L1688 Resolution Worksheet

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Introduction

The spatial resolution of various instruments and missions is a very important thing for us to consider in the course of our work. We're using data that come from several different surveys, with different spatial resolution. This is most vividly seen by a comparison of WISE channel 1 and 2 with Spitzer IRAC channel 1 and 2 because the wavelengths are the same (and the telescopes are different), but it will matter a lot in particular for the Herschel data.

MY GOALS for you in doing this are to develop a sense of (1) what resolution means and how it changes between telescopes, e.g., WISE vs. Spitzer vs. 2MASS vs. Herschel resolution; and (2) understand what the challenges will be for us in matching across wavelengths. Ancillary goals (e.g., you can't do this worksheet without also accomplishing these): (1) get used to working with FITS files, manipulating stretches, etc.; (2) identifying objects in and measuring distances on FITS files; (3) learn how to use Finder Chart (and other IRSA tools), ds9, and Skyview as resources to be used down the road on whatever you find yourself doing next.

For a general introduction, please start with the main text already on the wiki for Resolution. Please also look at the examples lower on that page, but you don't need to actually do the one that suggests that you go download data, etc. The skills you might have gained from that specific example will be stuff that we do as part of our project.

We will be using Finder Chart at IRSA to retrieve images, but we will also use Goddard's Skyview to retrieve larger FITS images. You need a way to view and interact with FITS files (see FITS explanation below). Finder Chart (and its more generic friend IRSA Viewer) allow you to interact directly with the FITS files. You could also use DS9 which you can download here: DS9. Also, ds9 was the topic of a tutorial in NITARP tutorials.

Software basics and other things to note

Background information

If you need a refresher on mosaics, see What is a mosaic and why should I care?

If you need a refresher on angular measures on the sky, see this site from LCOGT.

A bit more information on FITS format is elsewhere on the wiki. The most important thing about FITS format vs. other image formats is that JPGs (and for that matter GIFs or PNGs) are "lossy compressed" files, which means that images in those formats actually LOSE INFORMATION, particularly in comparison to the FITS file. JPGs are just fine for images you take of your kids with digital cameras - you rarely ever see evidence of the loss of information. (As an aside - you might see evidence of it if you take a picture of something with high contrast, or a sharp edge somewhere in the image. If you look at the jpeg up close, you will see 'ringing' of the sharp edge, which looks kind of like blurring. The wikipedia page on lossy compression linked above has an example of loss of information with JPGs.)

So, what this means is: any time you are doing science, whether that is using your eye to see small details in the image, or measuring distances, or doing photometry, you always want to be using the FITS file, never a JPG, PNG, or GIF.

When you download the FITS files (from anywhere), the default filename is very likely related to the process id on the server, e.g., it won't mean anything to you 10 minutes after you download it. In the process of downloading images, you should rename the images straightaway to be something that you can understand and remember later on.

We will largely be using Finder Chart, ds9 and Goddard's Skyview. Detailed documentation for all of these is available at their respective websites. I've made videos for Finder Chart and ds9 too (some aimed at NITARP participants, some at the professional astronomy community).

Skyview

For Skyview, we will use the full Query form, not Quick View and not Non-Astronomer's page.

Skyview pulls together some huge number of surveys in one place and makes them accessible to you in an easy, fast interface. It will resample and regrid and remosaic all sorts of surveys for you, from gamma rays to the radio. (That is, as we will see, both a strength and a weakness.) I don't know exactly if it conserves flux (e.g., if one can still do photometry off of the mosaics it provides); I would err on the side of caution and NOT use this for anything other than morphology, e.g., do science by eye with the mosaics, and you can use them for distance measurements on the images, but don't do photometry on these mosaics.

Skyview will always spawn the same second window for the results. The first time you call it, it will spawn a second browser tab or window (depending on your local configuration), and then, if you don't close that second tab or window explicitly, the next search results will go into that same window, even if it's hidden below where you are currently working. It will make it seem as if nothing has happened when you submit your search request.

