Friday, July 31, 2009

So Long, Farewell, Auf Wiedersehen, Good-Bye!

It's the last day of summer work! This is my last post! Ahhhh! ;)

Now that I've got my COSMOS data structures, I've gone through and plotted RA-Dec, some star/galaxy classification histograms, and CMDs. I'm also adding an "epilogue" about these to my summer work summary paper.

Classification and RA-Dec

The data includes four parameters by which I can classify stars. From the ACS data, there is the class column, just as in the GOODS data, as well as their own column called mu_class. As far as I have been able to determine by my plots and n_elements(...), the mu_class assigns objects with a class of 0.85 or 0.9 and higher as a star. The redshift catalog had two additional classifier columns, the zp_best and Type. Zp_best is based on redshift data, and based on the histograms, those assigned 0 (stars), correspond to the 1's (stars) according to the Type. The interesting thing is that, when plotted, though it is obvious that my classification of class greater than 0.75 includes a few more stars than their mu_class, that mu_class has a significantly higher number of stars than even the zp/type classification. Also, the zp/type RA-Dec plots show odd wholes in the footprint, as if spheres were subtracted out; I initially supposed that this was the case, with some kind of masking, but it seems rather significant, and I've not been able to find any further documentation explain it.


They look beautiful! At least, until you get down to the I-band; those look a little weird, but it could just be some magnitude limits acting funny-? Perhaps something to investigate further later. The G-R vs R plots are especially nice, and you can see clearly the differences in the stellar cut-offs by looking at the population getting whittled down.

Color-Color Plots

I made a couple of these really quickly, in B-V vs V-I, and you can again see the beautiful narrowing down of the stellar population between the different star-parameters.

Document, Files, etc.

I updated all of my Research document, included a few notes on my directory and file names, and copied it to data03, and eel, as well as e-mailed it to Beth and myself. I also went through and made sure to have copied all of my files in my home folder over to data03, since it's been like a week since I updated that. So, everything is all set, and now I'm kind of sad to be clearing my stuff out of the lab!

But it's been a great summer, and I'm sure I'll do more work in the future.

Au revior,

Tuesday, July 28, 2009

Hurray, COSMOS!

Well, it's been a tiring past few days, but it's finally done! The Cosmos catalogs were giving me some trouble, and the codes to data-structure-ify them were running into a lot of trouble.

All of the nonsense with the RA and Dec columns I sorted out: it turns out the data downloading site added its own two columns of calculated sexigesimal coordinates, in addition to the catalog's RA and Dec columns. Hence the confusion. So I'm just writing these as strings and ignoring them.

I ran into a lot of other troubles with a lot of "null" entries in other columns, so I had to read them in, used a where statement to find the "null"s and replaced them all with "99.9"s. Took a lot of lines of code, and a lot of things to get the structure to co-operate and accept the columns. But, after a lot of help from Beth with de-bugging and some code acrobatics, I got it to work this evening.

There is now a catalog for the ACS COSMOS data (cosmoscat), one for the photometric data (cosmosphotcat), and a merged catalog after spherematching their RAs and Decs (cosmos).

I've also got a pretty whole-survey RA-Dec plot already done! Next to tackle: classhist, comparing my star/galaxy classification parameter to theirs, selecting out stars, cmds, color-color, etc.

Also finished my LaTeX document on GOODS, and it looked great on squid, but when i scp'ed it to eel it turned crappy and images weren't displayed correctly, and i also had some trouble e-mailing the file. This to be checked out later.

Friday, July 24, 2009


So, now that I've finished up my analysis of my GOODS Stars, here are my conclusions:

The spatial distribution of the stars in the GOODS fields, both as a whole and the halo stars alone, is statistically random, showing no significant structures or streaming. To me this means one of two things, or more likely a combination thereof:
a) the stars were formed in the disk and somehow randomized and ejected into the halo
b) the stars are from Milky Way satellites, but the accretion event was so long ago that the tidal streams have settled.

I think (b) could probably account for most of them. I suppose there could be ways of telling, with metallicity or something else, which is the origin of these stars, should that be desired.

Anyway, I've written my results and conclusions up in my paper, and I'm just fine-tuning it now.

I'm moving on to (attempt to) run my process on another set of data, COSMOS- which as far as I can tell has over 1.1 million objects in it... much much larger that GOODS. Thus far it has been an unfruitful attempt, with numerous obstacles in the way of actually obtaining a readable file and getting IDL to process it. I don't know who structured their catalog, but they have made it really inaccessible by writing in the RA and Dec not in decimal form, so much of my difficulty has been getting those columns.

More work on COSMOS to be continued throughout next week.

Wednesday, July 22, 2009

Halo Stars

Nearly done with GOODS stars project!

