Difference between revisions of "Working with the IC 417 data"

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FOR REFERENCE: [[IC 417 Bigger Picture and Goals]]
 
FOR REFERENCE: [[IC 417 Bigger Picture and Goals]]
  
FOR REFERENCE: [[IC 417 DVD Contents]]. Includes instructions on how to force your computer to read any files with an extension you don't recognize (.tbl, .reg).
+
FOR REFERENCE: [[IC 417 Box Disk Contents]]. Includes instructions on how to force your computer to read any files with an extension you don't recognize (.tbl, .reg).
 +
 
 +
FOR CONTEXT: I know we have a wide range of ages and capabilities here. There are things tagged "BONUS" in here - this means "if you get to this point and need something to do while everyone else catches up, work on this." You can also do this later, at home, when you are reviewing what we did this summer. You need not do it here and now, or even necessarily at all. But it will give you a deeper understanding of what is going on.
  
 
=Useful Positions=
 
=Useful Positions=
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We are studying a square that is ~1 deg on a side, centered on 5:28:00 34:30:00.  
 
We are studying a square that is ~1 deg on a side, centered on 5:28:00 34:30:00.  
  
=Obtaining the data and bandmerging across catalogs=
+
'''Why?''' (a) Because we are looking for YSOs. (b) Because Camargo says there are several clusters of young stars in this region, and so we ought to be able to find some.
  
<font color="red">DONE</font>
+
'''Relevant links for reference''': [[IC 417 Bigger Picture and Goals]]
 +
 
 +
=Obtaining the imaging data=
 +
 
 +
<font color="red">DONE </font> (but be sure you have the files you need!)
  
We found data for this region from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008.  
+
'''Why?''' Need to figure out what data are in this region from which we might obtain photometry (=quantitative measures of brightness of objects) to use to look for IR excess sources.
  
We have already used FinderChart and other IRSA tools to retrieve 2MASS and WISE (and even Spitzer) data and catalogs.  
+
We found imaging data for this region from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008, but we can only get our hands on imaging data from DSS, WISE, 2MASS, GLIMPSE, and IPHAS.  We have already used FinderChart and other IRSA tools. We have already used Skyview at Goddard. We have already used ds9.
  
'''Big picture goal''': Get the data you need for this project. Get you comfortable enough to search for your own favorite target in WISE, understand what to do with the search results, and download data.  
+
'''Big goal''': Learn how to get images so that you can do this in the future without me.
  
'''More specific shorter term goals''': Obtain the relevant catalogs.
+
'''Process''': Either re-pull FITS images for yourself for our region in DSS, 2MASS, and WISE, or get them from the Box drive. You'll need this for the next step. BONUS: Spitzer/IRAC (GLIMPSE), and IPHAS. (I don't have images for UKIDSS.) NB: GLIMPSE and IPHAS on the Box disk do not cover the whole region -- you'll have to pull these images yourself if you need them over a different region.  
  
'''Relevant links''':  
+
'''Relevant links for reference''':  
 
*[[How do I download data from WISE?]]  
 
*[[How do I download data from WISE?]]  
 
*[http://irsa.ipac.caltech.edu/applications/wise/  Access the WISE archive directly].  
 
*[http://irsa.ipac.caltech.edu/applications/wise/  Access the WISE archive directly].  
 
*http://irsa.ipac.caltech.edu/Missions/wise.html WISE
 
*http://irsa.ipac.caltech.edu/Missions/wise.html WISE
 
*http://irsa.ipac.caltech.edu/Missions/2mass.html 2MASS
 
*http://irsa.ipac.caltech.edu/Missions/2mass.html 2MASS
 +
*[http://skyview.gsfc.nasa.gov/cgi-bin/skvadvanced.pl Goddard's Skyview]
 +
*[http://nitarp.ipac.caltech.edu/resource/8 ds9 NITARP Tutorial] (listed on that page, along with installation tips)
 +
*[http://hea-www.harvard.edu/RD/ds9/site/Download.html ds9 Download site]
 
*http://irsa.ipac.caltech.edu/data/SPITZER/GLIMPSE/ GLIMPSE
 
*http://irsa.ipac.caltech.edu/data/SPITZER/GLIMPSE/ GLIMPSE
*http://www.ukidss.org/ UKIDSS
 
 
*http://www.iphas.org/ IPHAS
 
*http://www.iphas.org/ IPHAS
  
What I did:
+
=Investigating the big mosaics =
#Download catalogs from these sources over our region.
 
#Using a computer, upload catalog1. Then, for each of the sources in catalog2, metaphorically sit on each source in catalog2 and look for a match in catalog1. If I find a match, associate those sources. If I do not find a match, sometimes I added the entire source to the catalog, and sometimes I just dropped it. (there are a LOT of sources here, many we do not care about.)
 
#Now have catalog1+catalog2. Do same for each source in catalog3, such that I merge in catalog3 with catalog1+2. Repeat for catalog4, etc.
 
#Given ensemble catalog, look for matches with Xavier's list of interesting sources. Tag them in the database.
 
#Repeat for Jose et al. 2008 Halpha stars, OB stars, and IPHAS' list of Halpha stars.
 
The process of merging the bands across catalogs is called "bandmerging."
 
 
 
After this process, I have about 29,000 objects in a master catalog, about 200 of which we care about. Remember that we are interested in the ENTIRE set of {things Xavier tagged as possibly young from the AllWISE catalog} PLUS {things Xavier tagged as possibly young from his own PhotVis reprocessing of the WISE data} PLUS {things Jose et al. tagged as Halpha stars} PLUS {things Meyer & Macak tagged as OB stars} PLUS {things IPHAS tagged as bright in Halpha}.
 
 
 
'''Questions for you''':
 
 
 
#How do you download catalogs for any of these surveys?
 
  
=Investigating the big mosaics =
+
<font color="green"><strike>DO THIS!</strike></font> <font color="red">DONE! </font>
  
<font color="red">Should I decommission this?</font>
+
'''Why?''' There is astrophysics in understanding what is bright/faint in each band. Spatial resolution is going to play a role downstream.
  
 
'''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, and you should plan on investing some time doing this section.'''  Some aspects of this were already discussed in the context of the Resolution worksheet.
 
'''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, and you should plan on investing some time doing this section.'''  Some aspects of this were already discussed in the context of the Resolution worksheet.
  
'''Big picture goal''': Recognize what is an instrumental artifact and what is real. Understand what is seen at each WISE and Spitzer band and all the other archival bands.
+
'''Big goal''': Understand what is part of the sky and what is an artifact (e.g., not part of the sky).  Recognize how the images differ among the various bands, and why.  ''(NB: this has come up during more than one telecon, which is why this task is here!)''  Understand (remind yourself) which survey has the lowest (worst) spatial resolution, and which has the best.
  
'''More specific shorter term goals''': Understand what is part of the sky and what is an artifact (e.g., not part of the sky).  Recognize how the images differ among the various bands, and why.
+
'''Relevant links for reference''':   
 
 
'''Relevant links''':   
 
 
*[[What is a mosaic and why should I care?]]  
 
*[[What is a mosaic and why should I care?]]  
 
*Possibly [[Making Mosaics Using MONTAGE]].  
 
*Possibly [[Making Mosaics Using MONTAGE]].  
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*[http://nitarp.ipac.caltech.edu/resource/8 ds9 NITARP Tutorial] (listed on that page, along with installation tips)
 
*[http://nitarp.ipac.caltech.edu/resource/8 ds9 NITARP Tutorial] (listed on that page, along with installation tips)
 
*[http://hea-www.harvard.edu/RD/ds9/site/Download.html ds9 Download site]
 
*[http://hea-www.harvard.edu/RD/ds9/site/Download.html ds9 Download site]
 +
*[http://irsa.ipac.caltech.edu/fftools/app.html IRSA Viewer]
  
'''Data''':
+
'''Process''': Load the images into a viewer of your choice, ds9 or IRSA Viewer. Compare the images. Answer the questions below.
Get from me (or download yourself) the fits files for DSS, WISE, 2MASS, Spitzer/IRAC (GLIMPSE), and IPHAS. (I don't have images for UKIDSS.)
 
  
 +
'''Hints and tips''': You may find it helpful to make 3-color images to more directly compare images in exactly the same region. Zoom in/out. Play with color stretches to bring out detail in the images.
  
 
'''Questions for you''':  
 
'''Questions for you''':  
 
#'''MOST IMPORTANT of these questions: Compare the mosaics across the bands. What changes? What stays the same? Why? (This is a DEEP question! See also next questions.)'''
 
#'''MOST IMPORTANT of these questions: Compare the mosaics across the bands. What changes? What stays the same? Why? (This is a DEEP question! See also next questions.)'''
#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?  
+
#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: why?) Are there more stars in the regions of nebulosity, or less? Why?  
 
#What is saturated? Are the same objects saturated in all bands? What are some other instrumental effects you can see?  
 
#What is saturated? Are the same objects saturated in all bands? What are some other instrumental effects you can see?  
#Notice the pixel scale. Which survey has the lowest resolution (biggest pixels)? (Bonus: is that the same as the native pixels for the survey? You will need to Google, or go back to your [[IC 417 Resolution Worksheet]] notes.
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#Notice the pixel scale. Which survey has the lowest resolution (biggest pixels)? (BONUS: is that the same as the native pixels for the survey? You will need to Google, or go back to your [[IC 417 Resolution Worksheet]] notes.)
 
#Make a three-color image. Do the stars match up? Does the nebulosity?  
 
#Make a three-color image. Do the stars match up? Does the nebulosity?  
#BONUS: 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.)
+
#BONUS: 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 -- check the proposal for the number. If it helps, there are 3.26 light years in a parsec.)
 +
 
 +
=Obtaining the catalog data and bandmerging across catalogs=
 +
 
 +
<font color="red">DONE</font>
 +
 
 +
'''Why?''' We need photometry (=a quantitative measure of brightness) of our sources. Others have already done photometry for us so we don't have to. We need to make the matches across catalogs -- no one else has ever done this before, by which I mean identified which sources in this region are seen in each one of these surveys, and tied the measurements together. (Think about that for a bit -- no one else has ever done this before...)
 +
 
 +
We found data for this region from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008.  We have already used FinderChart and other IRSA tools to retrieve 2MASS and WISE (and Spitzer) catalogs.
 +
 
 +
'''Big goal''': Learn how to get catalogs so that you can do this in the future without me. Understand what bandmerging is and why we need to do it.
 +
 
 +
'''Relevant links for reference''':
 +
*[[How do I download data from WISE?]]
 +
*[http://irsa.ipac.caltech.edu/applications/wise/  Access the WISE archive directly].
 +
*http://irsa.ipac.caltech.edu/Missions/wise.html WISE
 +
*http://irsa.ipac.caltech.edu/Missions/2mass.html 2MASS
 +
*http://irsa.ipac.caltech.edu/data/SPITZER/GLIMPSE/ GLIMPSE
 +
*http://www.ukidss.org/ UKIDSS
 +
*http://www.iphas.org/ IPHAS
 +
 
 +
The process of merging the bands across catalogs is called "bandmerging."  I did this for you because it would be a GIGANTIC pain in Excel (especially for 30,000 sources), or (worse) by hand. I"ve heard TopCat can do it easily, but I've never used that.
 +
 
 +
'''Process''' (What I did):
 +
#Download catalogs from these sources over our region.
 +
#Using a computer, load in catalogA. Then, for each of the sources in catalogB, metaphorically sit on each source in catalogB and look for a match in catalogA. If I find a match, associate those sources. If I do not find a match, sometimes I added the entire source to the catalog, and sometimes I just dropped it. (There are a LOT of sources here, many we do not care about, so having each and every source in here is less important than it might be.)
 +
#Now have catalogA+catalogB. Do same for each source in catalogC, such that I merge in catalogC with catalogA+B. Repeat for catalogC, etc.
 +
#Given ensemble catalog, look for matches with Xavier's list of interesting sources. Tag them in the database.
 +
#Repeat for Jose et al. 2008 Halpha stars, OB stars, and IPHAS' list of Halpha stars.
 +
 
 +
After this process, I have about 29,000 objects in a master catalog, about 200 of which we care about based on other steps below. Remember that we are interested in the ENTIRE set of {things Xavier tagged as possibly young from the AllWISE catalog} PLUS {things Xavier tagged as possibly young from his own PhotVis reprocessing of the WISE data} PLUS {things Jose et al. tagged as Halpha stars} PLUS {things Meyer & Macak tagged as OB stars} PLUS {things IPHAS tagged as bright in Halpha}.
  