In Skyview, you can ask for more than one survey at the same time, but it uses the same 'common options' you specify on the query page. To select more than one survey that are not adjacent in the list, hold down the command key while clicking. (That is, at least, on a mac. Your mileage may vary.)

Skyview will allow you to download both the JPG and the FITS file (click on "FITS" to download it). You want FITS, as per above. :)

If, in the future, you need to find Skyview, you will probably need to google "Goddard Skyview" as there is at least one other software package called Skyview (including one at IPAC that is mentioned more than once here in this wiki) that does something else entirely.

FITS Viewers: ds9

You need software capable of reading FITS files. There is some information on using a variety of packages here.

As our first but certainly not last example of "astronomers using whatever software you are most familiar with to do the job", you are more than welcome to use your own favorite FITS viewer (if yours has an easy way to measure distances).

You might as well start to get comfortable with using ds9. It's free, and available for just about any platform. There are at least 2 tutorials on using ds9 developed by NITARP students on the wiki for doing some specific things - search in the wiki on ds9 - and more from the rest of the web, including some listed at the bottom of this page. Also, ds9 was the topic of a tutorial in NITARP tutorials.

When clicking around on ds9 images, you may occasionally leave behind a green circle; this is a "region", and they are ultimately very helpful, but when learning things, they can be very annoying. To make accidental regions go away, pick the region, and hit backspace or delete on your keyboard or from the top regions menu.

For this worksheet, you need to be able to measure distances. Measuring distances in ds9 is basically creating a special 'region' that is a ruler, so you may find it clunky. From the menus on the top, select Region/Shape/Ruler. Click on one end of what you want to measure, then move to the other end and click again (or click-and-drag; you may need to experiment to see what your system wants). A line with arrows will be drawn connecting the two, along with the distance in text and dotted lines completing the triangle. By default, the distance will be in physical units (pixels of the image you are viewing), but by accessing the region's Get Information panel (top menu: Region/Get information; buttons in the middle of the ds9 screen: Region/Information), you can change both the endpoints and (more usefully) distance units to WCS so that the units will be in degrees, or minutes, or seconds.

In recent years, we have had some skittishness from Windows machines when running ds9. It may very well be that you will have an easier time using IRSA tools (see next) than ds9, although ds9 is (for the moment) ultimately more powerful.

ds9 Tutorials from Babar from 2012:

ds9 Tutorials from the official NITARP tutorial (Jan 2013):

Tutorial from Milton Johnson from 2016:

FITS Viewers: Finder Chart and IRSA Viewer

Finder Chart and IRSA Viewer both use software that is called "Firefly", and both tools have a similar look-and-feel. Finder Chart was originally designed to create finder charts for use at a telescope, but it has evolved into one of IRSA's most popular tools. It provides images from several surveys (and several bands), and allows simultaneous searches of the corresponding catalogs. IRSA Viewer is a more generic version of Finder Chart, providing the FITS viewer and one-by-one image retrieval and catalog searches.

In both cases, the search capability is integrated with the FITS viewer capability. (In Skyview, these capabilities are not integrated.) When Finder Chart or IRSA Viewer give you images as a result of a search, you are looking at (and interacting with) the original FITS files. There is a toolbox on the top of both tools that can be used with the images. You can change color stretches and color tables, you can leave markers on the image, you can read in catalogs (and ds9 regions files), etc. In Finder Chart, by default, all the images are locked together, so what you do to one image (zoom, etc.), happens to all of them. (To unlock them, click on the lock icon in the image toolbox.) (Just for completeness, in IRSA Viewer, there is no a priori guarantee that the images that are loaded are of the same patch of sky, so they are by default NOT locked.)

You can also measure distances in Finder Chart (or IRSA Viewer). For this Resolution worksheet, you need to be able to measure distances. Click on the ruler icon, then click and drag in the image to measure a distance. Click on the layers icon to bring up a pop-up that specifies the units for the length of the vector you have drawn in degrees, arcminutes, or arcseconds.

