-- AriannaSaba - 31 Jan 2019

Following the observation done on Monday, I analysed the data taken with my current algorithm.

We took pictures of M35 with different exposure times (60, 90, 120 seconds) and with all filters (red, green, blue, clear).

Other than taking pictures of the core part of the cluster, we also slewed the telescope one frame up and one frame down the initial set up in order to catch the rest of the cluster which might not have fitted in the first frame. This was done trying to consider a reference star on the lower or upper edge of the frame and moving the telescope until the star just disappeared from the frame.

In my analysis I combined the 3 frames together and analysed these as if it was a single bigger picture. This was done with the function np.concatenate along axis=0

I employed my algorithm to display the fits images taken with the 3 filters and doing B-V. The exposure time I chose was 90 seconds.

I calculated B-V simply doing the blue array minus the green array.


For each filter I calculated some statistics:







The flux was calculated by taking the mean value of counts of each pixel in the star (pixel value divided by the number of pixels in the star). This this value was then multiplied by the gain and divided by the exposure time. The error on the flux is the sqrt of it.

The magnitude was calculated as -2.5*np.log10(flux). The error in the magnitude = abs(-2.5/np.log(10)) * (error in flux/flux).

Plots of stars for each filter:




The stars found with the red filter were 198, blue 102, green 117.

B-V did not find any star because the threshold was higher than the mean: I have to investigate further why this has happened.


  • Next steps are to match same stars in different frames so that we don't count the same star twice.
  • No V vs B-V plot could be made
  • Histograms would take too much time to plot, so commented out that part. Still used the gaussian threshold.
  • Images size was (1017, 1530). Dark frames were instead (1020,1530).
Topic attachments
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PNGpng BV_fits.png r2 r1 manage 19.1 K 31 Jan 2019 - 10:24 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.30.53.png r1 manage 46.5 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.31.04.png r1 manage 96.9 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.31.17.png r1 manage 99.5 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.31.24.png r1 manage 99.6 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.31.32.png r1 manage 94.5 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.31.41.png r1 manage 101.2 K 31 Jan 2019 - 10:32 AriannaSaba  
PNGpng Schermata_2019-01-31_alle_10.54.39.png r1 manage 44.2 K 31 Jan 2019 - 10:55 AriannaSaba  
PNGpng blue_cluster-2.png r1 manage 22.1 K 31 Jan 2019 - 11:14 AriannaSaba  
PNGpng blue_cluster.png r1 manage 20.8 K 31 Jan 2019 - 10:51 AriannaSaba  
PNGpng blue_fits.png r2 r1 manage 68.5 K 31 Jan 2019 - 10:24 AriannaSaba  
PNGpng green_cluster-2.png r1 manage 22.8 K 31 Jan 2019 - 11:14 AriannaSaba  
PNGpng green_cluster.png r1 manage 23.5 K 31 Jan 2019 - 10:51 AriannaSaba  
PNGpng green_fits.png r2 r1 manage 71.8 K 31 Jan 2019 - 10:24 AriannaSaba  
PNGpng red_cluster.png r1 manage 24.7 K 31 Jan 2019 - 10:51 AriannaSaba  
PNGpng red_fits.png r2 r1 manage 75.6 K 31 Jan 2019 - 10:25 AriannaSaba  
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Topic revision: r1 - 31 Jan 2019 - AriannaSaba

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