Difference between revisions of "Working with CG4+SA101"

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−
=Downloading the data=
+
=Downloading the data <font color="red">DONE</font> =
  
 
[[Using the SHA, a concrete example]] is already tuned to this project.  There are bugs in the SHA! Let's work through this one together, as a big group.
 
[[Using the SHA, a concrete example]] is already tuned to this project.  There are bugs in the SHA! Let's work through this one together, as a big group.
Line 9: Line 9:
  
 
'''More specific shorter term goals''': Search on our targets. Understand the difference between the observations. Understand why I chose to use the observations that I did.
 
'''More specific shorter term goals''': Search on our targets. Understand the difference between the observations. Understand why I chose to use the observations that I did.
 +
 +
'''Relevant links from L1688 page''': [[Using_the_SHA,_a_concrete_example]]
  
 
'''Questions for you''':  
 
'''Questions for you''':  
Line 15: Line 17:
 
#Where is SA101 with respect to CG4? How much overlap is there in these observations?
 
#Where is SA101 with respect to CG4? How much overlap is there in these observations?
  
−
=Making the mosaics=
+
=Making the mosaics <font color="red">NEARLY DONE</font> =
  
 
In the generic case for most targets, you can probably use the online mosaics that come as PBCD (Level 2) mosaics (or, later, Level 3 delivered products, if they exist for the region you want).  In this case, we have some special circumstances: one of the observations was taken with cluster-mode targets, and there are some very bright stars here (bright at all Spitzer bands) which prompt some instrumental effects that require some special handling.
 
In the generic case for most targets, you can probably use the online mosaics that come as PBCD (Level 2) mosaics (or, later, Level 3 delivered products, if they exist for the region you want).  In this case, we have some special circumstances: one of the observations was taken with cluster-mode targets, and there are some very bright stars here (bright at all Spitzer bands) which prompt some instrumental effects that require some special handling.
Line 27: Line 29:
 
#What is image artifact and what is real sky?  What is saturated?
 
#What is image artifact and what is real sky?  What is saturated?
 
#How does the short frame differ from the long frame? Why do we do this?
 
#How does the short frame differ from the long frame? Why do we do this?
−
#Notice the pixel scale. What is the real pixel scale of IRAC (and MIPS)? What are the pixel scales of the images? Does that actually change the resolution? (for advanced folks - why did I do this?)  
+
#<font color="red">HWK</font> Notice the pixel scale. What is the real pixel scale of IRAC (and MIPS)? What are the pixel scales of the images? Does that actually change the resolution? (for advanced folks - why did I do this?)  
  
  
−
=Getting data from other wavelengths=
+
=Getting data from other wavelengths <font color="red">BASICALLY DONE</font>=
  
 
You have already made some progress on this in your literature search this Spring. (See [[Putting CG4 in Context Homework Page]]).
 
You have already made some progress on this in your literature search this Spring. (See [[Putting CG4 in Context Homework Page]]).
Line 37: Line 39:
  
 
'''More specific shorter term goals''': Go get data for SA101 and CG4 for comparison to our Spitzer data.  
 
'''More specific shorter term goals''': Go get data for SA101 and CG4 for comparison to our Spitzer data.  
 +
 +
'''Relevant links from L1688 page''': [[How can I get data from other wavelengths to compare with infrared data from Spitzer?]]
  
 
'''Questions for you''':  
 
'''Questions for you''':  
Line 42: Line 46:
 
#What wavelength did you pick and why?   
 
#What wavelength did you pick and why?   
 
#What coordinate system did you pick and why?
 
#What coordinate system did you pick and why?
−
#Get a smaller-scale image too, on the same scale as the Spitzer images.
+
#<font color="red">HWK</font> Get a smaller-scale image too, on the same scale as the Spitzer images.
−
#What band did you pick and why?  How is the resolution different? (You may need to do the next section before you can answer this.)
+
#<font color="red">HWK</font> What band did you pick and why?  How is the resolution different? (You may need to do the next section before you can answer this.)
−
#Figure out how to get a 2MASS catalog. I've done this for you, but you should be able to get this yourself too.
+
#<font color="red">HWK</font> Figure out how to get a 2MASS catalog. I've done this for you, but you should be able to get this yourself too.
  
−
=Investigating the mosaics=
+
=Investigating the mosaics <font color="red">HALF DONE</font> =
  
−
It is "real astronomy" to spend a lot of time staring at the mosaics and understanding what you are looking at. Don't dismiss this step as not "real astronomy." This is time well-spent.
+
It is "real astronomy" to spend a lot of time staring at the mosaics and understanding what you are looking at. Don't dismiss this step as not "real astronomy" just because you are not making quantitative measurements.  This is time well-spent.  Start with my mosaics, as opposed to the online mosaics.
  
 
'''Big picture goal''': Understand what is seen at each Spitzer band.
 
'''Big picture goal''': Understand what is seen at each Spitzer band.
  
 
'''More specific shorter term goals''': Recognize how the images differ between SA101 and CG4, and among the various bands.  
 
'''More specific shorter term goals''': Recognize how the images differ between SA101 and CG4, and among the various bands.  
 +
 +
'''Relevant links from L1688 page''': [[How can I make a color composite image using Spitzer and/or other data?]] and the questions on that page.
  
 
'''Questions for you''':  
 
'''Questions for you''':  
−
#Which band has more stars?
+
#How does the number of stars differ across the bands? Which band has the most stars? The fewest? (Bonus question: why?) The most nebulosity? The least? (Bonus question: why?) Are there more stars in the regions of nebulosity, or less? Why?
 +
#Do the star counts differ between SA101 and CG4? Why?
 +
#Which objects are saturated, in which bands?
 +
#<font color="red">HWK</font> How big are any of the features in the image (nebulosity, galaxy, space between objects)? (What do I mean by big?) in pixels, arcseconds, parsecs, and/or light years? (Hint: you need to know how far away the thing is. If it helps, there are 3.26 light years in a parsec.)
 +
#<font color="red">HWK</font> Make a three-color image.  What happens when you include a MIPS-24 mosaic in as one of the three colors with IRAC as the other two? Do the stars match up? Does the resolution matter? Can you tell from just a glance at the three-color mosaic which stars are bright at MIPS wavelengths?
 +
#<font color="red">HWK</font>  Which features are found across multiple wavelengths, beyond the Spitzer regime? Why?
 +
#<font color="red">HWK</font>  Obtain IRAS images from the web (via the SHA or other methods) and line them up with the Spitzer images of comparable wavelengths (e.g., 8 um with 12 um, 25 um with 24 um). How much more detail do you see with Spitzer that was missed by IRAS? Do you see more texture in the nebulosity? More point sources?  
  