Images retrieved via Finder Chart or IRSA Viewer are coming from the original archives corresponding to each survey, so they are basically guaranteed to be unresampled images, so they are OK for doing detailed science, including photometry. There is an excruciatingly simple way of guesstimating photometry within Finder Chart or IRSA Viewer, but it's nowhere near accurate enough for scientific analysis.

Finder Chart and IRSA Viewer also let you retrieve and overlay catalogs. Skyview doesn't let you do that at all. On the other hand, Finder Chart and IRSA Viewer are limited to the tiles currently publicly stored here at IRSA; most of the time, you won't notice the tiles, but the 2MASS tiles are crazy small (that's a technical term) so if you ask for any reasonable amount of sky at all, you'll get a tiny 2MASS image surrounded by black, blank sky. In order to get big 2MASS images, you need to get them some other way, like from Skyview.

Click on "download" to get the FITS (or the pngs, or a pdf, or the html for that matter).

The IRSA YouTube Feed has playlists on both Finder Chart and IRSA Viewer.

Notes on Distances

You can also measure distances by hand by comparing pixel coordinates. Note that as you move your mouse around on the image in any of these FITS viewers, it will give you an updated readout of the ra and dec near the top. You can change this from hh:mm:ss ddd:mm:ss format to decimal degrees for both ra and dec -- for ds9, you do this by picking from the "wcs" menu at the top, either 'degrees' or 'sexagesimal'. Make a note of the RA/Dec from which you want to measure a distance, and the RA/Dec of the end point of the distance measure.

No matter how, exactly, you do this, WATCH YOUR UNITS. RA by default is in hours, not degrees. Dec by default IS in degrees. How do you convert between hours and degrees? (Hint: there are 24 hours of RA ...and 360 degrees.)

Technically, to be absolutely correct, because you are calculating distances on a sphere, in order to do this, you need to do spherical trigonometry. This matters because the angle subtended by 1 hour of RA on the celestial equator is much larger than that subtended by 1 hour of RA near the celestial pole. For quick and dirty purposes, it should be mostly fine to simply subtract the RA and Dec to get a reasonable estimate of the distance BUT WATCH YOUR UNITS because RA by default is in hours:min of time:sec of time, not deg:arcmin:arcsec.

The spherical trig does make a difference, though. See this excerpt from someone's class notes with some really nice graphics and explanations of why you need to do this, and how to do it right. (hint: For the distances we'll consider here, you need a cosine of the declination. I won't make you do the full spherical trig in most cases.) For the ambitious, anticipating skills you'll need downstream from this worksheet, try programming a spreadsheet to do this for you, given two RA,Dec position pairs. NB: Be sure to watch your units on the Dec-- some cosine functions want radians, and some take degrees. (Bonus: how much of a difference in L1688 does it make if you leave out the cos(dec) term? Is that going to get worse or better if we move closer to the north celestial pole?)

Part 1: What size region should we study?

One of the big things we need to do is figure out how big of a region we want to take on. Towards that end, we need relatively big images of our region so that we can sensibly weed down. The field center corresponding to what I've collected in the context of the YSOVAR work is 16:27:10 -24:37:30.

The point of this exercise is to narrow down our region. The skills you're going to need here include: finding data, loading and viewing FITS images, aligning the images so that they all cover the same region of the sky, overlaying regions, changing the color stretch and maybe the color table.

The reason I want you to pull the data from IRSA directly and not just grab the copies of my Box drive is so that you know how to find data after your work on this team is done.

Finder Chart: DSS, 2MASS, WISE, SEIP, AKARI, IRAS...

Finder Chart gives you images from POSS, 2MASS, WISE, Spitzer (SEIP), AKARI, and IRAS in native pixel resolution (e.g., the pixels are the original ones from the data product from that survey). But it is limited by the size of the tiles provided by the corresponding survey.

Go to Finder Chart and ask it for images that are at least half a degree on a side.