 
=Previously identified sources=
 
=Previously identified sources=
  
<font color="red">Essentially done.</font>
+
<font color="red">NOW COMPLETELY DONE.</font>  
 +
 
 +
'''Why?''' Others have gone before us, and it pays to learn from them rather than reinvent the wheel.
  
You've already really done this prior to the visit, but this is where it kind of falls in the logical progression here. (I see the progression as : pick target, get data, get numbers for the sources in the images first from the literature and where others have done it for us, then do more ourselves, then make plots, etc.)
+
'''Big goal''': Understand what has already been studied and what hasn't in the region we care about.
  
'''Big picture goal''': Understand what has already been studied and what hasn't in the region we care about.
+
'''Relevant links for reference''': [[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]] and [http://irsa.ipac.caltech.edu/fftools/app.html IRSA Viewer]
  
'''Relevant links''':
 
*[[How can I find out what scientists already know about a particular astronomy topic or object?]]
 
*[[I'm ready to go on to the "Advanced" Literature Searching section]]
 
  
'''Process''':
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'''Process (what we did before)''':
 
#Search ADS, SIMBAD.
 
#Search ADS, SIMBAD.
 
#Identify literature of relevance.
 
#Identify literature of relevance.
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#Tag the interesting objects as interesting in the database so we can find them again.
 
#Tag the interesting objects as interesting in the database so we can find them again.
  
'''IMPORTANT''': when we are done with all of this, at the end of the process, for the sources we have settled on as 'interesting', we should get into SIMBAD and search for each of our sources, just to get another handle on whether or not anyone has done anything on them before -- because there just might be something else already identified in the literature.
+
'''Process (what to do now) and questions''':
 
+
#Load in one of the big images of your choice into ds9 or IRSA Viewer.
=Data Tables, part 1=
+
#Get the regions files that have all the literature sources and overlay them. (You probably want to do them one at a time and delete each one before loading the next.) Where are they in the image?
 
+
#Delete any regions you have loaded, and get the regions file that has the cluster locations from Camargo et al. and overlay them.  
You may have already have developed some of these skills via the [http://coolwiki.ipac.caltech.edu/index.php/IC_417_Summer_visit_logistics#Excel_to_know|shortlist of stuff I sent in April]. If not, this is the time to learn!
+
##One file is the FSR clusters as reported in Camargo et al., with the radii as reported in Camargo et al. Table 1. You should overplot this, compare it to the figure (or the file with the Camargo F19 clusters) and think, "Holy crap these are a lot smaller than they show in Fig 19!" Yep. I don't know what is going on either. BONUS: go reread Camargo and see if you can figure out why.
 
+
##Load the file with the F19 clusters marked. Can you see the clusters their computer found by you yourself looking at the distribution of point sources in the image by eye? They used 2MASS to find these clusters, so you may wish to look first in JHK to see if you can find them by eye. Looking in WISE is also useful -- are they apparent there? They might not be obvious to you. Either way, are you more or less confidence that Camargo et al. (and references therein) have actually identified clusters? Just because their computer said it and they said it in their paper does not mean it is right. You need to decide if you believe them. (Their confidence is high enough that they published it, so that should tell you that they believe it. To rigorously decide if you believe them, you need to read their description of what they did in their paper and decide if you believe that. Yes, that's a double bonus task.)
'''Big picture goal''': Learn how to manipulate data tables. Look at the data tables to identify what you need. Start to cope with source list proliferation.
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#Delete any regions files you have loaded, and get the regions file that has all the "sources in which we are interested" and overlay them. Where are they in the images? ''(Heads up Garrison! :) This is what you wanted to do!)''
 
 
'''More specific shorter term goals''': Understand how to import plain text tables into Excel (or another spreadsheet of your choice). Really look at the files as retrieved from the WISE archive and look at files as sent by Xavier and determine the relevant information out of these catalogs. Keep track of which files are which.
 
 
 
'''Relevant links''':  
 
*[http://www.youtube.com/watch?v=nCJ3ctOGvNk YouTube video] on what tbl files are, how to access them, and specifically how to import tbl files into xls. (10min) 
 
 
 
Note that many data tables come with many, many, many lines (like more than 100) at the top explaining what the contents of the file are. These are useful for keeping with the file (like a FITS header is useful to keep with the image), but when reading it into Excel, you may wish to delete all but a note to yourself about what the file is, and the headers of the data columns themselves.
 
  
'''Tasks and Questions for you''':  
+
'''Hints and Advice:''' The files on the box drive are:
#Practice for getting catalogs on your own: Get a WISE catalog, either from a download or the DVD. Find a way to read the file, perhaps by loading it into Excel. Cope with the long header - scan it, keep it elsewhere, but you may not want to read it in to your Excel copy. What information do we need? How do you figure out which ones have bad photometry?
+
*CamargoF19Clusters.reg = the clusters with positions as reported in Camargo et al., with sizes corresponding to what I can see in their Fig 19 (to the accuracy I can read it off the figure).
#I have already merged the catalogs from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008. The entire catalog has ~29,000 sources. This pretty much brings Excel to its knees. There is some utility in having the entire data set in order to make plots of 'everything' in order to see how the YSOs stand out as different. I dumped the entire catalog into a text file for you if you want it.
+
*FSRtable1.reg = the FSR clusters as reported in Camargo et al., with the radii as reported in Camargo et al. Table 1.
#I have a short list of ~200 sources that are our focus for our work. This catalog has all the data, but also an indication of why the source is on the list of interesting sources. Values for the "whyhere" column are combinations of 2-letter codes:
+
*carbonstars.reg = the one carbon star we know about
***xp = xavier found it from PhotVis processing (x=Xavier, p=PhotVis)
+
*interestingthings20150604.reg = all the sources in which we are interested (nothing dropped yet) -- DON'T LOAD THIS UNTIL YOU HAVE LOADED AND ABSORBED ALL THE REST OF THESE HERE because there are a lot of these sources and they in essence drown out the rest of the things here, in no small part because they overlay many of the other symbols.
***xw = xavier found it from the allWISE processing (x=xavier, w=wise)
+
*iphashalphastars.reg = all the objects reported by IPHAS as being bright in Halpha
***ha = Jose et al found it (and you corrected the positions for it) because it is an Halpha star (ha=Halpha)
+
*josehalphastars.reg = all the objects Jose et al. report as being bright in Halpha
***ih = IPHAS tagged it as bright in Halpha (=possibly young)
+
*obstars.reg = all the OB stars from the literature we could find. BONUS: Kronberger1 is shown in Camargo et al. F 19 as having an OB star in it. We don't have this star in our list. Can you go figure out what this object should be and where it comes from? We can add it to our list of objects in which we are interested.  
***ob = Meyer & Macak found it (and you corrected the positions for it) because it is an OB star (ob=OB)
+
*ourbigregion.reg = just for reference, in case you are using images other than mine -- this is a region file that defines the region that we are studying, e.g., the region covered in Camargo et al. F 19.
You will find some like 'xpxwha', which means Xavier found it in both of his processings (xp,xw), *and* it is an Halpha star (ha). There are many that have just one code.
 
*'''CAUTION 1:''' There are files from me with everything in the region (long) and files with just the things in which we are interested (short) -- meaning the literature-identified plus the new Xavier-identified.  
 
*'''CAUTION 2, AND THIS ONE'S A BIGGIE''': '''These catalog files generally have a mixture of detections and limits, measurements and errors, flux densities and magnitudes.''' You will need to be careful in importing this into Excel. The data are all Vega mags; some have errors and some have limits.
 
  
=Making color-color and color-magnitude plots=
+
=Data Tables (part 1) and Color-Color and Color-Magnitude Diagrams (part 1)=
  
 +
<font color="green"><strike>DO THIS!</strike></font> <font color="red">DONE! </font>
  
 +
'''Why?''' Xavier found sources with YSO-like colors by making a bunch of CMDs and CCDs and selecting objects from these diagrams. It behooves us to get a sense of what he did. (And, we will need to make more CMDs/CCDs downstream.)
  
OK, fair warning, some math involved, and the start of ''programming'' spreadsheets!
+
'''Big goal''': Learn how to manipulate data tables using IRSA Viewer for now (because it's easier for a quick plot and because it handles 29,000 sources more elegantly than Excel does). Make some of the plots Xavier made when he selected 'interesting' sources. Do our plots look like his from his paper?
  
'''Big picture goal''': Understand what plots to make. Understand the basic idea of using them to pick out certain objects.
+
'''Relevant links for reference''':  
 
+
*[http://irsa.ipac.caltech.edu/fftools/app.html IRSA Viewer]
'''More specific shorter term goals''': Make some color-color and color-mag plots using the complete WISE catalog imported into Excel in the last step. At the very least, make a plot of the entire distribution and highlight the YSO candidates from Xavier.  
 
 
 
'''Relevant links''':
 
 
*[[Color-Magnitude and Color-Color plots]]  
 
*[[Color-Magnitude and Color-Color plots]]  
 
*[[Gutermuth color selection]] - mostly currently Gutermuth color selection; includes analogy with M&Ms. Koenig color selection is similar in concept but uses different bands.
 
*[[Gutermuth color selection]] - mostly currently Gutermuth color selection; includes analogy with M&Ms. Koenig color selection is similar in concept but uses different bands.
 
*[[Finding cluster members]]  
 
*[[Finding cluster members]]  
 
*[[Color-color plot ideas]]  
 
*[[Color-color plot ideas]]  
*Also see slides from my set of talks on Monday.
+
*[http://arxiv.org/abs/1407.2262 Xavier's paper itself]
 +
*Also see slides from my talks on Monday.
  
'''Tasks and Questions for you''':  
+
'''Process''': Go get a WISE catalog for our region from IRSA, not me. Look at the data tables and Xavier's paper (available on the Box drive) to identify what you should plot. Make some plots that he made and see how our region compares to the regions he used in his most recent paper.
#To do these next steps, you need a catalog that merges the WISE catalog, the 2MASS catalog, and the catalog from Xavier. If you did all the steps in the prior task, you have this now; I also have a copy of this for you on the DVD.
 