 +
=Previously identified sources <font color="red">DONE</font> =
  
−
[[How can I make a color composite image using Spitzer and/or other data? | Go here]] and follow the tutorial (or use your own software) to explore the Spitzer mosaics as well as the mosaics at other wavelengths.  Think about the questions at the end of that page as they pertain to these data.
+
You've already done this. There is a table in our proposal.
  
−
Additional questions:
+
Previously Known Objects from Reipurth and Pettersson (1993) ''... fixed CG-Halpha 4''
−
#Look for image artifacts in the mosaics - they are certainly still there. What are real features of the sky and what is a feature of the instrument and/or reduction?  [http://ssc.spitzer.caltech.edu/irac/features/ IRAC artifact examples] and [http://ssc.spitzer.caltech.edu/mips/mipsinstrumenthandbook/70/#_Toc254160618 MIPS artifact examples] are online, both as part of the corresponding instrument handbook. 
+
{| border="1"
−
#If you have images that someone processed for you, how do they compare to the online mosaics produced by the pipelines?  What artifacts are better (or worse)?
+
|Star
−
#Which objects are saturated, in which bands?
+
|RA (J2000)
−
#How big are any of the features in the nebulosity? (What do I mean by big?) in pixels, arcseconds, parsecs, and/or light years? (Hint: you need to know how far away this thing is, and it's about 125 pc away. If it helps, there are 3.26 light years in a parsec.  If you're working with another object, you should look in the literature for distance estimates to it.)
+
|Dec (J2000)
−
#In this case, asteroids matter. The ecliptic latitude of L1688 is just -2.7 deg. (You can use Spot/Leopard or the SHA to convert coordinates for any other target you may be working with.)  The IRAC and MIPS maps were taken in two pieces. I gave you just one IRAC map, the combination of all frames, but I gave you 2 MIPS-24 frames, one from each epoch (separated by 3-5 hrs). Can you find the asteroids?  (personally, I'd use the blink feature in ds9, but you can use whatever you want.)
+
|V
−
#For the 70 um data, the SSC pipeline produces two sets of BCDs: filtered and unfiltered. The filtered data attempts to automatically remove some of the instrumental artifacts, but does not conserve flux for extended objects or for very bright point sources. I gave you a copy of both the filtered and unfiltered mosaics. Can you find the sidelobes around bright objects in the filtered image that are an artifact of the filtering process?
+
|(B-V)
 +
|(U-B)
 +
|Region
 +
|-
 +
|CG-Halpha 1
 +
|07 30 37.77
 +
| -47 25 07.21
 +
| >17
 +
|none
 +
|none
 +
|Sa 101
 +
|-
 +
|CG-Halpha 2
 +
|07 30 57.63
 +
| -46 56 12.50
 +
| >17
 +
|none
 +
|none
 +
|Sa 101
 +
|-
 +
|CG-Halpha 3
 +
|07 31 10.89
 +
| -47 00 33.40
 +
|14.99
 +
|1.60
 +
|0.91
 +
|Sa 101
 +
|-
 +
|CG-Halpha 4
 +
|07 31 21.92
 +
| -46 '''''57''''' 45.14 **
 +
|14.59
 +
|1.40
 +
|0.92
 +
|Sa 101
 +
|-
 +
|CG-Halpha 5
 +
|07 31 36.65
 +
| -47 00 14.13
 +
|15.25
 +
|1.26
 +
|0.23
 +
|Sa 101
 +
|-
 +
|CG-Halpha 6
 +
|07 31 37.45
 +
| -47 00 22.19
 +
|14.21
 +
|1.42
 +
|0.90
 +
|Sa 101
 +
|-
 +
|CG-Halpha 7
 +
|07 33 26.92
 +
| -46 48 43.51
 +
|13.97
 +
|1.19
 +
|0.84
 +
|CG 4
 +
|-
 +
|CG-Halpha 8
 +
|07 15 49.86
 +
| -48 31 27.16
 +
|15.33
 +
|1.39
 +
|0.13
 +
|CG 13
 +
|-
 +
|PHalpha 92
 +
|08 28 40.73
 +
| -33 46 23.17
 +
|13.38
 +
|1.27
 +
|0.91
 +
|CG 22
 +
|-
 +
|}
  
−
=Previously identified sources=
+
'''Big picture goal''': Understand what has already been studied and what hasn't in the image.
  
−
How many of these sources are 'famous' and how many are new that you have just discovered?
+
'''More specific shorter term goals''': Determine if the previously-known objects are saturated or not.
  