Q1.1 : For the images that it returns, what is the size of each pixel for each survey? (Option #1 to do this: Make the image big enough in your view of it that you can see pixels, and measure the size of it. Option #2 to do this: look in the FITS header.) Try at least one image from each of the surveys. Most of these surveys were electronic from the start; however, the original POSS was photographs, so the spatial resolution was set by the seeing at Palomar that night, AND the size of the silver grains on the photographic emulsion. When the plates got scanned, during the digitization process, this got mapped into the pixels you see in the images.

Q1.2 : You will need to Google for this one. What is the original native pixel size for these surveys? Finder Chart gives you images that come straight from the original surveys, so they should match the original native pixel size for each survey.

Q1.3 : Are there any images you've retrieved that have "run off the edge" of a stored tile. (Hint: yes.) Which ones?

Skyview

For the surveys where you have run off the tile rather dramatically (at least 2MASS), you can use Skyview to get a larger image. The four most important parameter choices Skyview gives you are:

  • center position
  • survey (wavelength)
  • image size in pixels
  • image size in degrees

Skyview will happily and without complaint or warning resample and regrid the pixels to whatever scale you want. What do you need to do to get 'native pixel' resolution out of Skyview? You should have the information from earlier questions to figure out how many pixels you need to cover at least 0.5 deg on a side, centered on 16:27:10 -24:37:30, so go and do the math, and ask Skyview to give you a full-sized image of your desired size. Note that you can request more than one survey at a time, but Skyview will use the same parameters for each of them.

Q1.4 : Did you do the calculations right? Here's how to check. Look at the sources in the 2MASS image you retrieved from Finder Chart (which you know is native px size) and compare it to the sources in the image you retrieved from Skyview. Have you lost information? (Try to make it lose information deliberately by asking for much larger pixels.) We'll work more with individual sources later in this page.

Q1.5 : Skyview attempts to knit tiles together, but sometimes you can see the original tile boundaries, and it looks like a patchwork quilt. Do you see this here?

Spitzer and Cores-to-Disks

Skyview won't give you Spitzer images, because Spitzer isn't an all-sky survey. But there are lots of large images available at IRSA from Spitzer. SEIP = Spitzer Enhanced Imaging Products, but this too works in tiles, and the request you give Finder Chart runs off the edges of some of those tiles. There are data there, just not in the tile that Finder Chart is pulling for you here.

Spitzer was the first NASA mission (or observatory of any sort) to specifically solicit large, coherent projects before launch. The reason for this was that, if something catastrophic happened and Spitzer broke quickly, by conducting these large, coherent investigations right out of the gate, then at least we'd have all these large, coherent data sets. Spitzer has been working for more than 3 times its nominal lifetime now, so that's not a concern. However, part of the deal with these early teams was that these teams would deliver products back to IRSA for distribution. Through this, we have changed the astronomy culture, and many people after that very first cycle have delivered products back to IRSA for distribution. Cores-to-disks (c2d, definitely *not* C2D) was one of those very first teams. They set out to make large maps of several famous star forming regions ... including L1688. Their delivered products are curated here at IRSA. They delivered maps of large regions as well as specific cores. You can go and get their data (stuff they delivered back to us, both images and catalogs). For this exercise, you want images of *cloud* (big maps) (as opposed to cores) and things marked "Oph" (for rho Ophiuchus, another name for this big SFR).

Q1.6 : Figure out how to get images. You can load them directly into IRSA Viewer from these pages. Some of the images will be very large, because they cover essentially all of the rho Ophiuchus region; if you load from this page into IRSA Viewer, you'll be using only Caltech's network, not your school's... You will need IRAC-1, IRAC-2, IRAC-3, IRAC-4 (all the ones tagged "comb" for combination), and MIPS-1 (MIPS 24). MIPS-2 is 70 microns and MIPS-3 is 160 microns, both of which are done better with Herschel/PACS. (You can get them for comparison if you want!) The full-size mosaics are there for all four IRAC bands, but I think the MIPS-24 is broken into two pieces. Which one has our target at 16:27:10 -24:37:30?

