Re: Observation data model comments

From: Anita Richards <amsr-at-jb.man.ac.uk>
Date: Sat, 8 May 2004 12:40:47 +0100 (BST)

On Sat, 8 May 2004, Alberto Micol wrote:

> > e.g. spatial coverage in objects/deg^2
>
> I would say that objects/deg^2 does not belong to "spatial coverage", it's
> instead a way to characterise the observation.
I don't quite understand what you mean - what class should objects/deg^2 be under? (in either case it is under the Characterisation superclass!)

This is what I meant: In the discussions about the Registry and Resource metadata, we discussed what spatial coverage and filling factor meant for observed data (images etc.) and for extracted data - source caalogues etc.

For images, the spatial coverage outer bounds are something like a box in RA and Dec. This may be subdivided into a few areas described here by Support. These two classes would probably be the same for extracted source catgalogues.

Within that, the coverage may again be sparse, for example a multi-beam survey which only covers certain strips, but rather than describe that in complicated detail I think that the filling factor for images describes how much of the area within each support is, on average, observed. Or it could be that if you had dithered over the sky with several partly overlapping WFPC2 pointings, the resulting image fits within a square but is too complicated to describe exactly, so you ahve covered 80% of the support.

However for extracted source catalogues, if the sources are close to point-like, then the most useful number for the user is the surface density of sources (e.g. if selecting among catalogues which are otherwise similar, you might want to search the one with the best fractional coverage first).

Your comment has made me realise that there is another case, which is catalogues of sources which are extended e.g. of HII regions or CO, in which case maybe the relevant filling factor is the fraction of the image with emission above the lower bound in flux density. But most catalogues don't make this obvious - at best you get the dimensions of a 2D Gaussian component fitted to the source or something.

> ---
> So, the observation is the same, it's the version that changes.
> (Hence, the requirement is that a VO identifier must be able to handle
> versioning.)

I will check if that works in the situations I am thinking of.

> You seem to separate Processing from Provenance. I would have tought that
> Processing is part of Provenance. Suppose that you want to describe a product
> which was generated by combining other products coming even from different
> instruments; in such case I would say that Processing and Provenance are very
> much intertwined.
>

Maybe that is before I put up my latest plot. I have now put Processing back as a part of Provenance but I am still a bit concerned as different processing methods will give data with different characterisation e.g. different synthesised beam size - for interferometry data you can re-weight the visibilities (as many times as you like) to give images with lower spatial resolution but greater sensitivity to extended flux (greater Max spatial scale) and lower noise rms - or v.v., higher spatial resolution but also higher noise and you lose extended flux of low surface brightness. So I am still a bit concerned whether in practice that can all be taken care of with versioning.

> ---
>
> Maybe a twiki problem ...
> > The gray boxes show classes which exchange information with other models,
> I can't see gray boxes, they are all white on my netscape/linux.
> I will try with macosx/safari ...

Sorry, next time I will make them darker. They are the ones which have lower-case prefixes (registry, quantity, community) They are OK with linux/mozilla (although the grey is similar to the blue of Characterisation on the screen, but not in hard copy).

> ---
>
> In the last table:
>
> Bounds: for Flux more than the noise rms I would use the limiting flux
> for the lower limit, and I would add the saturation level for the upper limit.
That is the difference between models for different situations, in radio interferometry the limiting flux is partly dependent on how you process the data and is normally taken as 3sigma noise (or more if noise is non-Gaussian) measured from the off-source image or region of the spectral or visibility domain. Similarly there is not usually a saturation upper limit (unless you are observing the Sun or very bad rfi or something else which makes a receiver go non-linear). There is a limit on the signal-to-noise ratio which you can achieve. However in Bounds I put quantities which are fixed limits for any one data product

> Support: for Flux I would use the min and max fluxes in the data.

That is a good idea as long as it is only applied where relevant. In the case of radio data, that is not always obvious or useful, especialy the min. which is some possibly negative noise level for total intensity images, whilst for Stokes Q it can be a meaningful negative value. If you want to know what is the minimum surface brightness object which can be found in total intensity in the data then some multiple of the noise rms is the best way.
Max is rather specialised for visibility data, for example in the combined visibilities plotted v. baseline length the max tells you what the total flux density within the field of view is on the max spatial scale to which the interferometer is sensitive. Radio models have to understand this but I don't think that it will do anything other than confuse most VO tools or users. However for total intensity images the max (in Jy/beam or Jy/object) could be useful, and for polarisation or spectral absorption images the min is too - thanks for suggesting that.