−
[[How can I find out what scientists already know about a particular astronomy topic or object? | Go here]] and follow the tutorial to explore the literature. ([[I'm ready to go on to the "Advanced" Literature Searching section | Move on to these examples and questions when you're ready]].)  More things to do: Find some old and some very recent papers on L1688.  For how many decades have people been studying this region?  Find some of the famous objects in your images.  Note that this is a pretty famous region, so it's doubtful that you will easily be able to construct a list of ALL the famous objects in this region in a short time, even using SIMBAD.  (If you're working on a different region, you may find many fewer papers on your region.  Your mileage may vary.)  Keep in mind too that people work in different coordinate systems.  A paper reporting on radio data may have a slightly different coordinate system than Spitzer (which is tied to 2MASS).  A paper from anything earlier than the 90s might be working in 1950 coordinates rather than 2000 coordinates, and may or may not provide high enough precision coordinates for you to easily find the corresponding object in your Spitzer images; you may need to find some archival data (POSS or 2MASS) to 'rediscover' the old object.  You will have to use your judgment to decide if any given object is really the same as the object in the Spitzer image, or if the Spitzer image didn't really detect the object, or can't resolve the object (e.g., can't distinguish it from a nearby object).
+
'''Relevant links from L1688 page''': [[How can I find out what scientists already know about a particular astronomy topic or object?]] and [[I'm ready to go on to the "Advanced" Literature Searching section]]  
  
−
=Doing photometry=
+
'''Questions for you''':
 +
#For each of the known objects, you have the RA/Dec - what are the pixel coordinates in the image? Does it change among the IRAC bands? In the MIPS band?
  
−
[[Units| Read about units before you get started....]] Then
+
=Doing photometry <font color="red">MOSTLY HWK</font>=
−
[[Photometry | read about photometry in general]], and finally read the [[I'm ready to go on to a more advanced discussion of photometry| advanced intro to photometry]]. 
 
  
−
The decision you now face is the following.  You have a mosaic with 100s to 1000s of sources, over at least 4 bands (and recall if you have HDR IRAC data, there are actually [at least] 2 frames per band, a long and a short one), so that's 8 IRAC frames, and probably you want to at least do MIPS-24 as well, for a total of 9 frames.  You need to decide if you are interested in photometry of just a few objects, in which case you might consider doing all of the photometry by hand, one object at a time, one band at a time.  On the other hand, you might be interested in having the computer automatically detect and measure the photometry of all the objects in the frame.  If this is the case, you need to tune the parameters of your photometry extraction software to the specific application you have here -- the specific band, source density, background, etc., etc.  No matter what you do, in order to check the accuracy of your photometry, you will probably end up doing this more than once on the same data set.  
+
OK, this step is doing to take the longest, be the most complex, involve the most steps and the most math.  
  
−
'''OPTION 1''': Using MOPEX to do many sources at once (not particularly recommended!): [[I'm ready to advance to a highly technical and in-depth discussion on downloading Spitzer data. | Go here]] and get the (admittedly still cryptic) doc file that is linked in partway down. Find the part on using Apex-1Frame.  Follow that for each channel (twice for HDR data!) to get the photometry.
+
Never just trust that the computer has done it right. It probably did what you asked it to do correctly, but you asked it to do the wrong thing. '''Always''' make some plots to test and see if the photometry seems correct.
  
−
'''OPTION 2A''': Using [http://spider.ipac.caltech.edu/staff/laher/apt APT] to do one source at a time: [[Aperture photometry using APT| Go here]] and work through the (somewhat skeletal) page.  If you take this option, I recommend you start with a short list of famous objects from the above step.  If you have suggestions for specific improvements for this tutorial, please let me know, or just implement them! 
+
'''Big picture goal''': Understand what photometry is, and what the steps are to accomplish it.  Understand the units of Spitzer images.  Understand how to assess if your photometry makes sense.
  
−
'''OPTION 2B''': Using APT to do a list of sources at once: Only AFTER you have thoroughly explored the parameter options in APT and thoughtfully considered what parameters to use, you can now send APT a list of targets, so you're no longer limited to doing one object at a time using APT.  I STRONGLY recommend that you try several by hand until you understand what is going on, and optimize your parameters correspondingly for the mosaic and channel and background levels you have in your specific mosaic.  
+
'''More specific shorter term goals''': Do photometry on a set of mosaics for the same sources.  Assess whether your photometry seems right.
  
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'''OPTION 3''': Using your own preferred software to do the photometry.  Be careful; read the stuff on [[Units]] first.
+
<font color="red">NEW:</font> [[CG4 photometry: more detailed instructions]]
  
−
'''IN ANY CASE''': Never just trust that the computer has done it right. It probably did what you asked it to do correctly, but you asked it to do the wrong thing. '''Always''' make some plots to test and see if the photometry seems correct.
+
'''Relevant links from L1688 page''': [[Units]] and [[Photometry]] and [[I'm ready to go on to a more advanced discussion of photometry]] and [[Aperture photometry using APT]]
  
−
RESULTS: Reduced (and bandmerged) photometry is included in the tarball above if you wish to short-cut this process, and I promise I won't think any less of you.  NOTE THAT this represents several days/weeks of a professional astronomer's time to do this photometry. You should not expect to be able to reproduce this effort in a few hours, and it is NOT CHEATING to just take my photometry, or that delivered by a Legacy team to IRSA.
 
  
−
For the data I gave you, I actually cropped the image and the catalog out of a MUCH MUCH MUCH larger mosaic and catalog.  The cropping of the image had to be done in pixel space, so north is not necessarily up, and the cropping is not necessarily strictly in RA/Dec. The cropping in the catalog is strictly RA/Dec.  This means that there will be wedges of images without sources. Sorry! If you really want those data, let me know, or go get the data yourself from the c2d delivery on the Legacy pages.
+
'''Questions for you''':
 +
#Use APT to explore the various parameters. What is a curve of growth?
 +
#What are the best parameters to use? (RTFM to find what the instrument teams recommend.)  What are the implications of those choices? What happens if you use other choices?
 +
#We should decide as a group which set of sources to measure, and have everyone measure the same sources. We will then compare all of our measurements among the whole group.
 +
#Compare the MOPEX source identifications I did from just one band with their corresponding image. Is it getting fooled by detector artifacts? ''you will need skyview for this, because you have the tbl files, as opposed to region files. Let me know if you want the reg files and I'll make you some.''
 +
#Compare the MOPEX source identifications from, say, IRAC band 3 with the image from IRAC band 1, or the source extractions from MIPS-24 with image from IRAC band 1. Are there a lot of stars (or other objects) in common? How does the nebulosity affect it? ''you will need skyview for this, because you have the tbl files, as opposed to region files. Let me know if you want the reg files and I'll make you some.''
 +
#Why did this happen? (see below)
  
−
Questions:
+
[[image:cg424.png]]
−
#If you are doing automatic source detection, compare the source extractions from any one band with its corresponding mosaic. Is it getting fooled by detector artifacts?
 