I've put copies of my images on the Box drive, if you need them.

Initial assessment

Load the images into your FITS viewer of choice. Find 16:27:10 -24:37:30 on either the MIPS-24 or PACS-70 images. You may need to fuss with the image stretch to be able to see sources near our region.

Q1.7 : How big of a region do you think you want to study, based just on the images?

Regions

Both ds9 and the IRSA tools allow you to overlay things. IRSA tools prefer IPAC table files (*.tbl files), but will accept regions files (*.reg); ds9 prefers region files and doesn't know what to do with tbl files.

I've made for you the following region files (which the wiki refuses to upload properly, so look for them on the Box drive):

  • circle that is 20 arcmin in radius
  • square that is 20 arcmin on a side
  • the regions covered by the YSOVAR monitoring data
  • the sources studied by Ribas (including the Herschel data)
  • the sources that the Herschel software pipeline identified in the PACS-70 and PACS-160 data

Overlay these regions on the images you have loaded into whatever tool you're using.

Q1.8 : We need to make sure we have at least some sources that Ribas didn't discuss, but we don't want to get stuck with a ton of sources that might not really be there in the PACS images. How big of a region do you think you want to study, now informed by the regions you've loaded in?

Part 2: Point Sources

The point of this exercise is to really, really start to look at the individual sources in our region. The skills you're going to need here include: loading/viewing/manipulating FITS images, overlaying catalogs, aligning the images so that they all cover the same region of the sky, and maybe measuring distances. Also: moving back and forth between tools to find the capability you need.

Calibrating your expectations for point sources: what sizes do we expect?

Googling to get what you need is ok!

Let's start by calibrating our expectations by thinking about the sizes of things in arcseconds (or arcminutes or degrees) with which we are more familiar before launching into measuring things on the FITS images.

  • Q2.1: What approximate angular size is the Moon?
  • Q2.2: What approximate angular size is Jupiter?
  • Q2.3: What approximate angular size is Proxima Centauri? It is a M5.5 Ve, and so its radius is about 0.15 Rsun. Its parallax is 774.25 milliarcsec.
  • Q2.4: Put our Sun, with a Kuiper Belt, at the distance of Proxima Centauri. What angular size would the Sun be? The Kuiper Belt? In reality, the circumstellar disk surface brightness is much, much fainter than the central star, but for purposes of this example, let's ignore that. Take the solar radius as 7e5 km and the KB as 6e9 km.
  • Q2.5: The disk around beta Pictoris is about 1650 AU in radius. (Beta Pic's parallax is 51.44 mas.) What angular size would that be? (Again, though, the brightnesses are so different, in order to see the disk at all, you have to block out the brightness of the central star and integrate for a long time.)
  • Q2.6: L1688 is about 120 pc away. Put a star/disk system just like Beta Pictoris in L1688. What size would it be, ignoring issues of surface brightness and contrast with the star?

THE POINT OF DOING THIS PART: will we see any disks or rings around our stars using our data? You may need the resolution information from the below to answer this. :) Having gotten the answer to this, you will be met with a Paddington Bear-style "hard stare" if I hear you telling anyone that the "rings" in the MIPS-24 data are rings of dust around those stars.

Point sources in our non-Herschel data

Normally, to 'believe' a detection of anything, astronomers require that it be seen in more than 1 pixel. If something is seen in just 1 pixel, it's hard to tell if it's a single hot pixel, or a cosmic ray, or a real detection. Thus, spatial resolution, if cited without a "per pixel", is most frequently quoted as certainly more than 1 pixel, often ~2 pixels. What this physically means, in essence, is BOTH the following two questions: (1) "How many pixels have to be affected before I believe it is a real detection?" and (2) "How close do two sources have to be before I can no longer distinguish them as two individual sources?" Real life numbers: the quoted resolution of IRAC is ~2 arcsec, but the native pixel size is 1.2 arcsec, and mosaics often have the pixels resampled to be 0.6 arcsec. The quoted resolution of the DSS is 1.7 arcsec per pixel (or about 2 arcsec, depending on the photographic plate).