K-S Test results for Halo Stars:

28th mag: 0.9855 average w/ 0.24225 stdev
27th mag: 0.9988 average w/ 0.20298 stdev
26.5th mag: 0.7996 average w/ 0.3058 stdev

28th mag: 0.9085 ave. w/ 0.18898 stdev
27th mag: 0.68989 ave. w/ 0.20114 stdev
26.5th mag: 0.8457 ave. w/ 0.1335 stdev

The trend towards more randomness in the 28th magnitude is still seen in the halo subset of GOODS stars, and these are not very different from those of the K-S test on the whole stellar catalog.

Given the high values, I'm comfortable gleaning from this that in the northern field the spatial distribution is random. Though the southern field has slightly lower values, they are still within the random-range, and within a standard deviation of the expected probability (based on the previous random vs random trials).

Wrapping Up

Now I'm just adding to the Results section of my Research Document, and I'll be wrapping up the GOODS stars project. Then I'll be playing with the COSMOS data and checking out its star/galaxy population and stellar spatial distribution.

Monday, July 20, 2009

K-S Test Results

Kolmogorov-Smirnov Test
Tests for how similar two data sets are, by measuring the largest distance between the two functions. The IDL function, kstwo, works by inputting two data sets and outputting the K-S statistic "D" and the corresponding "prob". If prob is small, the tests are likely not from the same origin. I ran this test on my data and a couple sets of random data, and taking the mean and standard deviation of numerous trials for comparison. I got the kinds of results I was expecting between the random sets, but got two differing results on the GOODS stars when I included my whole star catalog versus limiting it to the 27th magnitude.


GOODS-N to 27th mag vs. Random 1 (Normalized*, 1 set vs 9 sets)
d-mean: 0.19797699
d-stdev: 0.04482917
prob-mean: 0.69592268
prob-stdev: 0.2092225

*The first time I ran it, I hadn't yet normalized them, so the sets had varying total populations, and resulted in even higher values of d and lower probabilities.

GOODS-N to 28th mag vs. Random 1 (Normalized, 1 set vs 9 sets)
d-mean: 0.089285724
d-stdev: 0.055698492
prob-mean: 0.99998375
prob-stdev: 0.18113585

GOODS-S to 27th mag vs. Random 1 (Normalized, 1 set vs 9 sets)
d-mean: 0.16683391
d-stdev: 0.027475102
prob-mean: 0.84035881
probsigma: 0.12022707

GOODS-S to 28th mag vs. Random 1 (Normalized, 1 set vs 9 sets)
d-mean: 0.12184878
d-stdev: 0.042824080
prob-mean: 0.99533697
prob-stdev: 0.19727988

Random 2 vs. Random 3 (1 set vs 9 sets)
d-mean: 0.14321605
d-stdev: 0.055629589
prob-mean: 0.92319757
prob-stdev: 0.20686308

Random 2 vs. Random 3 (9 sets vs 9 sets)
d-mean: 0.12757371
d-stdev: 0.032610029
prob-mean: 0.98843256
prob-stdev: 0.070053501

Random 4 vs. Random 5 (100 sets vs 100 sets)
d-mean: 0.1610636
d-stdev: 0.046950535
prob-mean: 0.8827874
prob-stdev: 0.18292440


I'm more comfortable going with the statistics done on the GOODS data to the 27th magnitude, since in my work before eliminating the dimmest data points gave me a more stellar sample. This means their likenesses to randomness are lowered. The South field I think is still well within range to call "close to random" at about 84%, given the averages and standard deviations where the sets are known to be random. The North field I can't say quite as confidently, at almost 70%, but it lies at the edge of what I'd call random.

Friday, July 17, 2009


Made it through the week!

Accomplished all of the plots

Took a huge bite out of yesterday's To-Do List. Got all of the multi-plots done in both fields, including the histograms! The only persisting problem was in the smooth plots, for some reason the contour lines only showed up on the first of the 9 plots, while all of the other labels and commands, etc. worked throughout the for-loop. This is a mystery, to be looked at later if need be.

To Do:

Read up on and implement Kolmogrov-Smirnov test
Update Research Document

Thursday, July 16, 2009

Keep to the Code

Today: Spent the majority of the day engulfed in editing and writing code.

Fixed Random Distribution

Beth pointed out to me how I had inadvertently cut off the edges of the field, so this is now fixed. For some reason I kept coming up with errors when I tried to run the code for the southern field.

Made Multi-plots!

Since the northern field worked, I proceeded with that, adding a for-loop and a multi-plot command to run numerous trials and got a 3x3 set of RA-Dec plots, and a data structure saving these trials' data.

Smooth and Significance Histograms

Next on the list was to make the smoothed RA-Dec plots, and the accompanying statistical significance histograms. When I tried to run my code on the random data though, I again ran into errors, and have isolated a problem or two, but not the solutions. I think the next thing I'll try will be to skip over the part of the code that's tripping up and see if I can get the rest of it to work or if there are further issues.

To Do:

Southern random positions, and multi-plot, data structure
Smooth RA-Dec plots for both fields, and significance histograms
finish debugging and get smoothed RA-Dec plots
-make accompanying cumulative histograms
Kolmogrov Smirnoff Test
-to compare trends of random trials and observed data in addition to eye-balling it
Update Research Summary Document
Ditto to Alex's Nap Idea
late night showing of Harry Potter at the iMax: movie and company were great beyond expectations, but caused slight shortage of sleep.

