Hi Folks:

I'm rather new at this, so bear with me. :-)

When submitting observations to the AID, I'm wondering what error to report. When I do photometric reduction on an image using VPhot I get the following:

Target Mag Err Std Err(SNR) SNR Sky

TX Per 10.198 0.224 0.224 0.003 398 7

Now, up to this point I've been reporting (using this instance as an example) an error of 0.224, but in this example that seems an awful large error to me. When I took an estimate of AF And the other day and had a similar error I attributed it to a faint star and an underexposed image (for the star brightness I was taking). But this is not that way with TX Per. I got a good image. Its not faint, its sharp, its good. I don't think the magnitude error should be 0.224m.

Is this the error I should be reporting, or am I doing this totally wrong?

Thanks, guys!

----

Doc Kinne, KQR

Hi Doc,

That is the error to report (that is, it will be included in the AAVSO report file).

But I agree, it does sound large, especially if you think the image is good.

I can have a look at it if you like, to see if I can spot anything unusual.

Geir

Very interesting post regarding errors, but it refers to errors in

onelonely image.But what would be the correct error report for a bunch of images for instance, of a

non variable star if my final photometric measure was the arithmetic mean of all values of the bunch? Of course, each of the previous images have their corresponding error measured as said before.It would be the arithmetic mean of all errors as well?

Or would be the maximum value of all?

Or may be the "mean cuadratic error" of the all photometric measures interpreted as

From a probabilistic point of view this last option would be the correct, but is it the commonly done in practice?

Kind regards.

Illekaseki

Since this is already a thread about errors, I will use. I hope, this is okay...

I have the following Problem:

I took images of R Leo in different filters (B and V). There are only 2 comp stars in this field. When I use one of them as a check star, I get errors like 0.02 (or much better), although the difference between the messured value of my check star and its literature value differ much more, like 0.2. When I use both stars as comp stars, I get realistic values for the errors.

But the "report-function" says, that I have to use a check star, when I have more than 1 comp star.

What should I do in cases like this?

Another question: I have sometimes pretty bad pictures (due to bad guiding and seeing) which give me errors like .4 or .5. Is it still usefull to report those values, or not?

Hi, when you look at the photometry report for your image, you must see wich error is induced by faintness and poor SNR of some of the comparison stars. If you uncheck comp. stars with the worst SNR or wich adds more discrepancy (according to the hue of red), and press "refresh", you would get a magnitude value with better precision, closer to error according to SNR.

I've learned of that recently. It's worth the effort to check what comp. stars are you using when you measure in VPHOT.

Yes, I can use this methode if I have a few comp stars. But in this case I only have two of them. Both have similar brightnesses and SNR. The SNR ist not the problem, but the FWHM, which ist probably too big: about 6 pixels.

I finally figured out, how VPhot determines the magnitudes.

I still would like to know, how it calculates the errors. Is there any documentation about this?

It is logical, that the error, or better: uncertainty, of my measurement should decrease when I increase the number of comp stars. In VPhot the error increases, when I use two comp stars instead of one. Therefore, I would like to know, how VPhot determines the errors.

When I do my own error-calculations, I get different values and they do decrease with more comp-stars.

Sorry for perhaps beeing so annoying about this, but as a physicist, I know how important it is to give a good approximation of the uncertainties of measurements

The error estimate is calculated in two different ways depending on wether one or more comp stars are used, which probably explains what you observe.

In the case of a single comp star an error estimate is calculated for both the target star and the comp star, based on the stars Signal-to-Noise-Ratio, as

Err(SNR) = 2.5 * Math.Log10(1 + 1 / SNR)

SNR is calculated using the "CCD equation" involving ADU, gain etc, ref. the AAVSO CCD observer manual. Err(SNR) is displayed in the target star estimate table on the single image report page. The final error estimate is then the sum of squares of Err(SNR) for target and comp star:

Err = Sqrt( Err(SNR)t*Err(SNR)t + Err(SNR)c*Err(SNR)c )

In the case of multiple comp stars it is preffered that the standard deviation of the comp stars target estimate is used. The Single Image Photometry report table of comparison stars has a field called "Target estimate". The standard deviation of the mean of all the values in that field. This is listed as Std in the target estimate table on the same page. Now the final error estimate is taken as

Err = sqrt( std*std + Err(SNR)*Err(SNR) )

where Err(SNR) is as described above. This should be a conservative estimate.

The advantage of using the std is that it covers all kinds of errors, for instance errors in the sequence. If the comp stars magnitudes are inaccurat, perhaps an average from many catalogs of various quality, you might get a bad result even with bright stars with high SNR.

Thanks, this is the explanation I was also looking for.

Remaining question for me is the interpretation of the meaning of the given Err value - in terms of one Sigma as standard deviation or in terms of a range Mag +/- Err or ..?

Regards

Wilfried

Hello, I would be extremely happy if someone can help me in overcoming the following problem in V-star

While uploading a text file I am getting following message

org.aavso.tools.vstar.exception.ObservationReadError:No observations for the specified period or error in observations sources.

If some one has encounter this problem in the past please share the solution.

Regards

Santosh