  • Q2.7: For at least one frame from each of a few of the surveys we picked, from either your Finder Chart or Skyview images (assuming you are confident you have native pixel resolution), go and measure the sizes of 3 to 5 'typical' isolated point sources in these images. What kinds of sizes are you getting for each survey? (It is going to be hard to find 'typical' in IRAS; do what you can.) Changing the color table is useful for telling if the image is slightly asymmetric (implying a barely resolved companion) or saturated or other things.

These numbers are what people mean when they quote the 'resolution of a survey'.

  • Q2.8: Pulling out to the big picture again, why is it that IRAS sources are given as, e.g., "IRAS 23038+6215" and 2MASS sources are given as, e.g., "2MASS 23053628+6232466" ?

Point sources in our Herschel data

For our project, we will need Herschel data. The Herschel tiles are LARGE and our object is not necessarily in the middle of them. The easiest way in general to access the Herschel images is via HHLI, the Herschel High Level Images. Go and pull the PACS and SPIRE data for our region; note that you can find several tiles this way, and not all of them have the most data on our region. If you don't have enough memory on your computer to display them (or enough network bandwidth to easily download them), get my versions off the Box drive.

  • Q2.9 : What are the sizes of the pixels in the images? What is the resolution of the images?

For Reference: Tools for comparing resolution of various surveys

1. create a three-color image using bands of your choice. Finder Chart used to let you do this, but that's not possible in the current public version; IRSA Viewer is the best way do this using IRSA tools; on the main screen where you search for objects, you have a 3-color option, including loading from disk (as opposed to, say, IRSA holdings). However, IIRC, the final resolution of the 3-color image is set by whatever you load into the red plane, so even though your lowest spatial resolution observations are probably also the reddest, don't load them into the red plane. ds9 also allows you to make 3-color images. For ds9, you need to tell it, "Ok, I want to make a 3-color image now" (Frame/rgb) and then you can load in each plane separately (in the pop-up, pick the color plane, then do File/open. Change the color plane and go back to file/open, etc.). Whichever image has the lowest spatial resolution should be superduper obvious, because, say, the sources will appear to have blue blobby rings if you load the lowest resolution image into the blue plane.

2. blink images. You can flip through images by hand in any of these tools; ds9 will do it for you if you want. For ds9, do file/open and find the first image; do frame/new then file/open and load the second image, etc. If you used the command line trick (ds9 *.fits), you will load all the images into individual tiles, in alphabetical order (which is most likely not wavelength order!). If you did them one-by-one, you will have them virtually in a stack, in the order you loaded them. To see all of them at once, click on 'frame' then 'tile.' To get it back to one at a time (in a virtual stack), pick 'single.' To line them up on the sky, pick from the top "frame" menu/match/frame/wcs to match them in terms of area on the sky. (That command means, "align all the images I have loaded in ds9 to be North up, all on the same spatial scale as the image I have selected when I initiate this command." WCS stands for world coordinate system, meaning that there is information about the ra, dec, and mapping of pixels to ra and dec in the FITS header.) To scroll through the whole stack, pick 'next' or 'previous', or go ahead and blink them. You can configure the length of time spent on each frame. You can change the ordering - explore the menu options on the top "Frame" menu. In the 'single' frame case, the image you are looking at is the active one; in the 'tile' view, the one with the blue outline is the active one. Click on the tile to make it the active one. The commands are similar in the IRSA tools; there is a "match WCS" tickbox and you can view images one at a time or tiled in the tool.

Note that most of the work we can do using Finder Chart uses wavelengths shorter than Herschel, because it is linked to these shorter wavelengths. For our work, we will be more focused on the longer wavelengths, and consequently less able to just use Finder Chart by itself, for example.


Specific sources in our region

We're going to end up spending rather a lot of our time chasing details of individual sources across all of the bands we have. Indeed, this is going to be the heart of our work. Let's get started on this process with a few illustrative sources.