#Start from the complete WISE catalog. Pick at least one color-color or color-magnitude plot to make (Suggestion: W1-W2 vs W3-W4, K vs. W1-W4 plot, or a W1 vs. W1-W4 plot).  Figure out a way to ignore the "no data" flags (exactly what they are depends on which file you are starting from - they could be 'null' or they could be '-9'). Does the photometry seem ok? Identify the regions where you expect to find the plain stars and the IR excess objects. 
 
#Which objects are selected by Xavier's method as YSO candidates? Overplot them '''on the same plot''' as above with a different color and/or shape symbol. You may wish to try drawing the line segments on the plot too.  
 
#Bonus - read in one of my catalogs from the DVD that has literature sources indicated (e.g, the 'interesting' file loaded into Excel in the last step). Overplot these on the same plot, with a different color and/or shape symbol. Are the literature sources tagged as YSO candidates by Xavier or not?
 
#EXTRA BONUS, especially when circling back to this step - are there any sources you can identify in this diagram that might be worth a second look in SED or images?
 
  
Notes: For a W1-W2 vs W3-W4 plot. W1-W2 is (should be) centered on zero, because most of the objects seen in W1 and W2 are plain stars, so the color is zero. W3-W4 is notably NOT zero, because the only objects seen at W4 are the ones notably bright at W4, so they all are brighter than plain stars at W4. This is going to be a different morphology than a I1-I2 vs I3-I4 plot, where a much larger number of sources are seen, and a large fraction of those are plain stars. This gave me heart failure during the 2012 summer visit until I realized this. For a K vs. W1-W4 plot, or a W1 vs. W1-W4 plot... The YSO candidates are bright and red, generally. There are other CMDs you can try. See any of the literature we read in the Spring for ideas.  After we include some optical data, there will be even more CMDs we can try. We will come back to this step.
+
'''Advice and Hints:''' Remember that a plain star should have zero infrared color for basically any combination. (At least, it is 0 as long as the color is (shorter wavelength) minus (longer wavelength) !) You may find that W3-W4 is notably NOT zero for rather a lot of objects, because the only objects seen at W3 or W4 at the distances we are talking about here are the ones notably bright at W4, so they all are brighter than plain stars at W4. This is going to be a different morphology than a, IRAC color-color diagram (I1-I2 vs I3-I4 plot from somewhere else in the galactic plane), where a much larger number of sources are seen, they are closer on average, and a large fraction of those are plain stars. This gave me heart failure during the 2012 summer visit until I realized this. YSO candidates are bright and red, generally. There are other CMDs you can try.  After we include some optical data, there will be even more CMDs we can try.  
  
=Data Tables, part 2=
+
'''Specific questions/tasks for you''':
 +
In his paper, Xavier was not using our region. His plots WILL look different than ours. But can you find points from IC417 that are in the same region as the YSOs in Xavier's plots?
 +
#His fig 2 has w1-w2 on the y axis and w2-w3 on the x axis. Make this plot in IRSA Viewer. Do we have objects in the same place as the YSOs?
 +
#His fig 4,left is the same, but it doesn't look much like ours. Why? (Hint: what region is plotted?)
 +
#His fig 4,right has w1 on the y axis and w1-w3 on the x axis. Make this plot in IRSA Viewer. Do we have objects in the same place as the YSOs?
 +
#BONUS: Keep going. Do our versions of his plots look like his? Why or why not?
 +
#BONUS #2: Read in our massive, full (all 29,000 sources) bandmerged catalog and make more plots. You will need the tbl file with all the -9s in it -- the tbl file requires there to be an actual value in each "cell" of the tbl file in order to be valid.
  
  
 +
=Image Inspection=
  
OK, now we need to do some more advanced things with data tables, not necessarily limited just to those in Excel.
+
<font color="red">DONE.</font>
  
'''Big picture goal''': More on manipulating data tables. Cope with source list proliferation. ds9 regions files.
+
'''Why?''' OK, we've picked sources based on color (or, rather, Xavier did). For each of the sources in which we are interested (= Xavier's sources plus the literature YSOs), are they really point sources in the images?  (AKA, Do you believe what the computer is telling you?)  Will you believe the computer if it says that there is a detection there, especially at 22 um?
  
'''More specific shorter term goals''': Look at sources in WISE image. Learn how to use ds9 regions files. Possibly identify sources that might have Spitzer data in prep for photometry.
+
'''Relevant links for reference''': [http://irsa.ipac.caltech.edu/applications/finderchart/ FinderChart]
  
'''Tasks and Questions for you''':  
+
'''Process''' (what we already did):
#For each of the ''*known*'' objects, you have the RA/Dec - find some of the objects in the images you obtained above. (Hint: you want a ds9 regions file: [[file:brc38knownysos.reg.txt]] is the file for just the known ysos. The file off the DVD that has "withnames" in the filename also prints the row number on top of the region.) Take notes on any that look like the photometry may be corrupted or that you can easily dismiss as galaxies or other contaminants now that you are looking at better and/or different data than they had before. <font color="green">TEST SAMPLE: the first 4 previously known objects in the 'interesting' list (row numbers 1127, 1144, 1352, 1682)</font> (hint to find them in the image: they are sorted by, and therefore numbered by, RA). Which objects have a WISE match? Which might we worry about?
+
#Assemble list of sources in which we are interested from work above.
#BONUS ONLY IF YOU ARE INTERESTED IN BANDMERGING ... For each of the known YSOs (identified in the 'interesting' file), you have the RA/Dec - find the same objects in the big WISE catalog. Which objects are the matches? What constitutes a 'match'? Are there any with no matches?  Spot check a few of my matches between strictly literature catalogs. Did I match them correctly? Which ones are the same between papers and which are new to just one paper?
+
#Feed list to FinderChart and load POSS, 2MASS, and WISE images. Watch the size of the images you retrieve because it matters for context and automatic stretching that FinderChart does.  
#Now, start to pull together stuff from this step plus those above. You can plot RA/Dec of everything. Here, I've done this both in an x/y plot and overplotted on the image (click to get a big one). The first one has several types of objects (defined in plot itself) plotted just in a graph; the second one just has the "sources of interest" (==previously identified YSOs+new candidate YSOs), overplotted on the WISE-1 image (the green circle is the 20 arcmin radius circle that defines our region of interest.  
+
#Inspect each image. Is it really there at all bands? Is it a point source? Remember the reason that the source is on the list in the first place. (This is encoded in the stuff I gave you.) I expect a source that Xavier selected to have some WISE data, because he started from WISE data. Stars that are Halpha-selected may in fact NOT be detected in WISE. Resolution matters.  
<gallery widths="100px" heights="100px">
+
#Since we are looking for IR excesses, what the image looks like in 2MASS and WISE is the most important. It may well not be there in POSS, but that won't affect our SEDs because (a) we aren't using photometry from POSS, and (b) the optical images we have (or more precisely, the catalogs) go deeper than POSS.
file:Brc38where1jul2013.png
+
#For each source, check and see if we all agree. Ideally, reconcile differences, but this may be best done in concert with SED assessment in a few steps.
file:Brc38where2jul2013.png
 
</gallery>
 
Why are there some regions where WISE sources are missing? Are they really missing, or just missing from the catalog? Why are the Spitzer sources where they are? Why is there a patch of black in the center of the plot on the left (hint: Beltran et al.)?
 
#Can you identify which objects are likely to be in the region of Spitzer coverage? (Hint: I would do this using ds9 regions files and the Spitzer mosaics.) You will need this in order to complete the next section.
 
  
Things to note:
 
*We did a cone search on the wise catalog, and Xavier made a square mosaic. So we 'lose' the corners. which is fine; we have a ton of other things to worry about with the objects we have.
 
*There are far more sources seen at w1 that w4 (and you should know why by now!) :) most of the WISE sources are nicely on sources seen in w1; there are far fewer sources in the w4 image (as per large-scale image inspection above!).
 
  
'''For completeness''': The WISE catalog provides some matches to 2MASS, but it is unclear to me exactly where those matches come from, like which sources out of the 2MASS catalog did they use (which error flags did they keep, or did they just look for any matches in the 2MASS catalog?). When I take the WISE catalog's 2MASS matches and compare it to the 2MASS catalog I pull out of Gator myself, I find about 3% fewer matches than the WISE catalog does. I use a matching tolerance of 1 arcsec to match up sources. These 'extra' 3% must be either objects matched to the WISE source that are more than 1 arcsec away, or with a different set of error flags than I would use coming out of 2MASS. What this means in practice is that: (a) we can keep and use the WISE catalog's matches to the 2MASS sources; (b) we should remember this caveat, and if we notice any 2MASS data downstream from here that is weird (like a mismatch in the SED), then we should go back and check those 2MASS matches by hand with the original 2MASS catalog.
+
=Data Tables (part 2)=
  
=Doing Spitzer photometry=
+
<font color="green"><strike>DO THIS!</strike></font> <font color="red">DONE! </font>
  
<font color="red">DONE for the test set.</font> (Ultimately need to do for all sources of interest with Spitzer data - look at batch processing ("source list") photometry in APT.)
+
'''Why?''' For each of the sources we care about, we need to make SEDs so that we can decide if these sources have IR excesses. We also need to make CMDs/CCDs too. Getting data tables into Excel is the first step in that process.
  
OK, this step is going to take the longest, be the most complex, and involve the most steps out of everything (so far, anyway!).
+
'''Relevant links for reference''': [http://www.youtube.com/watch?v=nCJ3ctOGvNk YouTube video] on what tbl files are, how to access them, and specifically how to import tbl files into xls. (10min)
  
'''Never just trust that the computer has done it right. It probably did what you asked it to do correctly, but maybe you asked it to do the wrong thing. '''Always''' make some plots to test and see if the photometry seems correct.'''
+
'''Process''': Get "workingcatalog-interesting" and "workingcatalog-all" into Excel, with all columns divided appropriately.
  
'''Big picture goal''': Understand what photometry is, and what the steps are to accomplish it.  Ultimately, do Spitzer photometry on a source-by-source basis for the 'interesting' sources. Understand the units of Spitzer images. Understand how to assess if your photometry makes sense.
+
'''Hints and Advice''':
 +
Note that many data tables come with many, many, many lines (like more than 100) at the top explaining what the contents of the file are. These are useful for keeping with the file (like a FITS header is useful to keep with the image), but when reading it into Excel, you may wish to delete all but a note to yourself about what the file is, and the headers of the data columns themselves. Personally, I recommend generally keeping the original file and naming subsequent files similar names. For example, iphas.original.txt, iphas.xlsx, etc.
  
'''More specific shorter term goals''': For now, just do Spitzer photometry in all bands for a short list of test guys. Assess whether your photometry seems right.  
+
I made a catalog which has all the photometry for just the ~200 sources in which we are interested. It's useful (as before) to keep track of why the sources are in the list. Values for the "whyhere" column are combinations of 2-letter codes:
 +
*xp = xavier found it from PhotVis processing (x=Xavier, p=PhotVis)
 +
*xw = xavier found it from the allWISE processing (x=xavier, w=wise)
 +
*ha = Jose et al found it (and you corrected the positions for it) because it is an Halpha star (ha=Halpha)
 +
*ih = IPHAS tagged it as bright in Halpha (=possibly young)
 +
*ob = Meyer & Macak found it (and you corrected the positions for it) because it is an OB star (ob=OB)
 +
*cs = Carbon star.
 +
You will find some like 'xpxwha', which means Xavier found it in both of his processings (xp,xw), *and* it is an Halpha star (ha). There are many that have just one code.
  
