Working with the HG-WELS data
This page is similar in concept to the summer visit pages for my prior teams (Working with the C-CWEL data; Working with the C-WAYS data page; Working with the BRCs; Working with CG4+SA101 page; Working with L1688) HOWEVER, this page was developed and updated specifically for the 2014 HG-WELS team visit. Because this team has a very different science goal, it is very different, for the most part, than these other pages.
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.
Contents
- 1 Assembling our initial catalog
- 2 Assembling other data from large catalogs
- 3 Checking that the coordinates and photometry make sense, part 1 - image inspection
- 4 Making SEDs
- 5 Checking that the coordinates and photometry make sense, part 2 - SED inspection
- 6 Making CMDs
- 7 Determining excesses
- 8 Big picture again
Assembling our initial catalog
DONE but kept here for reference because it is easy to forget. AAAAND, LET'S DISCUSS THE QUESTIONS BELOW.
Big picture goal: Understand which sources have been studied for these three samples, and what has been measured for them.
We assembled our catalog in the spring from three sources:
- de la Reza's published catalog - biased towards sources bright in the IR
- Carlberg's published catalog - much less biased set of giants assembled without regard to IR or Li, spanning range of vsini
- Carlberg's private communication set of objects mentioned in the literature as Li rich (some of which subsequently vanished from de la reza's papers)
We have a list of 196 unique objects that we assembled, keeping track of where the source was listed. Some objects are listed in more than one of those three places.
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
- HG-WELS Bigger Picture and Goals
Questions for you
- Why is it important to keep track of which stars came from which of these samples?
- Why do we not need to assemble more stars from other places? (Both scientific and practical reasons!)
Assembling other data from large catalogs
PARTIALLY DONE - Luisa did this in their full glory but we need to do a few as a check and so you understand what I did...and so you can do it yourself later on your own for other projects.
Big picture goal: We are ultimately trying to get an understanding of whether or not these stars have excesses. It will further that goal if we accumulate as much data as we can from a variety of sources.
More specific shorter term goals: Use IRSA's catalog search to start assembling multi-wavelength information about these sources. Especially since our sources are (on average) bright, we have more potential catalogs that we can draw on.
Relevant links:
- How can I get data from other wavelengths to compare with infrared data from Spitzer? - though that wiki page focuses more on imaging. We need photometry.
- FinderChart at IRSA
- IRSA in general
- Catalog search at IRSA IMPORTANT AND NEW TO YOU
- Resolution - spatial resolution matters!
- HG-WELS Resolution Worksheet - the worksheet we did in the Spring
- Vizier
- YouTube Video Tutorial from IRSA about catalog searches
More words: Several surveys with archived data covered the whole sky. There are other surveys that just covered part of the sky. We are trying ultimately to determine if these sources have infrared (IR) excesses. We would like to assemble data from as many places as we can to flesh out the SEDs between optical (V-band) and 100 microns (the longest IRAS wavelength). As we spelled out in the proposal, the meat of what we are likely to use is probably going to be WISE 1 and WISE 4, or possibly K and WISE 4. But, as we will see below, having additional data can REALLY help us to assess whether or not we believe the two bands we will use to determine whether or not our sources have IR excesses.
- Get from your email (or assemble yourself) an IPAC table file with all our targets and their positions in decimal ra/dec.
- Go to the catalog search at IRSA
- Ultimately, for this portion of the process, you will want to assemble source lists from 2MASS, WISE, and IRAS. (For the record, I did these plus many more -- those, plus Akari, Denis, both PSC and FSC from IRAS, MSX, SEIP, and certain bright objects by hand in Vizier.) Pick one of 2MASS, WISE, and IRAS to start with.
- Do a multi-object search using that IPAC table file. Make sure to use 1-to-1 matching -- this option finds the source closest to your search position within your given search radius, and returns one line per object, even one line for those things that did not find a match. This greatly helps with the next steps.
- Look at what it gives you in response to your search. It comes up with a plot of distance to your source as a function of source number. Is there a place in the list where it gets much worse? Why is this?
- Save the output of the search to a file. Rename it and put it someplace you can find it.
