[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
RE: Data reduction methodology for V-I colors
Hey Michael,
I'll show my ignorance here. Seems like you can only use one zero point
across the entire night if you have no changing conditions across the entire
night (clouds, seeing?). And, you would have to be careful to only take
pictures during astronomical twilight. And, hope you live in an evenly dark
location (no nearby city/town). Don't all these factors add up to a
different zero point for every frame?
Just curious, as I do solve a color term for the night, and a unique zero
point for every frame. All at the same time (V and I). A nice, iterative
solution where I suspect some of my problems might be creeping in.
Cheers,
Rob
> -----Original Message-----
> From: owner-tass@listserv.wwa.com
> [mailto:owner-tass@listserv.wwa.com] On Behalf Of Michael Koppelman
> Sent: August 31, 2004 11:24 AM
> To: tdroege2@earthlink.net
> Cc: tass
> Subject: Re: Data reduction methodology for V-I colors
>
>
> But aren't you getting a different zeropoint solution for
> every frame?
> Why not use a single zeropoint for the entire night?
>
> On Aug 31, 2004, at 12:20 PM, Thomas Droege wrote:
>
> > Mike,
> >
> > Yep, this and a lot more. I cannot identify a "bad" night. I did a
> > lot of
> > work on the assumption that there was such a thing as a bad
> night. For
> > example, go through all the data and look for stars with
> big deviations
> > from the mean. (This should work because most stars are not
> > variable.) Now
> > sort all frames by fraction of stars with big deviations
> from the mean.
> > Now eliminate these from the data set and look at the result. I did
> > this
> > eliminating the noisiest 10%, 20%, 50% ... No improvement
> at any cut
> > level. Conclusion: Eliminating frames with lots of deviant
> > measurements
> > does not improve the quality of the data as a whole. No doubt
> > eliminating
> > noisy frames will improve the data when we solve other
> problems. But
> > noisy
> > frames are not even close to being the largest source of
> error or the
> > above
> > experiment would have made some improvement. It made no
> improvement.
> > I
> > was surprised. But when you think about it, the star measurement
> > scheme
> > that Michael uses really does a good job. It is something else.
> > Something
> > fundamental. Something related to position in the frame. If you
> > track a
> > field, the result is much better. But this just hides the problem.
> >
> > I think there are two likely suspects. I am working on
> one, Michael
> > is working on the other.
> >
> > 1) There is some gradient in the sky that produces errors in all
> > frames.
> >
> > Michael is working on this.
> >
> > 2) We don't have a good reference catalog. The result is that
> > depending on
> > where a star is in a frame, a different set of reference stars are
> > used.
> > If the mean of the reference star set is different for the two frame
> > positions, then this will produce an error.
> >
> > I am working on this.
> >
> > OK, I suspect that both have an effect and that there are
> still more
> > problems to be found. I know that I have made some small
> improvements
> > using 2. I am just waiting for more data and winter time with no
> > observations to sit and compute on this for a couple of months.
> >
> > Tom Droege
> >
> >
> >
> >
> >> [Original Message]
> >> From: Michael Koppelman <lolife@bitstream.net>
> >> To: Tass <tass@listserv.wwa.com>
> >> Date: 8/31/2004 11:57:14 AM
> >> Subject: Re: Data reduction methodology for V-I colors
> >>
> >> This got me thinking and I'm sure there are tech notes and such I
> >> could
> >> find about it but nonetheless -- have you guys considered
> calibrating
> >> the night rather than the frame? i.e. take the whole
> dataset, read in
> >> all the stars from the entire night, throw out the ones with high
> >> errors, match up the Landolt/Henden or other standards and get
> >> transforms for the whole night?
> >>
> >> Cheers,
> >> Michael
> >>
> >
> >
>
>