'''Relevant links''':
+
*'''CAUTION 1:''' There are multiple files from me with everything in the region (long) and files with just the things in which we are interested (short) -- meaning the literature-identified plus the new Xavier-identified. Look at the filename and contents, and ask questions until you are sure you are using the right file.
*[[Units]]
+
*'''CAUTION 2, AND THIS ONE'S A BIGGIE''': '''These catalog files generally have a mixture of detections and limits, measurements and errors, flux densities and magnitudes.''' You will need to be careful in importing this into Excel. The data are all Vega mags; some have errors and some have limits.
*[[Photometry]]
 
*[[I'm ready to go on to a more advanced discussion of photometry]]
 
*[[Aperture photometry using APT]], specifically [[Aperture_photometry_using_APT#Looking_for_a_cookbook.3F|this]], which is the closest thing to a cookbook I will give you. <font color="orange">THIS IS THE PAGE THAT HAS THE STEPS AND THE APERTURE/ANNULUS COMBINATIONS AND APERTURE CORRECTIONS IN IT</font>
 
*[http://www.youtube.com/watch?v=_w_5DgB0vKw YouTube video on using APT], including calculating the number APT needs.  (15 min because it starts from software installation and goes through doing photometry.)
 
*[http://www.youtube.com/watch?v=vmn4zX0bRrU YouTube video on photometry in general] (from NITARP tutorials)
 
*[http://www.youtube.com/watch?v=5lXAWfBW_NQ YouTube video overview of APT] (from NITARP tutorials)
 
 
 
To start, we should decide as a group which small set of sources to measure, and have everyone measure the same sources. We will then compare all of our measurements among the whole group. Ultimately, we will need to measure photometry for everything we care about that falls in the Spitzer maps. <font color="green">'''NEARLY ARBITRARILY''', I've picked 5384, 3704, 4009, 3896 as some good test particles.</font>
 
 
 
The measurements you get from the Spitzer images are in flux density, e.g., they will come in Jy (microJy or milliJy). It is easier to compare measurements if you convert these to magnitudes first. Ultimately, you need magnitudes for use in color-color and color-mag diagrams anyway. You will also need to convert these into the right units for addition to the SEDs. For now, just convert them to magnitudes. See [[Units#Units_of_Spitzer_Photometry]] and [[Central wavelengths and zero points]] for the numbers and formulae you need.
 
 
 
'''Steps''':
 
#obtain a ds9 regions file for the YSO candidates surviving to this point. (should have from tasks above)
 
#obtain the Spitzer mosaics (should have from tasks above)
 
#For each source that we care about in the image, identify x, y in each of the 4 IRAC channels and at least the first MIPS channel (24 microns). '''CAUTION: it is NOT going to be the same x, y in each image''', and the sky coverage will NOT be the same for each channel (meaning that if the source is not in I1 it may be in I2, I4, and M1 but not I3.  Sources WILL have the same RA and Dec, of course. Note that the image, when loaded into APT, is NOT north-up. There are three ways past users came up with to find the object in the image:
 
##load the image into ds9. put north up. find the object. now find the object in the image in APT.
 
##load the image into ds9. put north up. find the object. note the x and y. type the x and y into APT.
 
##under APT's tools, look for an option like "object locator" and type in the coordinates. It should be ##h##m##s and -##d##m##s format. One person in 2012 could not make this work. Most of the rest seemed to be able to make this work.
 
#While you are doing this, make note of the properties in the image of each source; you will need this downstream. Does it look clean or corrupted by a nearby object, an instrumental artifact, bright nebulosity, etc.?
 
#Go load the image into APT. Explore the parameters so that you understand what is going on. When you are ready to get to work, Measure photometry for all the sources in this image. Make sure the units work out such that you get the right numbers. Repeat for each channel, each Spitzer pointing.
 
#Add the flux density measurements for the Spitzer bands to your copy (mini copy?) of the master catalog for the corresponding source. ('bandmerging' by hand!)
 
#For making CMDs/CCDs, you need magnitudes. For making SEDs, you need flux densities. Sometimes you get magnitudes from archives, and sometimes you get flux densities. You need to be able to convert fluently between these quantities. So, convert the flux densities to magnitudes for later use. M=2.5 log (Fvega/F)... see [[Units]]
 
#When comparing multiple teams' measurements of the brightness of an object, it is easier to do if converted to magnitudes first.
 
 
 
'''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?
 
#Does the addition of the Spitzer points change your opinion on which YSO candidates are going to survive to the end of this process?
 
#Look at the new photometry with a critical eye. Which points look like they should be double-checked?
 
  
=Investigating the images of the objects=
+
'''BONUS''': Try making some color-color or color-magnitude diagrams. Example. Make a new column for W1-W4 and program Excel to do the math for you. Plot W1 vs. W1-W4. Make sure the axes go in the correct direction such that brighter objects are at the top. How does this look different than the plot of everything in the field that you made a few steps above using the full WISE catalog? Why is this?
 
 
'''Big picture goal''': Understand why we need to look at the images of each of our short list of candidates and get started actually doing it and weeding. Also look at any previously identified objects that were not selected by the color cuts.
 
 
 
'''More specific shorter term goals''': Figure out how to get images and/or find these things in our images. Calibrate your eyeball for the various images/resolutions/telescopes to figure out what is extended/corrupted/galaxy-like and what isn't. Drop the bad objects off our candidate YSO list.
 
 
 
You will need to obtain images of the 'interesting' objects in WISE, POSS, and 2MASS. You can do this using the IRSA [http://irsa.ipac.caltech.edu/applications/finderchart/ FinderChart], or the big images from before coupled with ds9 regions files. Either way, it takes time; I think it goes much faster with FinderChart. You can submit a batch list of targets. For the objects that have Spitzer data, you will also need to examine these images, but presumably in the APT step above, you have already done some if not all of this image assessment.  For each of these image sets, it will take a while to calibrate your eyeball, so you will probably need to do the whole list, and then go back and redo the first several or so to be sure that you have it right. 
 
 
 
<font color="green">'''Test set''':</font> This list represents a set of things not in BRC 38 that I deliberately picked so as to show you the range of things you might find in BRC 38, but are of a wider variety than we are likely to find in BRC 38. Some are deliberately tricky. After you do these, feel free to start on the BRC 38 set. [[file:imagetestsetblank.xlsx]] also see [[file:imagestestsetblank.tbl.txt]], which is a tbl file of this list, suitable for bulk uploading to FinderChart or other IRSA tools with this look-and-feel.
 
 
 
'''Relevant links''': 
 
*[[How can I get data from other wavelengths to compare with infrared data from Spitzer?]] 
 
*[[Resolution]] (specifically some of the concrete examples there)
 
*[http://irsa.ipac.caltech.edu/applications/finderchart/ IRSA finder chart] itself (direct link)
 
*[http://www.youtube.com/watch?v=4RHS497XeHQ YouTube video on using Finder Chart]. To use the small images from FinderChart to also examine larger images, download the FinderChart thumbnail images as FITS files, load them and the larger image(s) into ds9, pick one of the small finder chart images, and then pick 'Frame/Match/Frame/WCS'. All will snap to alignment with North up, on the same scale, with the target object in the center.
 
 
 
'''Questions for you''' (NB: these are questions that you should consider for each source when examining each BRC 38 object, not just the test set here):
 
#Which objects are still point sources at all available bands? Keep good notes on this!
 
#Which are instrumental artifacts? Or instrumental hiccups?
 
#Which might have corrupted photometry?
 
  
 
=Making SEDs =
 
=Making SEDs =
  
WARNING: lots of math and programming spreadsheets here too... '''you WILL do this more than once to get the units right!'''
+
<font color="green"><strike>DO THIS!</strike></font> <font color="red">DONE! </font>
  
'''Big picture goal''': Understand how to convert magnitudes back and forth to flux densities. Understand what an SED is and why it matters.
+
'''Why?''' For each of the sources we care about, we need to make SEDs so that we can decide if these sources have IR excesses. Let's do this!
  
'''More specific shorter term goals''': Program a spreadsheet to convert between mags and flux densities.
+
BRACE YOURSELF: lots of math and programming spreadsheets (You may have already have developed some of these skills via the [http://coolwiki.ipac.caltech.edu/index.php/IC_417_Summer_visit_logistics#Excel_to_know shortlist of stuff I sent in April]. If not, this is the time to learn!)  here... '''you WILL do this more than once to get the units right!'''
Make at least one SED yourself. 
 
  
Make sure you understand how to get the fluxes from the magnitudes. This is not easy to do right the first time, so you will get the wrong answer the first few times you try.
+
'''Relevant links for reference''':  
 
+
*[[Units]] - THIS IS A SUPER IMPORTANT PAGE.
'''Relevant links''':  
 
*[[Units]]  
 
 
*[[SED plots]]  
 
*[[SED plots]]  
 
*[[Central wavelengths and zero points]]
 
*[[Central wavelengths and zero points]]
 
*[[Studying Young Stars]]   
 
*[[Studying Young Stars]]   
  
We will ultimately need to make SEDs for everything, but for purposes of this example, let's work with the <font color="green">same test set of four as we worked with for Spitzer photometry above: 5384, 3704, 4009, and 3896.</font> Start with just one. You will ultimately plot log (lambda*F(lambda)) vs log (lambda) -- see the [[Units]] page. It will take time to get the units right, but once you do it right the first time, all the rest come along for free (if you're working in a spreadsheet). Spend some time looking at the SEDs. Look at their similarities and differences. Identify the bad ones, and discuss with the others why/whether to drop them off the list of YSO candidates.  See also stuff above about data at other wavelengths, and include literature/archival data from other sources where appropriate and possible. Make sure to keep careful track of those things that are limits rather than detections.
+
'''Process''': Program a spreadsheet to convert between mags and flux densities. Make at least one SED yourself.  Even if you don't get to the point of making SEDs, make sure you understand how to get the fluxes from the magnitudes. This is not easy to do right the first time, so you '''will''' get the wrong answer the first few times you try.
 +
 
 +
We will ultimately need to make SEDs for everything, but for purposes of this example, let's work with these three objects off the first few on our shortlist: 052532.00+345835.7, 052532.08+345815.2, 052532.62+344000.0.  Start with just one. You will ultimately plot log (lambda*F(lambda)) vs log (lambda) -- see the [[Units]] page. It will take time to get the units right, but once you do it right the first time, all the rest come along for free (if you're working in a spreadsheet). Spend some time looking at these SEDs. Look at their similarities and differences. Make sure to keep careful track of those things that are limits rather than detections. (Build skills for next step.)
  