−
#If you are doing automatic source detection, overlay the source extractions from, say, IRAC band 3 with the image from IRAC band 1, or the source extractions from MIPS-24 with image from IRAC band 1. Are there a lot of stars (or other objects) in common? How does the nebulosity compare?
 
  
−
=Bandmerging the photometry=
+
=Bandmerging the photometry <font color="red">HWK</font>=
  
−
Now that you have a measurement of the brightness of each object in each frame, you need to match the same object across multiple bands, called "bandmerging."  Maybe, if you used APT, you kept track of that manually. If you did the photometry automatically, you need to have the computer match the sources.  If you did it automatically, some of the sources you extracted might not even be real - this is a common problem, and you will have to tune the source extraction... or get rid of the false sources in the bandmerging step, since the false sources will generally not have counterparts at other bands.  Of course, some of the most interesting real sources also can be single-band detections...
+
I use my own code to do this; there is no pre-existing package to do this.  If you do it by hand (or semi-by-hand) using APT, you can manually merge the photometry. My merged photometry includes J through M24.
  
−
There is no GUI tool to bandmerge the photometry.
+
'''Big picture goal''': Understand what this process is.
  
−
The code I use is written in IDL (expensive to have a site license, even for academics), and for each band, starting with 2MASS JHK, looks for matches within 1 arcsecond in IRAC-1, then IRAC-2, then IRAC-3, then IRAC-4, and then within 2 arcseconds in MIPS-1, and then within 10 arcseconds in MIPS-2.  (Bonus questions: Why should I start with the 2MASS data and work up in wavelength? Why should this matching distance change?)
+
'''More specific shorter term goals''': Do this by hand.
  
−
RESULTS: Bandmerged photometry (including 2MASS data!) is included in the tarball above if you wish to short-cut this process, and I promise I won't think any less of you.
+
'''Relevant links from L1688 page''': [[Resolution]]
  
−
Questions:
+
'''Questions for you''':
 
#Make sure that I've merged the right sources across several bands by spotchecking a few of them. (Find an object that the catalog says is detected in at least 3 bands and then overlay the images in a 3-color image or Spot to see if there is really a source there, at exactly that spot, in all bands, or if it's a cluster of objects, or different objects getting bright at different bands.
 
#Make sure that I've merged the right sources across several bands by spotchecking a few of them. (Find an object that the catalog says is detected in at least 3 bands and then overlay the images in a 3-color image or Spot to see if there is really a source there, at exactly that spot, in all bands, or if it's a cluster of objects, or different objects getting bright at different bands.
 +
#Have I 'lost' the instrumental artifacts you noticed in the previous section? Or are there instrumental artifacts or otherwise false sources sill in the list?
 +
#Does resolution matter?  (Can you find a place where more than one IRAC source can be matched to the same MIPS source?)
  
−
=Working with the data tables=
 
  
−
I've provided the data tables in something called "IPAC table format" in the tarball above.  There is a long version with many columns, and a short version with many fewer columns.  Spot, Leopard, and IPAC's [http://www.ipac.caltech.edu/Skyview/ Skyview] all understand IPAC table format.  You can also import the file into Excel to play with it there.  NOTE THAT there are a LOT of sources in this relatively small mosaic.  You will want the computer to do as much work for you as possible - you don't want to be counting sources manually.
+
=Working with the data tables <font color="red">PARTIALLY HWK</font>=
  
−
You can use Spot, Leopard, or IPAC's Skyview to overplot the sources onto an image of your choice. NOTE AGAIN THAT there are a LOT of sources in this relatively small mosaic. Skyview (and maybe Spot/Leopard) don't understand the full table, with all those columns; that's why I provided the "catshort" version with just positions.
+
'''Big picture goal''': Understand how to work with the tables. Understand how to convert magnitudes back and forth to flux densities.  
  
−
Import the data table into Excel, as that's probably the easiest way for you to work with it. (DO I NEED TO WRITE A TUTORIAL ON THIS?)  There should even be a (contrived) way to get Excel to cough back up a file that is close enough to IPAC table format that you can manually edit it to be compatible - you might wish to do this for example, if you want to take just the IRAC-4 detections and overlay them on an IRAC-1 image. (see questions in 'photometry' above.)
+
'''More specific shorter term goals''': Import the table into excel. Program a spreadsheet to convert between mags and flux densities.
  
−
==A few words on working with IPAC's skyview==
+
'''Relevant links from L1688 page''': [[Units]] and [http://www.ipac.caltech.edu/Skyview/ Skyview] but lots of important words actually on the [http://coolwiki.ipac.caltech.edu/index.php/Working_with_L1688#Working_with_the_data_tables L1688 page itself], sorry.
−
(skyview is also free and available for a variety of platforms. There is a manual too.) Get into Skyview and "paint" ("pa") the image into a window. Use the left mouse button to pull up a "zoom window" in the upper left. Click the right button to zoom in and the left button to zoom out. Click the middle button to reposition the view. Read in the table and mark every source with a red circle of diameter 6 px. Use the "gpi" ("graphics pick") feature to click on individual sources and have the parameters from the tbl file printed in the terminal window. (Left button to select source, right button to quit out of it.) Use "er" to erase window.
 