Wednesday, July 15, 2009


Axes fixed

Contour RA-Dec plots are now beautiful.

Random position generator

Given the code to get me going. Set up a randomu and manipulated the arrays to have values within the RA's and Dec's of the GOODS-N field. Spherematched these with actual data positions to accommodate the odd shape of the footprint. Plotted 500 of the random sample of stars (and oplotted the GOODS survey), so check that they overlapped properly. Oddly, the Dec's range was fine, but the outer endges of the RA's got chopped off. Wasn't obvious to me how this happened by looking at the code, so this will be addressed tomorrow.

Random position cont...

-check out why edges got cut off
-make for southern field
-emperical comparison to observed stars' positions

Tuesday, July 14, 2009

Contoured Density Plots

Started off the day going over isochrone images with Beth

The Besancon Model still seems puzzling, showing a lot of faint red stars. The Trilegal looks better, and the isochrone fitted at 20kpc nearly follows the line of stars (great by my standards, since in my limited experience few things have lined up nearly this well, but Beth mentioned some discrepancies). We determined that the disk/halo stars cut-off should be at a v-i of 1.5.
I haven't yet started working the separated stars yet, as I got distracted today...

Distribution, smoothing, significance

Brainstorming ensues. Beth explained how the smoothing worked a little bit, which brought up some minor pixel issues. To get out the edges and contrasts we wanted, I used SEARCH2D to make a pixel map of just 1's and 0's to separate the outer area with no data. The significance ((image-mean)/stddev) was taken of the data, and plotted with the "nodata" area set to 0.0 on the grey-scale. I also made an accompanying histogram of n-sigma; it wasn't Gaussian but it had the right tailing-off-shape.

Went to talk on BLAST-thought it was cool

Contour lines

Adding to the distribution density plot are now contour lines. It took me pretty much all afternoon figuring out and working on the code from Beth to make these show up properly. In the end, with a little typo-spotting help from Gail, I got it to work. I even patted myself on the back a little for going back making the contour lines shift from black to white so that you could still distinguish them on the lighter and darker areas. Only problems are the axes... even more so when I tried to make another plot of the northern field (as I'd been working primarily with the southern one all day, and didn't want the poor guy to feel neglected).

(in no particular order)
Fixing axes

-Go through code again and see if I can't find the problem
-If not, talk to Beth about it
Implement color-cut
Random distribution generator

Monday, July 13, 2009


Finishing up from last week, I made gray-scale RA-Dec density plots, hess-style. Also considering going back to cutting out some of the faintest blue objects.

With some new direction on how to proceed in looking at the distributions of the GOODS stars, I set out with it in mind to select out the disk vs halo stars into two groups. Using our brains for this, I started with an isochrone generated online to check where on the Trilegal model it would fall. I had to convert it from Absolute to Apparent magnitude, using 20kpc as the distance. I was pleased to find that the curve fell along the stars in my hess diagram.

Next is to use magnitude and color limits to pick out the groups of stars and check out their distributions for any kind of structure or randomness.

Friday, July 10, 2009

Enough of this stuff, It's Friday, I'm in love

Yep, it's Friday. And I like that song. ^_^

So, with my nice new star catalogs, as of this morning I have:
1) made RA-Dec plots
2) made CMDs
3) made a histogram of the distribution of apparent magnitudes
4) done the above for the Besancon Model catalog for comparison

The N and S catalogs have 1151 and 1175 stars in them, respectively. In the RA-Dec plots their distribution appears pretty homogeneous across the fields. About 35% of the stars are magnitude 26.5 or brighter, and these have overall the same kind of random distribution, but with some odd voids in areas. (In the future- may consider a random coordinates generator to see the probabilities of distributions, to see if these voids are significant.)
The magnitude distribution of the model is of a similar shape, but with more evenly increasing numbers the fainter the stars, rather than the leap in numbers from brighter to fainter in the GOODS stars.

This afternoon I did a lot:
I started using the Trilegal model as another comparison for a star catalog.
I also learned how to make a Hess diagram, and with a little help from code from Alex and some of Dylan's work, I got it to work by the end of the day.

Further project direction Monday.

Wednesday, July 8, 2009

I'm Baaaaack!

I have returned from the British Isles and returned to work.

Since I had put together my research summary paper before leaving, it was easy to review and jump back in right where I left off. I spent the morning cleaning up a few things in my paper, and then spent most of the day working on polishing up and finalizing my flux-ratio cut-off. By group meeting after lunch I'd made a few plots trying to be more precise with my parameters and sort through the data, systematically eliminating fainter objects that clouded over the color-color plot and getting down to the good stars. By the end of the day I made the final call: up to 1.4 (best at magnitude 26.5 or brighter, but am including up to 28).

That being done, I now have my stars catalog and am going to look at their distributions.