However that reminds me of another issue: most radio images are measured in Jy/beam (or mJy/beam etc.) but none of the VO tools I ahve used can interpret that. As I hope I ahve made clear, the beam size is roughly determined by the provenance but within a factor of 2 it is a property of variable processing - noted as Restoring Beam under Resolution under Characterisation. The pixel size of an image is arbitrarily chosen (there are sensible limits but it is not a direct function of resolution). If you use e.g. AVO-Aladin or SExtractor to 'measure' the flux at a particular pixel the flux density is actually in Jy/beam, but the tools think that it is in Jy/pixel or in some cases Jy/arcsec^2.

I think that the most important development for VOs to handle radio data properly is to figure out how to extract the beam size from (often obscure) places in FITS headers for radio images and use the information intelligently. This could be by applying a linear multiplication factor to convert to Jy/pixel or Jy/arcsec^2 on the fly when required, e.g. for comparison with non-radio data (it is much easier than converting magnitudes to physical units!). However results from source exctraction should ideally be in both units as radio astronomers will expect Jy/beam.
>
> Sensitivity: for Temporal I would say "exposure map"
This is hard to generalise for radio interferometry. To make a good image this is the synthesis time, that is, the time it takes for the earth to tur to provide enough baseline coverage. For a sparse or linear array this is ideally 12 hr; for the VLA in a compact configuration it can be as little as 15 mins. However if you are observing a variable source (or a source with a variable core) you can extract a light curve from the visibilities with a time resolution limited only by sensitivity, a single scan (typically 5-10 mins) in some cases, could be an hour or more. Occasionally a single integration (which corresponds to your exposure?) may be useful, but that is rare.

>
> Sample precision: for Spatial -> pixel scale,
As I've explained, if interferometry image data have been conventionally reduced, the pixel is a rough indicator of sample precision, but it isn't an immutable property of the detector. For extracted source catalogues you can get to much higher point source position precision depending on the signal-to-noise; for the fidelity of imaging faint extended sources it is the natural synthesised beam.

> for Flux -> readout noise for CCD data.
I guess it is image(etc) noise again for interferometry.

As an aside, there is a whole additional set of jargon for single dish observations, where you may need to know how to convert Tant (antenna temperature) into non-instrument-dependent units (using Tsys, efficiency and sensitivity) etc. etc.

The main lesson to me from this, is that I think we will never end up with one table which covers every domain and even if we did the words chosen would mean different things to different people, causing confusion. This excercise (which we should indeed repeat for other domains, such as your HST expertise, x-ray etc.) should just tell us if the column and row headings of the matrix are usable, and then establish a translation mechanism at the most convenient point. For example, the VO needs to know SensitivityFunction.Spatial and an interferometry data centre can provide a usable form of that function (initially a pair e.g. 50% @ 5', or even just 5'), whilst a small single-dish data provider might require the VO to calculate the simple expression lambda/diameter from the FITS header.

---
There is another confusing issue in the Characterisation table.  The Flux
entry for Bounds includes limiting flux, which I presume is the 3sigma (or
whatever) noise level.  The Flux entry for Sensitivity is linearity.  That
is perfectly internally logical.... but most astronomers are used to
thinking of the limiting flux as the sensitivity of their instrument.

I suugest renaming either or both classes:
Bounds > SensitivityBounds
Sensitivity > SensitivityFunction
- what do you think?


>
> I love the fact that now the Radio domain is represented!
> (That's a challenge, though, since I need to understand/think radio now ...)
Thanks for your comments, it is very useful to discuss this. But I am not expecting the model to be modified to cover every interferometry quirk, the main thing is to start from the tools and science cases which we will work with in the next year and identify what information is needed for those. all the best a - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Dr. Anita M. S. Richards, AVO Astronomer MERLIN/VLBI National Facility, University of Manchester, Jodrell Bank Observatory, Macclesfield, Cheshire SK11 9DL, U.K. tel +44 (0)1477 572683 (direct); 571321 (switchboard); 571618 (fax).
Received on 2004-05-08Z13:41:27