  
−
      unix% skyview
+
'''Questions for you''':
−
      skyview version 02/28/00  (R3.4)
+
#How many stars are detected in each band? Is this about what you expected based on your answer to the questions in the mosaic section above? HINT: you can do this using Excel, you don't need to count these manually!! Ask if you need a further hint on exactly how to do this.
−
        Copyright (C) 1992, California Institute of Technology.
+
#Which stars ''in the catalog'' are the stars identified in the literature?
−
        U.S. Government Sponsorship under NASA Contract NAS7-918 is acknowledged.
+
#<font color="red">DONE</font> Make sure you understand how I got the magnitudes from the fluxes (or the fluxes from the magnitudes). You will need magnitudes for the next step, and fluxes for the step after that.
−
      > pa mosaic3.6long.fits
 
−
        reading file . . done
 
−
        scanning for max min . . done
 
−
        building histogram . . done
 
−
        redoing histogram . . done
 
−
        stretching from -2.190281e+00 to 2.686462e+00
 
−
      > zoom_pan
 
−
      Centered on RA = 5h07m35.69s  Dec = -6d20m44.4s
 
−
      > table extract3.6long.tbl mark $RA $Dec red circle 6
 
−
      > gpi
 
−
      mark came from line 145 of file [...]
 
−
      > er
 
  
−
==Questions and things to try==
+
=Making color-color and color-magnitude plots <font color="red">HWK</font>=
−
The final catalog should include only real detections, dropping false detections that are due to cosmic rays or other instrumental effects. (If you are constructing your own catalog, you will probably want to drop objects seen in just one band.)  
+
 
−
#How many stars are detected in each band? Is this about what you expected based on your answer to the questions in the mosaic section above? HINT: you can do this using Excel, you don't need to count these manually!! Ask if you need a further hint on exactly how to do this.
+
'''Big picture goal''': Understand what plots to make. Understand the basic idea of using them to pick out certain objects.
−
# Which stars ''in the catalog'' are the stars identified in the literature?
+
 
−
# [[Units | Read about Spitzer units]] and then make sure that you understand the difference between flux and magnitudes.  Check my unit conversion - or do the unit conversion yourself if you are working on your own. Make sure you understand how I got the magnitudes from the fluxes (or the fluxes from the magnitudes).  You will need magnitudes for the next step, and fluxes for the step after that.
+
'''More specific shorter term goals''': Make some plots. Understand the basic approach of Gutermuth et al. (see [[media:gutermuth-appa.pdf| Gutermuth et al. 2009, Appendix A]] -- this was handed out to you in hard copy in June)
 +
 
 +
'''Relevant links from L1688 page''': [[Color-Magnitude and Color-Color plots]] and [[Finding cluster members]] and [[Color-color plot ideas]]
 +
 
 +
'''Questions for you''':
 +
#Pick a diagnostic color-color or color-magnitude plot to make. Does my photometry seem ok?
 +
#Pick at least one color-color or color-magnitude plot to make. Figure out a way to ignore the -9 (no data) flags. Where are the plain stars?  Where are the IR excess objects?
 +
#Where are the famous objects in the plot? Where are the new YSO candidates I used the Gutermuth method to find?
 +
#Make a new column in your Excel spreadsheet with some colors.  Is there a way you can get Excel to tell you automatically which objects have an IR excess? Can you implement the Gutermuth selection? (You may not be able to do so.)
 +
#Make the plots that go into the Gutermuth selection, including the relevant lines on the plot.
 +
#Of the objects I have that fit the Gutermuth criteria, are any of them false or otherwise bad sources? How can you tell?
 +
#Bonus but very important question: How do you know that some of these sources aren't galaxies? Can you find something that is obviously a galaxy on the images? Can you think of a way using public data that already exist to check on the "galaxy-ness" of some of these objects?
  
−
=Making color-color and color-magnitude plots=
+
<font color="red">I provided some example plots in ysoplots.ps in each of the sa101 and cg4 directories.  In those plots, the YSO candidates that, by my calculation, pass the Gutermuth criteria, are circled.  (Check me on this!) However, note that not all of those sources may be real! Overlay them on any of the mosaics using sa101ysocand.reg or cg4ysocand.reg to check on which are real.  Moreover, because of the overlap of the mosaics, I may have "rediscovered" the same stars more than once. Overlay the two region files on the same mosaic to check. (Change the symbol color or shape by editing the region file, being careful to save it as a plain text file.)</font>
  
−
[[Color-Magnitude and Color-Color plots| Read about color-magnitude and color-color plots in general here first]].  Get Excel to cough up the magnitudes and learn how to make it generate a plot.  (DO I NEED TO HAVE SOMEONE WRITE A TUTORIAL ON THIS?)  The best way to pick which colors to plot, to be brutally honest, is to do a literature search, look at what other people did and how they interpreted it, and then make the same plot for your own data.  Try some of the plots from the intro presentation, or papers mentioned in the IR section of [[Finding cluster members]], but you should feel encouraged to branch out and try other papers that you find in the literature, since there are LOTS of color-color combinations, and they all tell you different things. [[Color-color plot ideas]] (Don't peek until you're stumped!)
+
=Making SEDs <font color="red">HWK</font>=
  
−
#Pick at least one color-color or color-magnitude plot to make.  Figure out a way to make it ignore the -9 (no data) flags. Where are the plain stars?  Where are the IR excess objects?
+
'''Big picture goal''': Understand what an SED is and why it matters.
−
#Where are the famous objects in the plot?  Where are the new YSO candidates?
 
−
#Make a new column in your Excel spreadsheet with some colors.  Is there a way you can get Excel to tell you automatically which objects have an IR excess?
 
−
#Bonus but very important question: How do you know that some of these sources aren't galaxies? Can you find something that is obviously a galaxy on the images?  Can you think of a way using public data that already exist to check on the "galaxy-ness" of some of these objects?  (Read about [[Finding cluster members]].)
 
  
−
=Making SEDs=
+
'''More specific shorter term goals''': Make at least one SED.
  
−
[[SED plots| Read about SEDs in general here first]].  Get [[Russ Laher's spreadsheet]] from me, or write your own.  Make sure you understand the difference between plotting up a ''flux density'' as a function of wavelength versus an ''energy density'' as a function of wavelength. (You may need to [[Units | read about Spitzer units]] first.)  Note that you probably want to make it a plot of log energy vs. log wavelength, not linear values.
+
'''Relevant links from L1688 page''': [[Units]] and [[SED plots]] and [[Russ Laher's spreadsheet]] and [[Studying Young Stars]]
  
 +
'''Questions for you''':
 
#Pick some objects to plot up, maybe some of the famous ones from above would be a good place to start, or the ones you flagged above as having an IR excess.   
 
