SkyView Blog

For some while we have been looking at how to put the data from the Wilkinson Microwave Anistropy Probe (WMAP) into SkyView. The WMAP data are central to our current understanding of cosmology. However WMAP images are generally stored in a the HEALPix format. HEALPix is a recursive projection where each pixel has equal area, and pixels are arranged in rings of constant latitude. This is illustratedin the image below

Pixels are successively refined with each pixel dividing into four subpixels. The pixels are normally stored as a linear array of pixels using one of two standard orders — not as an image.

Since HEALPix didn’t seem to be a normal projection, we’d held off supporting it. The original Gorski paper does suggest that you can represent the HEALPix data in a projection plane. However the HEALPix pixels are diamonds, not rectangles — and that doesn’t fit in with how we store images.

Recently we realized that by thinking just slightly outside the box, we can get around this and treat HEALPix as a standard projection. Although the HEALPix pixels normally look like:

in the plane where the equator runs horizontally, we’re not restricted to that. If we use a projection plane rotated by 45 degrees then those same HEALPix pixels look like

In this frame the pixels are perfectly normal, so SkyView can treat HEALPix just like any other projection. SkyView doesn’t care that the equator isn’t horizontal!

In practice we still do some special handling of the HEALPix data. To use our existing code we would have to reformat HEALPix-formatted FITS files as more standard images in the rotated HEALPix frame. Instead we choose to use the original format and use a new HealPixImage class. This makes a HEALPix file look like a regular image to the rest of SkyView. We’re in the process of testing the WMAP data and the HEALPix projection but they should be showing up in the released version of SkyView shortly.

[Added:] A paper by Mark Calabretta and B.F. Roukema discusses this in much more detail and in a more general context of HEALPix like projections. I’ve read this paper in the past, so it’s not unlikely that it’s ultimately where the I got the idea as well.

This image from 2008-12-10 09:39:28 is pretty interesting…

It looks like we are seeing some very special object with rings around it. What’s going on here?

This is a COMPTEL image, one of the lowest resolution surveys we have in SkyView. It’s taken in the hard X-ray/Soft gamma ray regime where it’s very difficult to build an imaging detector at all. The method used requires a complex deconvolution and yields at best a resolution of a few degrees. So the pixels are very large and the image would - absent distortions - cover almost the entire sky. However, you can’t project such a large region of the sky onto a single plane image without very large distortions. In fact the default projection that SkyView uses, the Tangent plane or Gnomonic projection, only shows half the sky no matter how big we make our image. The great circle 90 degrees from the center of the field of view is off at infinity. It’s rather like the way Mercator maps get enormously distorted as you near the poles — and even so you can never quite get there.

The middle of the image is reasonable enough, but as we approach the edges pixels are being stretched out in a radially symmetric pattern.

Another projection can show the whole sky in a more understandable fashion. One might try an Aitoff or Cartesian projection if you know that you want to see the entire sky. However if you want to make sure that a given point is at the center of the map, then something like the ZEA (for Zenithal Equal Area) projection might be nice. Here we’ve redone the picture in that projection:

The entire sky is shown here with the point opposite the requested center forming an infinitesimally thin ring around the image. So it is still distorted, but in a way that doesn’t obscure the global features as much. Every pixel represents the same area in the sky. The plane of our Galaxy shows up clearly as a circle of enhanced emission and the bright spot is the Crab nebula.

The lesson here is that you need to adapt your projection to the application. Some projections, e.g., the Tangent or Sine projections just won’t do very well for large fields of view. Others, e.g., the Cartesian projection near the pole, can be a poor choice when looking at a particular small region of the sky.

This image from 2008-12-06 15:57:53

shows a very interesting feature that looks like a giant worm squirming amongst the stars. In fact it’s actually a tiny hair that got on the photographic plate sometime in the process of taking, developing or scanning the image.

How can we tell that this isn’t Nobel-Prize-winning stuff? The obvious giveaway is how thin the feature is. The stars in the image are point sources blurred by optical limits, telescope jitter, and especially seeing. Any real astronomical source can be no sharper than they. Our worm is much thinner.

Hairs and dust show up occasionally on all of the surveys scanned from optical plates.

A new version of SkyView has been installed to accommodate the issues that off center GALEX GR4 images presented. GALEX now uses a special GalexExposure Image finder. This uses knowledge of the GALEX survey to find the center of the actual field of view for every observation. Specifically it looks for the AVASPRA and AVASPDEC keywords in the header and uses the pixel location corresponding to these coordinates as the center of the field of view. The center locations in the survey description file have also been updated to use the FOV centers rather than the nominal image centers.

Lots of people are using the Image gallery. One popular theme is to find images that look very peculiar. E.g., look at the image in the gallery from 2008-11-29 19:02:44

This is a very peculiar looking field in the DSS. It looks very pixelated, but it’s a normal sized image so the pixels are much larger than the actual image pixels. There are few if any stars visible? What’s going on?

We can find out by zooming out and doing a full square degree region around the same center: 101.35626366727445,-16.713875539779025. This gives us the image we see at 2008-12-01 16:59:43 in the gallery.

The image is actually the center of a massive burnt out region in the underlying photographic plate. We’re looking at Sirius! A big (40″) telescope, extremely sensitive emulsion and long exposure don’t mix well with the brightest star in the sky. The scattered light from Sirius is still affecting the data over this entire square degree but at least at this scale we can see the cause and at the edges we can begin to pick up other objects in the field. So don’t expect to see very bright stars in most of the optical surveys. They are a billion times brighter than the objects that these surveys were intended to detect.

The underlying GALEX observations used in SkyView are 3840×3840 pixel images where only  a circle with a radius of about 2900 pixels is actually exposed.  In earlier releases the exposed region seemed to be centered with the image square but that is no longer always the case for GR4.  The observation center can now be hundreds of pixels offset from the nominal image center.

SkyView tries to mask out the non-observed reqion when it combines GALEX observations, but when the mask is off-center this masking may go awry.  We’re downloading information from MAST giving the actual centers for the observations rather than the nominal image centers and we will update the survey description file for MAST appropriately within the next few days to accommodate this, but in the meantime GR4 images may show unexpected blank patches.

CLI users of SkyView can play with the image finder setting to try to mitigate this, but this is unlikely to help in most cases.