 
Another try at explaining:
 
Another try at explaining:
*''What do you have?'' UBVRIriHalpha, JHK, WISE data in Vega mags. IRAC, MIPS data in microJanskys.
+
*''What do you have?'' UBVIriHalpha, JHK, WISE, Spitzer data, all in Vega mags.  
*''What do you need to get?'' everything into Jy, which are units of Fnu. Then convert your Fnu in Jy into Fnu in cgs units, ergs/s/cm2/Hz, so multiply by 10^-23. Then convert your Fnu into Flambda in cgs units, so multiply by c/lambda^2, with c=2.99d10 cm/s and lambda in cm (not microns!).  Then get lambda*Flambda by multiplying by lambda in cm.  Plot log (lambda*Flambda) vs. log (lambda).
+
*''What do you need to get?'' everything into Jy, which are units of Fnu -- look up how to convert between mags and flux density ([[Units]] page and [[Central wavelengths and zero points]]). Then convert your Fnu in Jy into Fnu in cgs units, ergs/s/cm2/Hz, so multiply by 10^-23. Then convert your Fnu into Flambda in cgs units, so multiply by c/lambda^2, with c=2.99d10 cm/s and lambda in cm (not microns!).  Then get lambda*Flambda by multiplying by lambda in cm.  Plot log (lambda*Flambda) vs. log (lambda).
*Once you make your first SED correctly, the rest are easy. But that first one is hard.
+
*Once you make your first SED correctly, the rest are easy. But that first one is hard!
*Then you need to look through each of the SEDs and decide which look like you expect, which need photometry to be checked, and which seem unlikely to be legitimate YSOs. This is a judgement call, and your judgement will improve with time as you gain some experience.
+
*Ultimately, you need to look through each of the SEDs and decide which look like you expect, which need photometry to be checked, and which seem unlikely to be legitimate YSOs. This is a judgement call, and your judgement will improve with time as you gain some experience. (This is also the next step.)
 +
 
 +
You can do all of this in one massive spreadsheet such that you do the calculations for all ~200 SEDs at once. This is the power of Excel. Or, you can make one at a time. (You will probably need to plot one at a time anyway, because stupid Excel.)  You can start from the Excel you yourself created in the prior task, or from mine. Your call.
 +
 
 +
AT MINIMUM, the goal here is to get at least a 2MASS+WISE SED just for the three sources I'm asking about here. Therefore, you may wish to start from the most pared-down version of the Excel spreadsheets I've provided. You can always do more if you are feeling ambitious (e.g., doing optical through 22 um, or doing more SEDs than just these 3).
  
 
'''Questions for you''':
 
'''Questions for you''':
#What do the IR excesses look like in your plots?  Do they look like you expected? Like objects in Monday's ppt or elsewhere?
+
#What do the IR excesses look like in your plots for these three example sources?  Do they look like you expected? Like objects in Monday's ppt or elsewhere?
#Find some SEDs of things you know are ''not'' young stars for comparison - pick some with zero IR color. (You may be able to find some sources with zero color among the previously identified YSOs). What do they look like?
+
#BONUS, '''If you made more SEDs:''' For comparison, find these objects and look at their SEDs: 052743.28+343156.5 052839.40+344008.5. Do you expect them to have a large excess based on [3.4]-[22]? What do they look like? Why are we considering these objects?
  
 
=Assessing SEDs =
 
=Assessing SEDs =
  
Now that you've made some SEDs, we need to next look at them with a critical eye.  
+
<font color="green"><strike>DO THIS!</strike></font> <font color="red">FIRST PASS DONE! Needs a second pass...</font>
  
'''Big picture goal''': Understand what to expect in a YSO SED and how to discard objects for having questionable SEDs (or put them on the list for checking source matching, photometry, etc).
+
'''Why?''' Now that you've made at least one SED, you know how to do this. We will wave our magic wand and assume you can do it, given enough time, for all 200 sources of interest. With some help from me, then, to jump that barrier in the limited time we have here at Caltech, we need to next look at the SEDs from all 200 sources of interest with a critical eye. They will not all be clean and neat. We will need to fold in information learned from the image assessments.
  
'''More specific goals''': Examine the SEDs for all of our candidate objects. Use them to further evaluate the quality of the YSO candidates from the YSO candidate list.
+
'''Big goal''': Understand what an SED is and why it matters. Understand what to expect in a YSO SED and how to discard objects for having questionable SEDs (or put them on the list for checking source matching, photometry, etc).
  
'''Relevant links''':  
+
'''Relevant links for reference''':  
 
*[[Studying Young Stars]]   
 
*[[Studying Young Stars]]   
 
*the detailed object-by-object discussion in the appendix of the [http://lanl.arxiv.org/abs/1105.1180 cg4 paper].  
 
*the detailed object-by-object discussion in the appendix of the [http://lanl.arxiv.org/abs/1105.1180 cg4 paper].  
 +
*[http://irsa.ipac.caltech.edu/applications/finderchart/ FinderChart] to check images on the fly
  
<font color="green">'''Test set''':</font> This list represents a set of things not in BRC 38 (they actually are all BRC27) that I deliberately picked so as to show you the range of things you might find in BRC 38, but are of a wider variety than we are likely to find in BRC 38. Some are deliberately tricky. After you do these, feel free to start on the BRC 38 set using the SEDs you made in the prior step. [[file:sedtestsetblank.xlsx]] and [[file:brc27trainingjustSEDs.pptx]]
+
'''Process Overview''': Examine the SEDs for all of our candidate objects. Use them to further evaluate the quality of the YSO candidates from the YSO candidate list. Combine with notes from the image assessment (or redo image assessment on the fly) to decide if each is a good candidate. Identify the bad ones, and discuss with the others why/whether to drop them off the list of YSO candidates.  Look at their similarities and differences. Make sure to keep careful track of those things that are limits rather than detections. After you get through the SED assessment, we will reconvene and compare all our notes.  Then, we will have a set of objects in which we are interested, and we should have (will have) notes on each of the objects, obtained from the image check and the SED check. We need to next collate all of these such that we can tag objects as "unlikely to be real YSOs", or "literature YSOs (that may or may not have a disk)", or "still surviving as new YSO candidates".
  
<font color="green">'''For the BRC 38 set,'''</font> after you make all the SEDs, you will need to spend some time really looking at the SEDs -- all of them! -- but for now, return to the set of four test SEDs you made above. Look at their similarities and differences. Identify the bad points, and discuss with the others why/whether to drop them off the list of YSO candidates. See also stuff above about data at other wavelengths, and include literature/archival data from other sources where appropriate and possible. Make sure to keep careful track of those things that are limits rather than detections. Compare your notes on SEDs with notes on images (e.g., if it's tagged "iffy" in images and "iffy" in SEDs, chances are excellent that it is not a good candidate).
+
More mechanics of process:
 +
Get the file with all the SEDs in it from the Box drive. We will do the first 9 as a group. Then you should work as a 2 or 3-person team and go through each of the objects you're assigned and make notes about what you see. There is a blank Excel file in the Box drive for you to use, or maybe we should use a Google doc to collect responses.   (Ideally would have at least 5 teams of 2 or 3, and have at least 2 teams do each source. For 200 sources, that's at absolute minimum ~30 per team to have just one team per object.)
  
'''Questions for you''':
+
'''Questions''' to think about for each source: Does it look like a YSO SED? Does it look like the data weren't tied to the correct source or there were spatial resolution problems? Discuss with your partner about whether or not you believe each source, and why. Do you believe each point in the SED? If not, why not? Don't forget to compare your notes on SEDs with notes on images (e.g., if you decide it is "iffy" in images AND "iffy" in SEDs, chances are excellent that it is not a good candidate).  Keep good notes on this!
#Which objects look like clear YSO SEDs? Which objects do not? Keep good notes on this throughout BRC 38!
+
 
#What's the deal with this one (why does it look like this)? (In my SED, the y-axis units are cgs units [sorry], *=FTN data, +=optical literature data, diamonds=2mass, circles=irac, stars=WISE, arrows=limits, and boxes=MIPS if they exist, which they don't here.)
+
'''Advice:'''
[[file:chauhan109sed.png]]
+
#Limits in SEDs. Sometimes the source is too bright or too faint for these catalogs. In either case, the catalogs will often report, in essence, "I don't know how bright this thing really is, but I can tell that it must be brighter or fainter than this." That is what a limit means. The limits can be important in the SEDs -- because we are combining catalogs with different sensitivities, there may very well be objects that are undetected. Limits can also help us determine if the source is correctly matched across bands -- detected at a particular brightness but also having a limit at a nearby band that is much below that detection suggests a source mismatch.
 +
#Accreting young stars, or stars that are rotating quickly (often because they are young) are bright in Halpha. If Halpha is much above the rest of the SED, that's OK, and in fact a GOOD THING, because that is more evidence that the star is young. That is why the Halpha point is colored red in my SEDs.
 +
#Remember that in the context of IR excesses, 2 to 22 microns is the most important. There may be wackiness in the optical, and it may matter (especially if there is a mismatch between sources) but if UKIDSS J doesn't match with 2MASS J, that's less of an issue than if, say, IRAC 3.6 microns doesn't match with WISE 3.4 microns, because we care more about the IR side of the SED.
 +
#Black triangles = IPHAS ri. Black plus signs = Jose et al. UBVI Red triangle = Halpha (which means that bright is ok). Black diamonds = 2MASS. Green squares = UKIDSS. black stars = WISE. blue circles = IRAC.
  
 +
=CMDs and CCDs, part 2=
  
Answer: This source is near a bright nebulous patch in the WISE images that either is being inappropriately tagged as a point source (with its flux densities attached to this source) or whose brightness is contaminating the photometry beyond recovery. The Spitzer data are critical for sorting out what is going on here. And I still don't know what is going on with the optical data - it's apparently wrong for this source, but this is the best possible match given the information we have in the literature, so maybe the people who wrote the paper with the optical data screwed something up either in bandmerging or in their photometry.
+
<font color="green"><strike>DO THIS!</strike></font> <font color="red">DONE, at least with the results of the first pass above. </font>
  
=Assembling the Keepers and Duds=
+
'''Why?''' We have now weeded the objects in which we are interested to get rid of the things that really have problems. We now have a shortlist of things that we are starting to believe may be YSOs. We have a lot of ancillary data, and we can do more checking using these data to see how confident we are in these objects, so that we can refine our list of true YSO candidates vs. junk.
  
'''Goal:''' Make progress towards assembling final list of things we think are real YSO candidates and those we think are junk.
+
''We will reassess on the fly, but most likely, we will have everyone make one plot (like we did for the SEDs) and then we will wave our magic wand and assume you can make these plots, given enough time, for our entire catalog, and highlight the sources of interest. With some help from me, again, I will make several CMDs and CCDs and we will talk about them as a group.''
  
By this point, you have (will have) a set of objects identified from the literature or from Xavier, and you should have (will have) notes on each of the objects, obtained from the literature check, the image check, and the SED check. Collate all of these such that you can tag objects as "unlikely to be real YSOs", or "literature YSOs (that may or may not have a disk)", or "still surviving as new YSO candidates".
+
'''Process''':  By this point you should have a list of things that have survived tests.  You can make a wide variety of CMDs and CCDs with these objects highlighted. We will then go through each of them and decide what to believe.
  
=Revisiting CMDs and CCDs=
+
Make a WISE color-mag diagram such as one of the ones you made earlier, but this time do it in Excel. Overplot the survivors of the image and SED tests on this diagram. Where do they fall? Are they where you expect them to be? You may wish to plot the WISE data for *everything* and then just overplot the interesting ones. Or you may wish to just plot the interesting ones, and look at WISE plots for comparison. Tag any of the survivors as less likely if they aren't where they should be.
  
'''Goal:''' We have more data, so we should use it to refine our list of true YSO candidates vs. junk.
+
Repeat for 2MASS color-color and color-mag diagrams.  Don't forget about reddening. Are the sources where you expect them to be?
  