#Pick some objects to plot up, maybe some of the famous ones from above would be a good place to start, or the ones you flagged above as having an IR excess.   
−
#What do the IR excesses look like in your plots?  Do they look like the SEDs [[Studying Young Stars| on this page]] or in the intro presentation?  
+
#What do the IR excesses look like in your plots?  Do they look like you expected?  
−
#Which ones of these sources have optical (or any other) data as well, from your web search above, or from the literature?  Add these to your bandmerged catalog (not sure if Russ' spreadsheet can handle this...)
+
 
−
#If using Russ' spreadsheet, fit some SEDs with some blackbodies. How many blackbodies does it take to make a good fit to some of the sources with the most detections (like all 3 2MASS, all 4 IRAC, and MIPS-24)?
+
<font color="red">I made some SEDs and will email them around to give you an indication of what kinds of numbers you should be getting when you do this calculation for yourself. Many of them do NOT look like I expect. The 24 micron flux may be wrong for some, and the strange shape of some others of them suggest that they are not real and/or background galaxies. Note that I did this just for the objects that I selected via Gutermuth method, and not the set of previously known objects.</font>
  
 
=Analyzing SEDs=
 
=Analyzing SEDs=
 +
 +
'''This is advanced, and we may not get here.'''  And, lots of information on the L1688 page, sorry.
  
 
Add a new column in Excel to calculate the slope between 2 and 8 microns in the log (lambda*F(lambda)) vs log (lambda) parameter space. This task only makes sense for those objects with both K band and IRAC-4 detections.  (For very advanced folks: ''fit'' the slope to all available points between K and IRAC-4 or MIPS-24.  How does this change the classifications?)
 
Add a new column in Excel to calculate the slope between 2 and 8 microns in the log (lambda*F(lambda)) vs log (lambda) parameter space. This task only makes sense for those objects with both K band and IRAC-4 detections.  (For very advanced folks: ''fit'' the slope to all available points between K and IRAC-4 or MIPS-24.  How does this change the classifications?)
Line 172: Line 263:
 
*if the slope < -1.6 then class = III
 
*if the slope < -1.6 then class = III
 
These classifications come from Wilking et al. (2001, APJ, 551, 357); yes, they are the real definitions  ([[Studying Young Stars| read more about the classes here]])!  
 
These classifications come from Wilking et al. (2001, APJ, 551, 357); yes, they are the real definitions  ([[Studying Young Stars| read more about the classes here]])!  
−
#How many class I, flat, II and III objects do we have in this set of extractions?  [[Finding cluster members| Read about finding cluster members]] and then decide how many of the objects in this set of extractions are really cluster members, which aren't, and which ones are ambiguous. 
+
#How many class I, flat, II and III objects do we have?
−
#Does the ratio of Class I, flat, II, and III objects change when considering just the objects you think are members?  Assuming that the classes are really representative of ages, do you see how cluster membership can affect the age you estimate for a cluster?
 
 
#Where are the objects with infrared excesses located on the images? Are all the Class Is in similar sorts of locations, but different from the Class IIIs?
 
#Where are the objects with infrared excesses located on the images? Are all the Class Is in similar sorts of locations, but different from the Class IIIs?
−
 
−
 
−
For very advanced folks: [http://cfa-www.harvard.edu/youngstars/dalessio/ suite of online models from D'Alessio et al.] and [http://caravan.astro.wisc.edu/protostars/ suite of online models from Robitaille et al.].  Compare these to the SEDs we have observed.
 
  
 
=Writing it up!=
 
=Writing it up!=
  
−
Write up your results. Be sure to include:
+
We need to write an AAS abstract!  And, lots of information on the L1688 page, sorry.
−
#How the data were taken.
 
−
#How the data were reduced.
 
−
#What the Spitzer properties are of the famous objects, including how the Spitzer observations confirm/refute/resolve/fit in context with other observations from the literature.
 
−
#What the Spitzer properties are of other sources here, including objects you think are new YSOs (or objects you think are not), and why you think that.
 
−
#How this region compares to other regions observed with Spitzer.
 
−
 
 
−
Take inspiration for other things to include from other Spitzer papers on star-forming regions in the literature.
 

Latest revision as of 19:01, 23 November 2010

This page is meant to be used in conjunction with the Working with L1688 page, and was developed specifically for the 2010 CG4 team visit.


Downloading the data DONE

Using the SHA, a concrete example is already tuned to this project. There are bugs in the SHA! Let's work through this one together, as a big group.

Big picture goal: Get you comfortable enough to search for your own favorite target, understand what to do with the search results, and download data.

More specific shorter term goals: Search on our targets. Understand the difference between the observations. Understand why I chose to use the observations that I did.

Relevant links from L1688 page: Using_the_SHA,_a_concrete_example

Questions for you:

  1. Compare the IRAC AORs for sa101 from pid 20714 and for cg4 from pid 462. How are they the same/different?
  2. Figure out how to get the instrument parameters. Does this help you assess how the AORs are the same/different? (For advanced folks - how come I'm not using the AOR from pid 20714?)
  3. Where is SA101 with respect to CG4? How much overlap is there in these observations?

Making the mosaics NEARLY DONE

In the generic case for most targets, you can probably use the online mosaics that come as PBCD (Level 2) mosaics (or, later, Level 3 delivered products, if they exist for the region you want). In this case, we have some special circumstances: one of the observations was taken with cluster-mode targets, and there are some very bright stars here (bright at all Spitzer bands) which prompt some instrumental effects that require some special handling.

Big picture goal: Recognize at a glance what is an instrumental artifact and what is real.

More specific shorter term goals: Look at the online mosaics and the mosaics I created. Understand the differences. Understand why I had to make the mosaics for us and why we could not use the online mosaics in this case.

