plots, VO photometry, Bayes fit, chi-2 fit,…) using the “Save Results” tag.

 

 

 

Step13.- A summary of all steps executed to carry out the workflow can be found in the “Log” tag.

 

 

 

Step14.- A detailed description of how VOSA works can be found in the “Help” tag.