- Circle back and repeat for the rest of 2MASS, WISE, and IRAS. You will need a smallish radius for 2MASS and a largish radius for WISE and IRAS. (I used, I think, 5 arcsec for 2MASS and 20 arcsec for WISE and IRAS.)
- Note that, as long as you use the same input tbl file every time and choose 1-to-1 matching every time, there is always the same number of lines in the output file. This makes matching across catalogs very easy. Note that all catalogs return the same columns (source name, input ra/dec, matched source id, matched source ra/dec), as well as a wide variety of additional columns. Identify the columns out of these catalogs that you actually need. (Work with the group to identify which columns you need. Hint: the photometric measurements, the errors on them, and the phot quality flags.)
- Start an Excel file. Read in one of the search results tbl files. Delete the columns you don't need. Repeat for the other search results tbl files. Copy and paste very carefully to match the same source across all the catalogs into one Excel sheet, such that in the end you have one row per object with all the relevant resulting information you have discovered about these sources. Save often! This process is sometimes called "bandmerging" because it is merging across bands (wavelengths).
Checking that the coordinates and photometry make sense, part 1 - image inspection
DONE at least a first pass.
Big picture goal: Just because the computer says it, does not make it right. Always check to make sure that the computer is correct. (AKA "count your change.")
More specific shorter term goals: Investigate the images for each source. Do we have the coordinates right? Is it just one point source? This is one of the major goals of our work, to determine if there is "source confusion" at these locations.
Relevant links:
- FinderChart at IRSA
- Resolution - spatial resolution matters!
FLESH THIS OUT
you may need to loop back to the prior step after doing this. i did. make a list of IRAS sources that become more than one piece - major goal of work. note that we identified coordinate issues in this step.
Making SEDs
PARTIALLY DONE - Luisa made full SEDs in their full glory but we need to do a few as a check and so you understand what I did. We may skip this initially and circle back.
WARNING: lots of math and programming spreadsheets here too... you WILL do this more than once to get the units right!
Big picture goal: Understand how to convert magnitudes back and forth to flux densities. Understand what an SED is and why it matters.
More specific shorter term goals: Program a spreadsheet to convert between mags and flux densities. 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:
We will ultimately need to make SEDs for everything, for all bands, but to make this tractable, let's work with just some bands (WHAT) and just a few sources (WHICH? PICK EXTREME SOURCES AND FLESHED OUT ONES. one that vizier padding needed, one IRAS steep non giant, one no disk, one conventional disk). 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 more or less 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, circle back to fix photometry if necessary. Discuss with the others what to do and why. Make sure to keep careful track of those things that are limits rather than detections.
Another try at explaining:
- What do you have? (UBVRI,) JHK, WISE data in Vega mags. IRAS data in Janskys. CHECK
- 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).
- 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 stars. This is a judgement call, and your judgement will improve with time as you gain some experience.
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?
- 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?
Checking that the coordinates and photometry make sense, part 2 - SED inspection
#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.) (Note that this example comes form last year but is still good for us to look at. Then, they were worrying about Spitzer vs. WISE; now we are worrying about WISE vs. IRAS. same idea!)
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.
MAKE LIST OF SOURCES WITH IRAS TOO BRIGHT given wise. Bonus: add RJ line
Making CMDs
OK, fair warning, some math involved, and the start of programming spreadsheets!
Big picture goal: Understand what plots to make. Understand the basic idea of using them to pick out certain objects.
More specific shorter term goals: Make some color-color and color-mag plots using our assembled catalog.
Relevant links:
- Color-Magnitude and Color-Color plots
- Finding cluster members
- Also see slides from my set of talks on Monday.
make k vs k-22 for 2mass, and then merge of 2mass and denis. for detections (not limits). use irsa viewer because then can pick sources. make w1 vs w1-w4 for detections (not limits)
make a table for htem with cat src and lim clearly (more clearly) marked so IRSA Viewer can parse more easily.
reproduce funky color-color from dela reza. make updated version. color-color appropriate?
Determining excesses
calculate chi values for various combinations. identify soruces with excesses in prior plots. are these excesses based solely on one point or is there corroborating evidence for an excess?
Big picture again
for each sub sample, what is IR excess fraction? at what wavelengths?
IRx vs. vsini, A(Li), Vmag?, carbon isotope ratio?