I've created a region file for you with three positions (indsrcs.reg). For these two:

  • 16:27:11.739,-24:38:32.19
  • 16:27:09.430,-24:37:19.71

Call them up in whatever FITS viewer works for you. Decide what size images you need, or how much you need to zoom. Are these sources present in all available bands in J band and longer? If not, which bands have this source? You will need to change the color stretch, at least. Are any bands saturated? Bonus: find the name of any counterparts in particular for Spitzer SEIP, but also any other bands in which you can find the counterpart. Double-bonus: how far offset from this position are these counterparts?

For this location:

  • 16:27:28.061,-24:39:30.92

How many sources are there? Are these sources present in all available bands in J band and longer? If not, which bands have this source? Are any saturated? Bonus: find the name of the Spitzer components (HARD) and any Herschel counterparts. Double-bonus: how far offset from this position are these counterparts?

Pulling it all together

Recall that THE POINT of doing this is to start to develop a sense of (1) what resolution these various telescopes have (and how to get reliable images out of these tools); and (2) why this matters for our multi-wavelength catalog merging. Is this starting to make more sense?

Questions to be sure you know the answer to (for reference, I guess these are Q3.x):

  1. How can you get access to data using Skyview? Using Finder Chart? When would you use one vs. the other?
  2. Just because you have resampled an image to really tiny pixels, does it add information to the image? (Will you laugh at CSI and Law & Order and their compatriots when they wave a magic wand over an image? "Computer, ENHANCE!")
  3. Will we see disks or rings in our data?
  4. How does the spatial resolution compare among 2MASS, WISE, Spitzer/IRAC, Spitzer/MIPS, Herschel/PACS, Herschel/SPIRE?
  5. Is is possible that the sources seen as individual with Herschel will break into pieces when viewed with IRAC?
  6. Is there any guarantee that a single source seen with Herschel is really a single object?


Postscript on the resolution issues: Slight improvements are sometimes possible

By this point, I've hammered into you things about the native resolution from these various surveys. You should have a gut-level understanding now that you can't get more information out of the image than was recorded by it in the first place.

However.

I have swept some things under the rug. IRAS data was so interesting, and it was going to be so long before astronomers got any more data in those wavelengths on that scale, that very clever people got to work on how to get even more information out of IRAS data. Imagine those big IRAS pixels scanning over a patch of warm sky. The next time the spacecraft scans that same patch of sky, the pixels are offset a little bit from where it was on the last pass, and consequently the fluxes it measures are just a little different. Same for the next scan, and the next. If you have lots of scans over the same region, each of which are at slightly different positions (that's important), you can recover a little bit of the information on a slightly higher (better) spatial resolution. This page has some general information on the specific application of this method to IRAS, called "Hi-Res", along with example pictures. It uses the Maximum Correlation Method (MCM; H.H. Aumann, J.W. Fowler and M. Melnyk, 1990, AJ, 99, 1674). It is computationally expensive (meaning it takes a while to run), and requires lots of individual tweaking and customization, so it has not been run (blindly) over the whole sky. The degree of improvement is related to the number of scans; as for WISE, the number of passes is a function of the ecliptic latitude, so just running Hi-Res doesn't get you a specific improved resolution. Hi-Res got famous in the context of IRAS. People are developing ways to run this kind of algorithm on WISE and even Spitzer data, but we're not going to try and use it, as there are no particularly user-friendly interfaces to it (at least at the level we would need), and the incremental benefit we'd gain from this probably outweighs the work it would take to get there.

Note - critical to making this process work is that the camera moves between scans to slightly different positions, and the source it is looking at is not changing in brightness. Will this process work on security camera videos?

In the context of our project, we won't need to care about any of this, but I thought I should be complete in case anyone cares! :)

Next steps

  • Assemble list of objects from Herschel and Spitzer. Make sure that we have matched them appropriately across wavelengths in the catalog.
  • For each of these sources, take notes on which look like point sources and which may be breaking into pieces in the higher-resolution (shorter-wavelength) images.
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