NITARP Day 4: Digging Into Data

Walden studs at Caltech sign-s

David Black and students from Walden School of Liberal Arts at Caltech in Pasadena, CA: July, 2014.

On Thursday, July 31, 2014 my students and I continued our NITARP (NASA/IPAC Teacher Archive Research Program) experience at Caltech. Today we dug deeply into the K-giant data and converted the magnitude data at various wavelengths for our target stars into flux densities. We took the spreadsheet of stars Dr. Luisa Rebull had built and created the necessary formulas to do the conversions and calculations, then charted SEDs (Spectral Energy Distributions) of the 180 + stars in our list. I explained the process for doing this in my last post, when we practiced the process with five stars. Today we charted all of them.

NITARP 9-flux densities

A page from my astronomy notebook written at Caltech. It describes how to convert magnitude data for stars into flux densities in photons per centimeter squared per second for various wavelengths.

We also cross compared the fluxes at different wavelengths, such as comparing all the stars’ fluxes at 3.4 minus 4.6 microns, or J minus K, or 12 minus 22 microns. These differences were charted into color-color diagrams (CCDs) and color-magnitude diagrams (CMDs). I had been doing similar things in my BYU research over the summer, comparing hydrogen alpha narrowband with hydrogen alpha broadband to get a CMD for open clusters in Cassiopeia. Just like the Be stars that were isolated far to the left in my diagram, we were looking for outliers to the right of the main grouping of stars. These would indicate infrared excesses and be the stars we would want to explore further.


Notes on how to interpret color-magnitude diagrams (CMDs) for our data. The WISE mission chose four wavelengths (3.4, 4.6, 12, and 22 microns) to study for very specific reasons. These wavelengths are able to detect dust, gas, near-Earth asteroids, galaxies, brown dwarfs, and other objects that give off specific infrared signatures. Our CMDs are meant to isolate the K-giant stars we are studying from other types of objects such as galaxies and brown dwarfs while showing which stars have real infrared excesses.

Allow me to explain. When an SED is developed, it compares the logarithms of the wavelengths (horizontal axis) versus the logarithms of the flux densities (photons per square centimeter per second hitting the sensors of the WISE or IRAS or 2MASS detectors) at each wavelength. Logarithms are used since the differences between the wavelengths on the missions we’re looking at would produce an exponential curve otherwise, which is hard to analyze. Logarithms turn exponentials into straight lines. Now, on a K-giant SED, the flux density will peak in the orange part of the spectrum (hence the name K-giant). From there on through the red and infrared, what is called the Raleigh-Jean side of the Wien’s Law curve, the line is basically straight (or has a constant slope). So when we take the flux density at say 22 microns and subtract it from the flux density at 4.6 microns for a normal star, the change in slope is zero. This is what we chart, basically, in a CMD. Now it’s a bit more complex than this – really, we use the calculus chain rule and so on. John Gibbs tried to explain this to me, but my calculus is so rusty I doubt I could even do a simple derivative these days.

NITARP 7-real science

Some of my notes during the Caltech visit. Our goal: to create a poster for the AAS conference. But as these notes say, even negative results are useful for science. We found only five stars from this initial pass at the data that match our criteria, probably not enough to draw conclusions from. But with further data and more detailed analysis, perhaps a paper in a refereed journal may be possible.

The upshot of all this is that a normal star with a straight Raleigh-Jean side will show up on a CMD chart near zero. Anything to the right will not be a normal star. Too far to the right and it may be a galaxy (it would be at the bottom right in the CMD) or some other non-stellar object or post-asymptotic branch star (very old orange giant). We were studying young K-giants, just beginning to expand and perhaps consuming their inner planets in the process. So we were looking for a group of stars in the CMDs to the right of the main bunch between about 2.5 and 7 standard deviations from the mean of zero for our chi values. These target stars show more flux at the longer infrared wavelengths than they should have, or, in other words, they have an infrared excess. Yes, we can eyeball an SED and say that it looks like we have a hump or an arm, but these CMDs turn the differences into real numbers we can analyze.

Total Excel star sheet

The whole shebang! This is part of our final Excel spreadsheet with all the calculations that convert the magnitude measures into flux densities, then calculates various Color-Color differences for making CCDs and CMDs. The final two columns (pink and green) calculate the significance of the differences using a Chi test for signal over noise. Those between 2.5 and 7 chi values from the mean are in our target range. The question marks are for those with too large of a chi value.

The end results of all this number crunching (remember, we were looking at about 180 + objects originally, but had eliminated many as being non-stellar) were finally revealed: we had maybe five K-giant stars in our list that fit the criteria of having an infrared excess, a high abundance of lithium, and faster-than-normal rotation. We were hoping for many more. Five doesn’t seem like enough to draw any conclusions.

CCD with marked stars

Color-color diagram (CCD) with all the sources in our list. Normal stars are grouped at the zero-zero area of the diagram. The ones marked with red Xs are too far out to be stars at all. The non-X dots are objects of interest to us. They are stars with infrared excesses that may have consumed their own planets.