Questions for you:

  1. Compare the online mosaics with mine. Did I do a better job of creating good mosaics?
  2. What is image artifact and what is real sky? What is saturated?
  3. How does the short frame differ from the long frame? Why do we do this?
  4. HWK Notice the pixel scale. What is the real pixel scale of IRAC (and MIPS)? What are the pixel scales of the images? Does that actually change the resolution? (for advanced folks - why did I do this?)


Getting data from other wavelengths BASICALLY DONE

You have already made some progress on this in your literature search this Spring. (See Putting CG4 in Context Homework Page).

Big picture goal: Understand how to use the various archives to find non-Spitzer data.

More specific shorter term goals: Go get data for SA101 and CG4 for comparison to our Spitzer data.

Relevant links from L1688 page: How can I get data from other wavelengths to compare with infrared data from Spitzer?

Questions for you:

  1. If you have not yet, figure out where CG4+SA101 are in the sky. How do they fit in to the larger Gum Nebula?
  2. What wavelength did you pick and why?
  3. What coordinate system did you pick and why?
  4. HWK Get a smaller-scale image too, on the same scale as the Spitzer images.
  5. HWK What band did you pick and why? How is the resolution different? (You may need to do the next section before you can answer this.)
  6. HWK Figure out how to get a 2MASS catalog. I've done this for you, but you should be able to get this yourself too.

Investigating the mosaics HALF DONE

It is "real astronomy" to spend a lot of time staring at the mosaics and understanding what you are looking at. Don't dismiss this step as not "real astronomy" just because you are not making quantitative measurements. This is time well-spent. Start with my mosaics, as opposed to the online mosaics.

Big picture goal: Understand what is seen at each Spitzer band.

More specific shorter term goals: Recognize how the images differ between SA101 and CG4, and among the various bands.

Relevant links from L1688 page: How can I make a color composite image using Spitzer and/or other data? and the questions on that page.

Questions for you:

  1. How does the number of stars differ across the bands? Which band has the most stars? The fewest? (Bonus question: why?) The most nebulosity? The least? (Bonus question: why?) Are there more stars in the regions of nebulosity, or less? Why?
  2. Do the star counts differ between SA101 and CG4? Why?
  3. Which objects are saturated, in which bands?
  4. HWK How big are any of the features in the image (nebulosity, galaxy, space between objects)? (What do I mean by big?) in pixels, arcseconds, parsecs, and/or light years? (Hint: you need to know how far away the thing is. If it helps, there are 3.26 light years in a parsec.)
  5. HWK Make a three-color image. What happens when you include a MIPS-24 mosaic in as one of the three colors with IRAC as the other two? Do the stars match up? Does the resolution matter? Can you tell from just a glance at the three-color mosaic which stars are bright at MIPS wavelengths?
  6. HWK Which features are found across multiple wavelengths, beyond the Spitzer regime? Why?
  7. HWK Obtain IRAS images from the web (via the SHA or other methods) and line them up with the Spitzer images of comparable wavelengths (e.g., 8 um with 12 um, 25 um with 24 um). How much more detail do you see with Spitzer that was missed by IRAS? Do you see more texture in the nebulosity? More point sources?

Previously identified sources DONE

You've already done this. There is a table in our proposal.

Previously Known Objects from Reipurth and Pettersson (1993) ... fixed CG-Halpha 4

Star RA (J2000) Dec (J2000) V (B-V) (U-B) Region
CG-Halpha 1 07 30 37.77 -47 25 07.21 >17 none none Sa 101
CG-Halpha 2 07 30 57.63 -46 56 12.50 >17 none none Sa 101
CG-Halpha 3 07 31 10.89 -47 00 33.40 14.99 1.60 0.91 Sa 101
CG-Halpha 4 07 31 21.92 -46 57 45.14 ** 14.59 1.40 0.92 Sa 101
CG-Halpha 5 07 31 36.65 -47 00 14.13 15.25 1.26 0.23 Sa 101
CG-Halpha 6 07 31 37.45 -47 00 22.19 14.21 1.42 0.90 Sa 101
CG-Halpha 7 07 33 26.92 -46 48 43.51 13.97 1.19 0.84 CG 4
CG-Halpha 8 07 15 49.86 -48 31 27.16 15.33 1.39 0.13 CG 13
PHalpha 92 08 28 40.73 -33 46 23.17 13.38 1.27 0.91 CG 22

Big picture goal: Understand what has already been studied and what hasn't in the image.

More specific shorter term goals: Determine if the previously-known objects are saturated or not.

Relevant links from L1688 page: How can I find out what scientists already know about a particular astronomy topic or object? and I'm ready to go on to the "Advanced" Literature Searching section

Questions for you:

  1. For each of the known objects, you have the RA/Dec - what are the pixel coordinates in the image? Does it change among the IRAC bands? In the MIPS band?

Doing photometry MOSTLY HWK

OK, this step is doing to take the longest, be the most complex, involve the most steps and the most math.

Never just trust that the computer has done it right. It probably did what you asked it to do correctly, but you asked it to do the wrong thing. Always make some plots to test and see if the photometry seems correct.

Big picture goal: Understand what photometry is, and what the steps are to accomplish it. Understand the units of Spitzer images. Understand how to assess if your photometry makes sense.

More specific shorter term goals: Do photometry on a set of mosaics for the same sources. Assess whether your photometry seems right.

NEW: CG4 photometry: more detailed instructions

Relevant links from L1688 page: Units and Photometry and I'm ready to go on to a more advanced discussion of photometry and Aperture photometry using APT


Questions for you:

  1. Use APT to explore the various parameters. What is a curve of growth?
  2. What are the best parameters to use? (RTFM to find what the instrument teams recommend.) What are the implications of those choices? What happens if you use other choices?
  3. We should decide as a group which set of sources to measure, and have everyone measure the same sources. We will then compare all of our measurements among the whole group.
  4. Compare the MOPEX source identifications I did from just one band with their corresponding image. Is it getting fooled by detector artifacts? you will need skyview for this, because you have the tbl files, as opposed to region files. Let me know if you want the reg files and I'll make you some.
  5. Compare the MOPEX source identifications from, say, IRAC band 3 with the image from IRAC band 1, or the source extractions from MIPS-24 with image from IRAC band 1. Are there a lot of stars (or other objects) in common? How does the nebulosity affect it? you will need skyview for this, because you have the tbl files, as opposed to region files. Let me know if you want the reg files and I'll make you some.
  6. Why did this happen? (see below)

Cg424.png

Bandmerging the photometry HWK

I use my own code to do this; there is no pre-existing package to do this. If you do it by hand (or semi-by-hand) using APT, you can manually merge the photometry. My merged photometry includes J through M24.