By this point you should have (will have) a list of things that have survived tests. We have optical data for a lot of these objects. You can make optical CMDs and see if the "literature YSOs (that may or may not have a disk)" and "still surviving as new YSO candidates" fall in the 'right place' in these diagrams. For context, take all the optical data we have for all the objects in the region and plot r vs r-i from the IPHAS data. Overplot the survivors on this diagram. Are they where they should be (above the ZAMS)? Do this again, but for r-Halpha vs. r-i.  Are the survivors where they should be (substantially above the unreddened main sequence locus)? Tag any of the survivors as less likely if they don't meet these criteria.
+
We have optical data for a lot of these objects. You can make several different possible optical CMDs and see if the "literature YSOs (that may or may not have a disk)" and "still surviving as new YSO candidates" fall in the 'right place' in these diagrams. For context, you could take all the optical data we have for all the objects in the region and plot r vs r-i from the IPHAS data. Overplot the survivors on this diagram. Are they where they should be (above the ZAMS)? Do this again, but for r-Halpha vs. r-i.  Are the survivors where they should be (substantially above the unreddened main sequence locus)?
  
 
=Analyzing SEDs=
 
=Analyzing SEDs=
  
'''This is advanced, and we may not get here.''' 
+
<font color="green">DO THIS.</font>
  
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 at all?)
+
'''Why?''' There are empirically defined groupings of SED shapes -- Class 0s and Class Is are the most embedded (presumably youngest); Class IIIs are the least embedded (presumably oldest). How do our new YSOs compare to this? Have we mostly found Class IIs?
 +
 
 +
'''Process''': 
 +
Add a new column in Excel to calculate the slope between 2 and 22 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 WISE-4 detections.  (For very advanced folks: ''fit'' the slope to all available points between K and WISE-4.  How does this change the classifications, if at all?)
 
*if the slope > 0.3 then the class = I
 
*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 > -0.3 then the class = 'flat'
Line 323: Line 304:
 
*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?
+
#How many class I, flat, II and III objects do we have? What are any implications for apparent ages?
 
#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?
 +
#How do those locations compare to the Camargo et al Fig 19 cluster positions and ages?
  
 
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.
 
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.
 +
 +
=Going back to check the literature=
 +
 +
<font color="green">DO THIS (if we can).</font>
 +
 +
'''Why?''' We did a pretty thorough literature check a few months ago, but (a) it's not infallible, and (b) astronomers have kept on publishing since then. For each of the objects we are asserting are new YSOs, we should go back and check the literature to be sure, e.g., that someone else didn't just publish a spectrum that says its a carbon star (meaning, not a young star).
 +
 +
'''Process''': Go back into SIMBAD and search for each of our sources. Has anyone has done anything on them before? Are we the first ever on our planet to care about this source? Keep careful notes!
 +
  
 
=Putting this in context a little: Methodology=
 
=Putting this in context a little: Methodology=
  
This step is important for this particular project, because of the nature of the existing literature for the objects we are studying. Again, we may or may not get to this before you leave California.
+
<font color="green">DO THIS (if we can).</font>
  
'''Big picture goal''': Understand how what we did is different than what others (Chauhan, Choudhury, (Rebull/Johnson)) did with the IRAC (IRAC+MIPS) data to find young stars.
+
'''Why?''' Other people have looked for YSOs here before. Need to understand how what we are doing is different, and why we are finding different objects.
  
'''More specific shorter term goals''': Knowing what you do now, go back and reread Chauhan et al. and Choudhury et al. Do a detailed comparison of our method for finding young stars and that from those two papers.  
+
'''Process''': Knowing what you do now, go back and reread Jose et al. (2008). Make a detailed comparison of our method for finding young stars and that from the Jose et al. paper.  
  
'''Relevant links''': [[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]] and [[C-CWEL Journal Club]].
+
'''Relevant links for reference''': [[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''':
 
'''Questions for you''':
#What are the steps (cookbook-style) that Chauhan et al. used to find YSOs?
+
#What are the steps (cookbook-style) that Jose et al. used to find YSOs?
 
#What were our steps?  
 
#What were our steps?  
 
#How are they different?   
 
#How are they different?   
Line 346: Line 337:
 
=Putting this in context a little: Science=
 
=Putting this in context a little: Science=
  
'''Goal:''' put our work in context with other literature on BRC38 and other star-forming regions from the literature.
+
<font color="green">DO THIS.</font>
  
How many YSOs with IR excess did we see? How many literature YSOs did not have IR excesses? Do we have any evidence that the YSOs from the literature are not actually YSOs? How many new YSOs did we see? What is the fraction of Class I/flat/II/III? How do those fractions compare to what was found by C-WAYS in BRC 27?
+
'''Why?''' We've been doing a lot of nitty gritty work with the data. But now it's time to back up and look at the big picture again.
 +
 
 +
'''Goal:''' put our work in context with the literature.
 +
 
 +
'''Process''':
 +
#Go back and look at Camargo's figure. Overlay the surviving YSOs and Camargo's clusters on an image. Did we find YSOs in their clusters? Why or why not? Can you think of reasons why we would/wouldn't find them?
 +
#How many YSOs with IR excess did we see? How many literature YSOs did not have IR excesses? Do we have any evidence that the YSOs from the literature are not actually YSOs? How many new YSOs did we see? What is the fraction of Class I/flat/II/III?  
  
 
=Writing it up!=
 
=Writing it up!=
  
'''Goal:''' We need to write an AAS abstract and then the poster, and if we're lucky, a paper!
+
<font color="green">DO THIS.</font>
 +
 
 +
'''Why?''' Now that we have completed a lot of work, we need to tell other people what we did, and what we found out about the Universe that no one else knows yet.
 +
 
 +
'''Goal:''' We need to write an AAS abstract and then the poster.
  
 
We need to include:
 
We need to include:
 
#How the data were taken.
 
#How the data were taken.
 
#How the data were reduced.
 
#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 IR properties are of the previously identified YSOs here, 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.
+
#What the IR properties are of the new sources we have found, 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.
+
#Whether we found YSOs in the clusters from Camargo.
 
 
Take inspiration for other things to include from other Spitzer papers on star-forming regions in the literature.
 

Latest revision as of 01:50, 18 June 2015

This page is an updated version of the Working with the C-CWEL data page (and to some extent the Working with the HG-WELS data page), which was an update of the Working with the C-WAYS data page, which was an update of the Working with the BRCs page, which was an update of the Working with CG4+SA101 page, which was an update of the Working with L1688 page. This page was developed and updated specifically for the 2015 IC 417 team visit.

Please note: NONE of these pages are meant to be used without applying your brain! They are NOT cookbooks! This is presented as a linear progression because of the nature of this page, but we have already done some things "out of order", and moreover, chances are excellent that you will go back and redo different pieces of this at different stages of your work.

FOR REFERENCE: IC 417 Bigger Picture and Goals

FOR REFERENCE: IC 417 Box Disk Contents. Includes instructions on how to force your computer to read any files with an extension you don't recognize (.tbl, .reg).

FOR CONTEXT: I know we have a wide range of ages and capabilities here. There are things tagged "BONUS" in here - this means "if you get to this point and need something to do while everyone else catches up, work on this." You can also do this later, at home, when you are reviewing what we did this summer. You need not do it here and now, or even necessarily at all. But it will give you a deeper understanding of what is going on.

Useful Positions

(just for reference)

We are studying a square that is ~1 deg on a side, centered on 5:28:00 34:30:00.

Why? (a) Because we are looking for YSOs. (b) Because Camargo says there are several clusters of young stars in this region, and so we ought to be able to find some.

Relevant links for reference: IC 417 Bigger Picture and Goals

Obtaining the imaging data

DONE (but be sure you have the files you need!)

Why? Need to figure out what data are in this region from which we might obtain photometry (=quantitative measures of brightness of objects) to use to look for IR excess sources.

We found imaging data for this region from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008, but we can only get our hands on imaging data from DSS, WISE, 2MASS, GLIMPSE, and IPHAS. We have already used FinderChart and other IRSA tools. We have already used Skyview at Goddard. We have already used ds9.

Big goal: Learn how to get images so that you can do this in the future without me.

Process: Either re-pull FITS images for yourself for our region in DSS, 2MASS, and WISE, or get them from the Box drive. You'll need this for the next step. BONUS: Spitzer/IRAC (GLIMPSE), and IPHAS. (I don't have images for UKIDSS.) NB: GLIMPSE and IPHAS on the Box disk do not cover the whole region -- you'll have to pull these images yourself if you need them over a different region.

Relevant links for reference:

Investigating the big mosaics

DO THIS! DONE!

Why? There is astrophysics in understanding what is bright/faint in each band. Spatial resolution is going to play a role downstream.

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, and you should plan on investing some time doing this section. Some aspects of this were already discussed in the context of the Resolution worksheet.

Big goal: Understand what is part of the sky and what is an artifact (e.g., not part of the sky). Recognize how the images differ among the various bands, and why. (NB: this has come up during more than one telecon, which is why this task is here!) Understand (remind yourself) which survey has the lowest (worst) spatial resolution, and which has the best.

Relevant links for reference:

Process: Load the images into a viewer of your choice, ds9 or IRSA Viewer. Compare the images. Answer the questions below.

Hints and tips: You may find it helpful to make 3-color images to more directly compare images in exactly the same region. Zoom in/out. Play with color stretches to bring out detail in the images.

Questions for you:

  1. MOST IMPORTANT of these questions: Compare the mosaics across the bands. What changes? What stays the same? Why? (This is a DEEP question! See also next questions.)
  2. 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: why?) Are there more stars in the regions of nebulosity, or less? Why?
  3. What is saturated? Are the same objects saturated in all bands? What are some other instrumental effects you can see?
  4. Notice the pixel scale. Which survey has the lowest resolution (biggest pixels)? (BONUS: is that the same as the native pixels for the survey? You will need to Google, or go back to your IC 417 Resolution Worksheet notes.)
  5. Make a three-color image. Do the stars match up? Does the nebulosity?
  6. BONUS: 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 -- check the proposal for the number. If it helps, there are 3.26 light years in a parsec.)

Obtaining the catalog data and bandmerging across catalogs

DONE

Why? We need photometry (=a quantitative measure of brightness) of our sources. Others have already done photometry for us so we don't have to. We need to make the matches across catalogs -- no one else has ever done this before, by which I mean identified which sources in this region are seen in each one of these surveys, and tied the measurements together. (Think about that for a bit -- no one else has ever done this before...)

We found data for this region from WISE, 2MASS, Spitzer/IRAC (GLIMPSE), UKIDSS, IPHAS, and Jose et al. 2008. We have already used FinderChart and other IRSA tools to retrieve 2MASS and WISE (and Spitzer) catalogs.

Big goal: Learn how to get catalogs so that you can do this in the future without me. Understand what bandmerging is and why we need to do it.

Relevant links for reference:

The process of merging the bands across catalogs is called "bandmerging." I did this for you because it would be a GIGANTIC pain in Excel (especially for 30,000 sources), or (worse) by hand. I"ve heard TopCat can do it easily, but I've never used that.