OK, that might seem to be disappointing. All this work for only five viable candidates. But as my notes from the day say, in science most results are negative or ambiguous. Even these results have value – they tell us what didn’t work or what needs to be clarified before we try again. Science textbooks make it seem that science is one unbroken string of right answers, but that is far from the truth. If all science ever had were right answers, there would be no cause for scientific revolutions that overthrow the status quo. It’s when the answers don’t make sense or our expectations prove wrong that progress is really made, as long as we stick with it and keep experimenting despite lack of results.

CMDs with iffy stars

Color-Magnitude Diagrams comparing 3.4-22 microns and K-22 microns. The grouping of stars along the zero point is what one would expect for normal stars without infrared excesses. All the star to the right show high IR excesses. The ones circles are non stars, iffy, or just plain weird when looking at their SEDs. The ones to the upper left are based on data that has upper limits but no definite values. Our objects of interest are the uncircled dots and X’s to the right of the main group. These have IR excesses that fall between 2.5 and 7 chi values away.

We have proven one thing, which is that the older De la Resa paper using IRAS data was inaccurate in light of the better WISE and 2MASS data. We found a lot of source confusion, non-stellar objects, and various other problems due to the low resolution of the IRAS data. As for the stars provided by Jolene Carlberg, perhaps if we can add in more K-giant stars, or look further at our data and eliminate noise and errors, more viable stars will emerge and we may yet get a paper out of this. One issue we have to resolve is that some of the data was listed as limits instead of definite values. We also need to search the SINBAD database and elsewhere to find out more on these questionable objects. But for now, we have learned a great deal and done our small part to advance astrophysics. We at least have enough for a scientific poster for AAS. Tomorrow we will work on the educational poster by evaluating how much students have learned.

Elena and Kendal with Luisa

Elena and Kendall with Dr. Luisa Rebull at Caltech, calculating flux densities for K-giant stars in our study using WISE and 2MASS data.

As for my students, they did fairly well today. I helped Rosie work through the spreadsheet issues and conversions. Kendall and Elena worked with some of the other students and with Dr. Rebull to understand the flux density conversions and the color-color diagrams.

Rosie and Elena work on SEDs

Rosie and Elena working on SEDs at Caltech for our HG-WELS study.

We went to lunch as teachers to discuss plans for our educational review tomorrow while the students went to different restaurants and diners around Caltech. Rosie went to the restroom just as we were leaving for lunch but didn’t tell anyone, so each group of students assumed she was with one of the other groups and she got left behind. She called me after I had walked over a mile away, so I had to hoof it back to Caltech, then walk with her until I found some students at a diner nearby. It was a hot day and I was pretty sweaty by the time I got back to the other teachers.

HG-WELS Caltech-s

The entire HG-WELS (Hungry Giants-WISE Excess Lithium Study) group at Caltech: July, 2014.

After we finished for the afternoon, we gathered by the Caltech main sign for group photos. Here are photos of the whole group and of my students and I. We ate supper in Old Town Pasadena again. Teachers ate at an Italian restaurant I had eaten at before when I came down for the Curiosity landing conference. We also got some excellent gelato.

Colorado Blvd

HG-WELS teachers in Old Town Pasadena on Colorado Boulevard.

Jordan and I

My son Jordan and I during my visit to Caltech.

My son Jordan lives in Los Angeles and works for a video rental company that specializes in renting cameras to production companies for filming reality TV shows. He is their Lead Technician, and is an expert at all types of video and audio equipment. He met me at the Comfort Inn and we went out to dinner together at BJ’s Restaurant and Brewhouse in Arcadia. It was my second supper, but the food was excellent. I’ve been here before, having stayed several times at hotels in the area, including the Embassy Suites Hotel across the street when I was the Educator Facilitator for the NASA Explorer Schools program at JPL. We talked about his work and his new camera and how he liked southern California. It was good to see him again. John took some photos of us on my iPad when we got back to Pasadena.

About davidvblack

I teach courses in multimedia, 3D animation, Earth science, physics, biology, 8th grade science, chemistry, astronomy, engineering design, STEAM, and computer science in Utah. I've won numerous awards as an educator and am a frequent presenter at state and national educator conferences. I am part of the Teachers for Global Classrooms program through the U.S. Department of State and traveled to Indonesia in the summer of 2017 as an education ambassador. I learned of the Indonesian education system and taught classes in astronomy and chemistry at a high school near Banjarmasin in southern Borneo. I am passionate about STEAM education (Science, Technology, Engineering, Arts, and Mathematics); science history; photography; graphic design; 3D animation; and video production. This Spaced-Out Classroom blog is for sharing lessons and activities my students have done in astronomy. The Elements Unearthed project ( will combine my interests to document the discovery, history, sources, uses, mining, refining, and hazards of the chemical elements.
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