Figures, Tables, and Images
Stephen St.Vincent - Swarthmore College

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30 June 2005
I've updated the line-of-sight velocity contours for all of the time snapshots from yesterday.

In addition, I've made some pages that contain more easily compared shots:
Flared Disk   |   Zone 17   |   Zone 37   |   Zone 58   |   Zone 76   |   Zone 101



29 June 2005
Below are links to galleries of images from D3grid.pro for various zones:
Flared Disk   |   Zone 17   |   Zone 37   |   Zone 58   |   Zone 76   |   Zone 101




28 June 2005

My first emission line profile. The data come from an analytic data set representing a "flared disk" (see below). The tilt angle is 135 degrees and the number of slices is 60.


A line of sight velocity contour for the flared disk analytic distribution.



27 June 2005


Volume contour after adding 2 significant digits to the determination of &theta for each point. It looks much smoother than before (see 16 June 2005).



24 June 2005


Rotation! This is an image of two opposing slices merged together. The simulation has been tilted by 2.6 radians (completely arbitrary number). I've put all of the shots from zone76
here.



23 June 2005


The new histogram using the new definition of emission measure.


Another contour of line-of sight velocity, this time with a tilt angle of &pi


A contour of line-of sight velocity with a tilt angle of zero.
A contour of line-of-sight velocity with a tilt angle of &pi / 2. Notice how the material near the magnetic equator (except for the plasma) has a negative velocity, meaning that it is moving towards the observer.



21 June 2005


A contour plot of line-of-sight velocity with no star rotation or tilt. The observer would be positioned at the top of the plot infinitely (or at least effectively infinitely) far away.



20 June 2005


Histogram resulting from D3grid.pro. This is an emission measure vs. temperature histogram from one slice of the entire star (1/8 of the star in this case). Interestingly, it has some dissimilarities in comparison to the image directly below it.


18 June 2005


The final version of my emission measure histogram, which I sent to Marc Gagne to be sent to ApJ. Pretty, no?


17 June 1005


This is a histogram of the same data as from yesterday, but with the bins shifted to the right by 0.25. The shape has clearly changed.


16 June 2005


This is a contour from D3grid.pro that now takes out the effects of wind from behind the star. The occultion line is jagged, but only because of the way IDL handles the contouring. The next image shows the locations of the data points overlaid, which makes this patently clear.


Occultion image with data points overlaid. It is clear to see that the appropriate points have been zeroed and that it's simply the contouring routine that gives the jagged appearance.


This is the little histogram that caused all the headaches with the volume calculations. And at the end of the day, fixing the volume didn't change the histogram one bit, just as I expected. This is by far my most boring picture to date.


The new resultant volume contour. Notice the symmetry between the top and bottom halves of the image that was lacking in previous images (see 13 June 2005).



14 June 2005


This is an image created using D3grid.pro of zone 76. Here, the slice is of &phi = 4 with 50 divisions. Note that the X-axis now shows how many stellar radii the image would extend with respect to the observer; due to the angle, the slice would actually extend out of the page towards (or away from) the observer. The full scale is still 9 stellar radii, but because this slice is at an angle with respect to the viewer, those 9 stellar radii are be compressed into the 5.5+ seen above. Also note that the image has been reveresed; it is in fact the opposite side from the one I've been using up to this point.



13 June 2005


Contour of emission measure, with the threshold set to Log(T)=7.


A contour of emission measure.


a contour plot showing volume per data point using the new equation for volume.



10 June 2005


A contour plot showing the physical volume represented by each data point, assuming that each volume is a ring through
0 &le &phi &le 2 &pi


A contour plot showing the physical area represented by each data point.



09 June 2005


A look at a different image, zone58, that exhibits the same magnetic field behavior as before. This offers a great view of the field "islands" that I'm getting. Note that the plot title is inaccurate.


08 June 2005


A close-up of a hot plasma region, with magnetic fields included


Temperature contour with full formatting. No magnetic field lines here.


Density contour with full formatting.


Velocity contour with full formatting.




07 June 2005


This is my first all-IDL image. I've used a different color scheme because I like the white background better. My code maintains the aspect ratio for easy image-size adjustments and whites-out the star. In addition, I've thrown in the magnetic field contour lines for reference.



03 June 2005


So it turns out that there was no problem with the spatail distribution of data, just the way I was reading it in. I've fixed that somehow, and the above image is the result of my new "4- point" interpolation, which takes the nearest point in each of the 4 quadrants relative to the pixel and takes the weighted average of those points as the interpolated value. The dimensions of the sample are 500x500. Clearly, the results are better than yesterdays, but still not nearly as good as Origin's. Of particular interest, though, is the slight forking to the very right of the graph, which is seen in Origin's plots but not previously in mine.
02 June 2005


Here is the full image of zone76 using my interpolation. Some wierd stuff is going on near the surface of the star that I can't really explain.
01 June 2005


This is a small portion of zone76 that was processed using my low-budget interpolation instead of origin. Clearly it isn't anywhere near as good, but still my interpolation method works to some extent and can be easily (hypothetically at least) modified to be more accurate. One can also see that the interpolation is better where there's more data, i.e. to the far left of the image.