Process (What I did):

  1. Download catalogs from these sources over our region.
  2. Using a computer, load in catalogA. Then, for each of the sources in catalogB, metaphorically sit on each source in catalogB and look for a match in catalogA. If I find a match, associate those sources. If I do not find a match, sometimes I added the entire source to the catalog, and sometimes I just dropped it. (There are a LOT of sources here, many we do not care about, so having each and every source in here is less important than it might be.)
  3. Now have catalogA+catalogB. Do same for each source in catalogC, such that I merge in catalogC with catalogA+B. Repeat for catalogC, etc.
  4. Given ensemble catalog, look for matches with Xavier's list of interesting sources. Tag them in the database.
  5. Repeat for Jose et al. 2008 Halpha stars, OB stars, and IPHAS' list of Halpha stars.

After this process, I have about 29,000 objects in a master catalog, about 200 of which we care about based on other steps below. Remember that we are interested in the ENTIRE set of {things Xavier tagged as possibly young from the AllWISE catalog} PLUS {things Xavier tagged as possibly young from his own PhotVis reprocessing of the WISE data} PLUS {things Jose et al. tagged as Halpha stars} PLUS {things Meyer & Macak tagged as OB stars} PLUS {things IPHAS tagged as bright in Halpha}.

Previously identified sources

NOW COMPLETELY DONE.

Why? Others have gone before us, and it pays to learn from them rather than reinvent the wheel.

Big goal: Understand what has already been studied and what hasn't in the region we care about.

Relevant links for reference: 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 and IRSA Viewer


Process (what we did before):

  1. Search ADS, SIMBAD.
  2. Identify literature of relevance.
  3. Read literature.
  4. Extract from it the data we care about.
  5. For data tables of sources obtained via non-electronic detectors (even some electronic detectors), assess how good the positions are. Can we blindly match these sources to the ensemble catalog (which has positions better than an arcsec)?
  6. If not, use FinderChart to investigate each source by hand to 'correct' its position to be one that can be merged blindly with the rest of the catalog.
  7. Then, merge in the literature observations (in this case, optical multiwavelength catalog from Jose et al for everything they detected), and conclusions about objects (in this case, list of Halpha stars from two places, list of OB stars in essence from 2 places).
  8. Tag the interesting objects as interesting in the database so we can find them again.

Process (what to do now) and questions:

  1. Load in one of the big images of your choice into ds9 or IRSA Viewer.
  2. Get the regions files that have all the literature sources and overlay them. (You probably want to do them one at a time and delete each one before loading the next.) Where are they in the image?
  3. Delete any regions you have loaded, and get the regions file that has the cluster locations from Camargo et al. and overlay them.
    1. One file is the FSR clusters as reported in Camargo et al., with the radii as reported in Camargo et al. Table 1. You should overplot this, compare it to the figure (or the file with the Camargo F19 clusters) and think, "Holy crap these are a lot smaller than they show in Fig 19!" Yep. I don't know what is going on either. BONUS: go reread Camargo and see if you can figure out why.
    2. Load the file with the F19 clusters marked. Can you see the clusters their computer found by you yourself looking at the distribution of point sources in the image by eye? They used 2MASS to find these clusters, so you may wish to look first in JHK to see if you can find them by eye. Looking in WISE is also useful -- are they apparent there? They might not be obvious to you. Either way, are you more or less confidence that Camargo et al. (and references therein) have actually identified clusters? Just because their computer said it and they said it in their paper does not mean it is right. You need to decide if you believe them. (Their confidence is high enough that they published it, so that should tell you that they believe it. To rigorously decide if you believe them, you need to read their description of what they did in their paper and decide if you believe that. Yes, that's a double bonus task.)
  4. Delete any regions files you have loaded, and get the regions file that has all the "sources in which we are interested" and overlay them. Where are they in the images? (Heads up Garrison! :) This is what you wanted to do!)

Hints and Advice: The files on the box drive are:

  • CamargoF19Clusters.reg = the clusters with positions as reported in Camargo et al., with sizes corresponding to what I can see in their Fig 19 (to the accuracy I can read it off the figure).
  • FSRtable1.reg = the FSR clusters as reported in Camargo et al., with the radii as reported in Camargo et al. Table 1.
  • carbonstars.reg = the one carbon star we know about
  • interestingthings20150604.reg = all the sources in which we are interested (nothing dropped yet) -- DON'T LOAD THIS UNTIL YOU HAVE LOADED AND ABSORBED ALL THE REST OF THESE HERE because there are a lot of these sources and they in essence drown out the rest of the things here, in no small part because they overlay many of the other symbols.
  • iphashalphastars.reg = all the objects reported by IPHAS as being bright in Halpha
  • josehalphastars.reg = all the objects Jose et al. report as being bright in Halpha
  • obstars.reg = all the OB stars from the literature we could find. BONUS: Kronberger1 is shown in Camargo et al. F 19 as having an OB star in it. We don't have this star in our list. Can you go figure out what this object should be and where it comes from? We can add it to our list of objects in which we are interested.
  • ourbigregion.reg = just for reference, in case you are using images other than mine -- this is a region file that defines the region that we are studying, e.g., the region covered in Camargo et al. F 19.

Data Tables (part 1) and Color-Color and Color-Magnitude Diagrams (part 1)

DO THIS! DONE!

Why? Xavier found sources with YSO-like colors by making a bunch of CMDs and CCDs and selecting objects from these diagrams. It behooves us to get a sense of what he did. (And, we will need to make more CMDs/CCDs downstream.)

Big goal: Learn how to manipulate data tables using IRSA Viewer for now (because it's easier for a quick plot and because it handles 29,000 sources more elegantly than Excel does). Make some of the plots Xavier made when he selected 'interesting' sources. Do our plots look like his from his paper?

Relevant links for reference:

Process: Go get a WISE catalog for our region from IRSA, not me. Look at the data tables and Xavier's paper (available on the Box drive) to identify what you should plot. Make some plots that he made and see how our region compares to the regions he used in his most recent paper.

Advice and Hints: Remember that a plain star should have zero infrared color for basically any combination. (At least, it is 0 as long as the color is (shorter wavelength) minus (longer wavelength) !) You may find that W3-W4 is notably NOT zero for rather a lot of objects, because the only objects seen at W3 or W4 at the distances we are talking about here are the ones notably bright at W4, so they all are brighter than plain stars at W4. This is going to be a different morphology than a, IRAC color-color diagram (I1-I2 vs I3-I4 plot from somewhere else in the galactic plane), where a much larger number of sources are seen, they are closer on average, and a large fraction of those are plain stars. This gave me heart failure during the 2012 summer visit until I realized this. YSO candidates are bright and red, generally. There are other CMDs you can try. After we include some optical data, there will be even more CMDs we can try.

Specific questions/tasks for you: In his paper, Xavier was not using our region. His plots WILL look different than ours. But can you find points from IC417 that are in the same region as the YSOs in Xavier's plots?

  1. His fig 2 has w1-w2 on the y axis and w2-w3 on the x axis. Make this plot in IRSA Viewer. Do we have objects in the same place as the YSOs?
  2. His fig 4,left is the same, but it doesn't look much like ours. Why? (Hint: what region is plotted?)
  3. His fig 4,right has w1 on the y axis and w1-w3 on the x axis. Make this plot in IRSA Viewer. Do we have objects in the same place as the YSOs?
  4. BONUS: Keep going. Do our versions of his plots look like his? Why or why not?
  5. BONUS #2: Read in our massive, full (all 29,000 sources) bandmerged catalog and make more plots. You will need the tbl file with all the -9s in it -- the tbl file requires there to be an actual value in each "cell" of the tbl file in order to be valid.


Image Inspection

DONE.

Why? OK, we've picked sources based on color (or, rather, Xavier did). For each of the sources in which we are interested (= Xavier's sources plus the literature YSOs), are they really point sources in the images? (AKA, Do you believe what the computer is telling you?) Will you believe the computer if it says that there is a detection there, especially at 22 um?

Relevant links for reference: FinderChart

Process (what we already did):

  1. Assemble list of sources in which we are interested from work above.
  2. Feed list to FinderChart and load POSS, 2MASS, and WISE images. Watch the size of the images you retrieve because it matters for context and automatic stretching that FinderChart does.
  3. Inspect each image. Is it really there at all bands? Is it a point source? Remember the reason that the source is on the list in the first place. (This is encoded in the stuff I gave you.) I expect a source that Xavier selected to have some WISE data, because he started from WISE data. Stars that are Halpha-selected may in fact NOT be detected in WISE. Resolution matters.
  4. Since we are looking for IR excesses, what the image looks like in 2MASS and WISE is the most important. It may well not be there in POSS, but that won't affect our SEDs because (a) we aren't using photometry from POSS, and (b) the optical images we have (or more precisely, the catalogs) go deeper than POSS.
  5. For each source, check and see if we all agree. Ideally, reconcile differences, but this may be best done in concert with SED assessment in a few steps.


Data Tables (part 2)

DO THIS! DONE!

Why? For each of the sources we care about, we need to make SEDs so that we can decide if these sources have IR excesses. We also need to make CMDs/CCDs too. Getting data tables into Excel is the first step in that process.

Relevant links for reference: YouTube video on what tbl files are, how to access them, and specifically how to import tbl files into xls. (10min)

Process: Get "workingcatalog-interesting" and "workingcatalog-all" into Excel, with all columns divided appropriately.

Hints and Advice: Note that many data tables come with many, many, many lines (like more than 100) at the top explaining what the contents of the file are. These are useful for keeping with the file (like a FITS header is useful to keep with the image), but when reading it into Excel, you may wish to delete all but a note to yourself about what the file is, and the headers of the data columns themselves. Personally, I recommend generally keeping the original file and naming subsequent files similar names. For example, iphas.original.txt, iphas.xlsx, etc.

I made a catalog which has all the photometry for just the ~200 sources in which we are interested. It's useful (as before) to keep track of why the sources are in the list. Values for the "whyhere" column are combinations of 2-letter codes:

  • xp = xavier found it from PhotVis processing (x=Xavier, p=PhotVis)
  • xw = xavier found it from the allWISE processing (x=xavier, w=wise)
  • ha = Jose et al found it (and you corrected the positions for it) because it is an Halpha star (ha=Halpha)
  • ih = IPHAS tagged it as bright in Halpha (=possibly young)
  • ob = Meyer & Macak found it (and you corrected the positions for it) because it is an OB star (ob=OB)
  • cs = Carbon star.

You will find some like 'xpxwha', which means Xavier found it in both of his processings (xp,xw), *and* it is an Halpha star (ha). There are many that have just one code.

  • CAUTION 1: There are multiple files from me with everything in the region (long) and files with just the things in which we are interested (short) -- meaning the literature-identified plus the new Xavier-identified. Look at the filename and contents, and ask questions until you are sure you are using the right file.
  • CAUTION 2, AND THIS ONE'S A BIGGIE: These catalog files generally have a mixture of detections and limits, measurements and errors, flux densities and magnitudes. You will need to be careful in importing this into Excel. The data are all Vega mags; some have errors and some have limits.

BONUS: Try making some color-color or color-magnitude diagrams. Example. Make a new column for W1-W4 and program Excel to do the math for you. Plot W1 vs. W1-W4. Make sure the axes go in the correct direction such that brighter objects are at the top. How does this look different than the plot of everything in the field that you made a few steps above using the full WISE catalog? Why is this?

Making SEDs

DO THIS! DONE!

Why? For each of the sources we care about, we need to make SEDs so that we can decide if these sources have IR excesses. Let's do this!