Big picture goal: Understand what this process is.

More specific shorter term goals: Do this by hand.

Relevant links from L1688 page: Resolution

Questions for you:

  1. Make sure that I've merged the right sources across several bands by spotchecking a few of them. (Find an object that the catalog says is detected in at least 3 bands and then overlay the images in a 3-color image or Spot to see if there is really a source there, at exactly that spot, in all bands, or if it's a cluster of objects, or different objects getting bright at different bands.
  2. Have I 'lost' the instrumental artifacts you noticed in the previous section? Or are there instrumental artifacts or otherwise false sources sill in the list?
  3. Does resolution matter? (Can you find a place where more than one IRAC source can be matched to the same MIPS source?)


Working with the data tables PARTIALLY HWK

Big picture goal: Understand how to work with the tables. Understand how to convert magnitudes back and forth to flux densities.

More specific shorter term goals: Import the table into excel. Program a spreadsheet to convert between mags and flux densities.

Relevant links from L1688 page: Units and Skyview but lots of important words actually on the L1688 page itself, sorry.

Questions for you:

  1. How many stars are detected in each band? Is this about what you expected based on your answer to the questions in the mosaic section above? HINT: you can do this using Excel, you don't need to count these manually!! Ask if you need a further hint on exactly how to do this.
  2. Which stars in the catalog are the stars identified in the literature?
  3. DONE Make sure you understand how I got the magnitudes from the fluxes (or the fluxes from the magnitudes). You will need magnitudes for the next step, and fluxes for the step after that.

Making color-color and color-magnitude plots HWK

Big picture goal: Understand what plots to make. Understand the basic idea of using them to pick out certain objects.

More specific shorter term goals: Make some plots. Understand the basic approach of Gutermuth et al. (see Gutermuth et al. 2009, Appendix A -- this was handed out to you in hard copy in June)

Relevant links from L1688 page: Color-Magnitude and Color-Color plots and Finding cluster members and Color-color plot ideas

Questions for you:

  1. Pick a diagnostic color-color or color-magnitude plot to make. Does my photometry seem ok?
  2. Pick at least one color-color or color-magnitude plot to make. Figure out a way to ignore the -9 (no data) flags. Where are the plain stars? Where are the IR excess objects?
  3. Where are the famous objects in the plot? Where are the new YSO candidates I used the Gutermuth method to find?
  4. Make a new column in your Excel spreadsheet with some colors. Is there a way you can get Excel to tell you automatically which objects have an IR excess? Can you implement the Gutermuth selection? (You may not be able to do so.)
  5. Make the plots that go into the Gutermuth selection, including the relevant lines on the plot.
  6. Of the objects I have that fit the Gutermuth criteria, are any of them false or otherwise bad sources? How can you tell?
  7. Bonus but very important question: How do you know that some of these sources aren't galaxies? Can you find something that is obviously a galaxy on the images? Can you think of a way using public data that already exist to check on the "galaxy-ness" of some of these objects?

I provided some example plots in ysoplots.ps in each of the sa101 and cg4 directories. In those plots, the YSO candidates that, by my calculation, pass the Gutermuth criteria, are circled. (Check me on this!) However, note that not all of those sources may be real! Overlay them on any of the mosaics using sa101ysocand.reg or cg4ysocand.reg to check on which are real. Moreover, because of the overlap of the mosaics, I may have "rediscovered" the same stars more than once. Overlay the two region files on the same mosaic to check. (Change the symbol color or shape by editing the region file, being careful to save it as a plain text file.)

Making SEDs HWK

Big picture goal: Understand what an SED is and why it matters.

More specific shorter term goals: Make at least one SED.

Relevant links from L1688 page: Units and SED plots and Russ Laher's spreadsheet and Studying Young Stars

Questions for you:

  1. Pick some objects to plot up, maybe some of the famous ones from above would be a good place to start, or the ones you flagged above as having an IR excess.
  2. What do the IR excesses look like in your plots? Do they look like you expected?

I made some SEDs and will email them around to give you an indication of what kinds of numbers you should be getting when you do this calculation for yourself. Many of them do NOT look like I expect. The 24 micron flux may be wrong for some, and the strange shape of some others of them suggest that they are not real and/or background galaxies. Note that I did this just for the objects that I selected via Gutermuth method, and not the set of previously known objects.

Analyzing SEDs

This is advanced, and we may not get here. And, lots of information on the L1688 page, sorry.

Add a new column in Excel to calculate the slope between 2 and 8 microns in the log (lambda*F(lambda)) vs log (lambda) parameter space. This task only makes sense for those objects with both K band and IRAC-4 detections. (For very advanced folks: fit the slope to all available points between K and IRAC-4 or MIPS-24. How does this change the classifications?)

  • if the slope > 0.3 then the class = I
  • if the slope < 0.3 and the slope > -0.3 then the class = 'flat'
  • if the slope < -0.3 and the slope > -1.6 then class = II
  • if the slope < -1.6 then class = III

These classifications come from Wilking et al. (2001, APJ, 551, 357); yes, they are the real definitions ( read more about the classes here)!

  1. How many class I, flat, II and III objects do we have?
  2. Where are the objects with infrared excesses located on the images? Are all the Class Is in similar sorts of locations, but different from the Class IIIs?

Writing it up!

We need to write an AAS abstract! And, lots of information on the L1688 page, sorry.

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