BRACE YOURSELF: lots of math and programming spreadsheets (You may have already have developed some of these skills via the shortlist of stuff I sent in April. If not, this is the time to learn!) here... you WILL do this more than once to get the units right!

Relevant links for reference:

Process: Program a spreadsheet to convert between mags and flux densities. Make at least one SED yourself. Even if you don't get to the point of making SEDs, make sure you understand how to get the fluxes from the magnitudes. This is not easy to do right the first time, so you will get the wrong answer the first few times you try.

We will ultimately need to make SEDs for everything, but for purposes of this example, let's work with these three objects off the first few on our shortlist: 052532.00+345835.7, 052532.08+345815.2, 052532.62+344000.0. Start with just one. You will ultimately plot log (lambda*F(lambda)) vs log (lambda) -- see the Units page. It will take time to get the units right, but once you do it right the first time, all the rest come along for free (if you're working in a spreadsheet). Spend some time looking at these SEDs. Look at their similarities and differences. Make sure to keep careful track of those things that are limits rather than detections. (Build skills for next step.)

Another try at explaining:

  • What do you have? UBVIriHalpha, JHK, WISE, Spitzer data, all in Vega mags.
  • What do you need to get? everything into Jy, which are units of Fnu -- look up how to convert between mags and flux density (Units page and Central wavelengths and zero points). Then convert your Fnu in Jy into Fnu in cgs units, ergs/s/cm2/Hz, so multiply by 10^-23. Then convert your Fnu into Flambda in cgs units, so multiply by c/lambda^2, with c=2.99d10 cm/s and lambda in cm (not microns!). Then get lambda*Flambda by multiplying by lambda in cm. Plot log (lambda*Flambda) vs. log (lambda).
  • Once you make your first SED correctly, the rest are easy. But that first one is hard!
  • Ultimately, you need to look through each of the SEDs and decide which look like you expect, which need photometry to be checked, and which seem unlikely to be legitimate YSOs. This is a judgement call, and your judgement will improve with time as you gain some experience. (This is also the next step.)

You can do all of this in one massive spreadsheet such that you do the calculations for all ~200 SEDs at once. This is the power of Excel. Or, you can make one at a time. (You will probably need to plot one at a time anyway, because stupid Excel.) You can start from the Excel you yourself created in the prior task, or from mine. Your call.

AT MINIMUM, the goal here is to get at least a 2MASS+WISE SED just for the three sources I'm asking about here. Therefore, you may wish to start from the most pared-down version of the Excel spreadsheets I've provided. You can always do more if you are feeling ambitious (e.g., doing optical through 22 um, or doing more SEDs than just these 3).

Questions for you:

  1. What do the IR excesses look like in your plots for these three example sources? Do they look like you expected? Like objects in Monday's ppt or elsewhere?
  2. BONUS, If you made more SEDs: For comparison, find these objects and look at their SEDs: 052743.28+343156.5 052839.40+344008.5. Do you expect them to have a large excess based on [3.4]-[22]? What do they look like? Why are we considering these objects?

Assessing SEDs

DO THIS! FIRST PASS DONE! Needs a second pass...

Why? Now that you've made at least one SED, you know how to do this. We will wave our magic wand and assume you can do it, given enough time, for all 200 sources of interest. With some help from me, then, to jump that barrier in the limited time we have here at Caltech, we need to next look at the SEDs from all 200 sources of interest with a critical eye. They will not all be clean and neat. We will need to fold in information learned from the image assessments.

Big goal: Understand what an SED is and why it matters. Understand what to expect in a YSO SED and how to discard objects for having questionable SEDs (or put them on the list for checking source matching, photometry, etc).

Relevant links for reference:

Process Overview: Examine the SEDs for all of our candidate objects. Use them to further evaluate the quality of the YSO candidates from the YSO candidate list. Combine with notes from the image assessment (or redo image assessment on the fly) to decide if each is a good candidate. Identify the bad ones, and discuss with the others why/whether to drop them off the list of YSO candidates. Look at their similarities and differences. Make sure to keep careful track of those things that are limits rather than detections. After you get through the SED assessment, we will reconvene and compare all our notes. Then, we will have a set of objects in which we are interested, and we should have (will have) notes on each of the objects, obtained from the image check and the SED check. We need to next collate all of these such that we can tag objects as "unlikely to be real YSOs", or "literature YSOs (that may or may not have a disk)", or "still surviving as new YSO candidates".

More mechanics of process: Get the file with all the SEDs in it from the Box drive. We will do the first 9 as a group. Then you should work as a 2 or 3-person team and go through each of the objects you're assigned and make notes about what you see. There is a blank Excel file in the Box drive for you to use, or maybe we should use a Google doc to collect responses. (Ideally would have at least 5 teams of 2 or 3, and have at least 2 teams do each source. For 200 sources, that's at absolute minimum ~30 per team to have just one team per object.)

Questions to think about for each source: Does it look like a YSO SED? Does it look like the data weren't tied to the correct source or there were spatial resolution problems? Discuss with your partner about whether or not you believe each source, and why. Do you believe each point in the SED? If not, why not? Don't forget to compare your notes on SEDs with notes on images (e.g., if you decide it is "iffy" in images AND "iffy" in SEDs, chances are excellent that it is not a good candidate). Keep good notes on this!

Advice:

  1. Limits in SEDs. Sometimes the source is too bright or too faint for these catalogs. In either case, the catalogs will often report, in essence, "I don't know how bright this thing really is, but I can tell that it must be brighter or fainter than this." That is what a limit means. The limits can be important in the SEDs -- because we are combining catalogs with different sensitivities, there may very well be objects that are undetected. Limits can also help us determine if the source is correctly matched across bands -- detected at a particular brightness but also having a limit at a nearby band that is much below that detection suggests a source mismatch.
  2. Accreting young stars, or stars that are rotating quickly (often because they are young) are bright in Halpha. If Halpha is much above the rest of the SED, that's OK, and in fact a GOOD THING, because that is more evidence that the star is young. That is why the Halpha point is colored red in my SEDs.
  3. Remember that in the context of IR excesses, 2 to 22 microns is the most important. There may be wackiness in the optical, and it may matter (especially if there is a mismatch between sources) but if UKIDSS J doesn't match with 2MASS J, that's less of an issue than if, say, IRAC 3.6 microns doesn't match with WISE 3.4 microns, because we care more about the IR side of the SED.
  4. Black triangles = IPHAS ri. Black plus signs = Jose et al. UBVI Red triangle = Halpha (which means that bright is ok). Black diamonds = 2MASS. Green squares = UKIDSS. black stars = WISE. blue circles = IRAC.

CMDs and CCDs, part 2

DO THIS! DONE, at least with the results of the first pass above.

Why? We have now weeded the objects in which we are interested to get rid of the things that really have problems. We now have a shortlist of things that we are starting to believe may be YSOs. We have a lot of ancillary data, and we can do more checking using these data to see how confident we are in these objects, so that we can refine our list of true YSO candidates vs. junk.

We will reassess on the fly, but most likely, we will have everyone make one plot (like we did for the SEDs) and then we will wave our magic wand and assume you can make these plots, given enough time, for our entire catalog, and highlight the sources of interest. With some help from me, again, I will make several CMDs and CCDs and we will talk about them as a group.

Process: By this point you should have a list of things that have survived tests. You can make a wide variety of CMDs and CCDs with these objects highlighted. We will then go through each of them and decide what to believe.

Make a WISE color-mag diagram such as one of the ones you made earlier, but this time do it in Excel. Overplot the survivors of the image and SED tests on this diagram. Where do they fall? Are they where you expect them to be? You may wish to plot the WISE data for *everything* and then just overplot the interesting ones. Or you may wish to just plot the interesting ones, and look at WISE plots for comparison. Tag any of the survivors as less likely if they aren't where they should be.

Repeat for 2MASS color-color and color-mag diagrams. Don't forget about reddening. Are the sources where you expect them to be?

We have optical data for a lot of these objects. You can make several different possible optical CMDs and see if the "literature YSOs (that may or may not have a disk)" and "still surviving as new YSO candidates" fall in the 'right place' in these diagrams. For context, you could take all the optical data we have for all the objects in the region and plot r vs r-i from the IPHAS data. Overplot the survivors on this diagram. Are they where they should be (above the ZAMS)? Do this again, but for r-Halpha vs. r-i. Are the survivors where they should be (substantially above the unreddened main sequence locus)?

Analyzing SEDs

DO THIS.

Why? There are empirically defined groupings of SED shapes -- Class 0s and Class Is are the most embedded (presumably youngest); Class IIIs are the least embedded (presumably oldest). How do our new YSOs compare to this? Have we mostly found Class IIs?

Process: Add a new column in Excel to calculate the slope between 2 and 22 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 WISE-4 detections. (For very advanced folks: fit the slope to all available points between K and WISE-4. How does this change the classifications, if at all?)

  • 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? What are any implications for apparent ages?
  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?
  3. How do those locations compare to the Camargo et al Fig 19 cluster positions and ages?

For very advanced folks: suite of online models from D'Alessio et al. and suite of online models from Robitaille et al.. Compare these to the SEDs we have observed.

Going back to check the literature

DO THIS (if we can).

Why? We did a pretty thorough literature check a few months ago, but (a) it's not infallible, and (b) astronomers have kept on publishing since then. For each of the objects we are asserting are new YSOs, we should go back and check the literature to be sure, e.g., that someone else didn't just publish a spectrum that says its a carbon star (meaning, not a young star).

Process: Go back into SIMBAD and search for each of our sources. Has anyone has done anything on them before? Are we the first ever on our planet to care about this source? Keep careful notes!


Putting this in context a little: Methodology

DO THIS (if we can).

Why? Other people have looked for YSOs here before. Need to understand how what we are doing is different, and why we are finding different objects.

Process: Knowing what you do now, go back and reread Jose et al. (2008). Make a detailed comparison of our method for finding young stars and that from the Jose et al. paper.

Relevant links for reference: 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. What are the steps (cookbook-style) that Jose et al. used to find YSOs?
  2. What were our steps?
  3. How are they different?
  4. Did we recover all of the young stars identified in the literature? Some will not have IR excesses, so those will not be recovered by an IR-based color selection.

Putting this in context a little: Science

DO THIS.

Why? We've been doing a lot of nitty gritty work with the data. But now it's time to back up and look at the big picture again.

Goal: put our work in context with the literature.

Process:

  1. Go back and look at Camargo's figure. Overlay the surviving YSOs and Camargo's clusters on an image. Did we find YSOs in their clusters? Why or why not? Can you think of reasons why we would/wouldn't find them?
  2. How many YSOs with IR excess did we see? How many literature YSOs did not have IR excesses? Do we have any evidence that the YSOs from the literature are not actually YSOs? How many new YSOs did we see? What is the fraction of Class I/flat/II/III?

Writing it up!

DO THIS.

Why? Now that we have completed a lot of work, we need to tell other people what we did, and what we found out about the Universe that no one else knows yet.

Goal: We need to write an AAS abstract and then the poster.

We need to include:

  1. How the data were taken.
  2. How the data were reduced.
  3. What the IR properties are of the previously identified YSOs here, in context with other observations from the literature.
  4. What the IR properties are of the new sources we have found, including objects you think are new YSOs (or objects you think are not), and why you think that.
  5. Whether we found YSOs in the clusters from Camargo.